SEC_data_analysis/docs/search.json at main · gp1981/SEC_data_analysis · GitHub

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[
  {
    "objectID": "setup.html",
    "href": "setup.html",
    "title": "Import required libraries",
    "section": "",
    "text": "Import required libraries\npackages &lt;- c(“tm”, “proxy”,“httr”,“jsonlite”,“tidyverse”, “readxl”,“magrittr”, “kableExtra” ,“tibble”,“knitr”, “here”,“openxlsx”, “furrr”, “zoo”)\nfor (package in packages) { if (!(package %in% installed.packages())) { install.packages(package) }\n# Load the package library(package, character.only = TRUE) }\n\n\nSource required functions\nsource(“../code/Functions/data_retrieval.R”) # Sourcing the data retrieval functions source(“../code/Functions/data_analysis.R”) # Sourcing the data analysis functions source(“../code/Functions/data_visualization.R”) # Sourcing the data visualization functions source(“../code/Functions/utils.R”) # Sourcing utility functions\n\n\nRequired datasets\ndata_dir &lt;- here(“data”)"
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    "title": "Explore data retrieved from SEC",
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    "text": "In this section, we delve into the structure of the SEC data obtained from the API. The data follows a structured format in compliance with SEC reporting standards, utilizing XBRL (eXtensible Business Reporting Language). XBRL is a standardized language designed to enhance the accuracy and reliability of financial reporting.\n\n\nXBRL (eXtensible Business Reporting Language): XBRL is a structured, machine-readable format ensuring consistency and comparability across companies and filings. As specialized language for business and financial data, XBRL enables standardized communication and presentation of financial information. It uses XML (eXtensible Markup Language) to tag financial data with labels that provide context and meaning. This tagging allows for easier analysis, comparability, and extraction of data by both humans and machines.\n\n\n\nConsistency: XBRL ensures consistency in financial reporting by providing a standardized set of tags for financial concepts, making it easier to compare data across different companies and periods.\nEfficiency: The use of XBRL streamlines the process of collecting, analyzing, and disseminating financial information, reducing the need for manual data entry and interpretation.\nTransparency: XBRL enhances the transparency of financial data, as each financial concept is tagged with a specific label, providing clear identification and context.\n\n\n\n\nWithin the SEC data retrieved through the API, XBRL is utilized to structure financial information.\nA basic understanding XBRL1 is necessary for navigating and interpreting the structured financial data retrieved from the SEC. It ensures a standardized approach to financial reporting, facilitating meaningful analysis and comparison.\nFirst, we load the required libraries and files.\n\n\nShow the code\nsource(\"setup.qmd\")          \n\n\nNow, let’s retrieve the necessary objects for data exploration:\n\n\nShow the code\n# Load company_data\ncompany_data &lt;- readRDS(\"company_data.RDS\")\ncik &lt;- readRDS(\"cik.RDS\")\n\n\nThe data retrieved from the SEC API is structured financial data compliant with SEC reporting standards.\nTo navigate through this structure for analysis, consider the following key elements:\n\ncik: The Central Index Key (CIK) is a unique identifier assigned to each company filing reports with the U.S. Securities and Exchange Commission (SEC).\nentityName: This is the name of the company, in our case “JAKKS Pacific, Inc.”\nfacts: The main container for financial data, housing two critical sections:\n\ndei: Contains Document and Entity Information (DEI), providing basic company details.\nus-gaap: Holds financial data following the U.S. Generally Accepted Accounting Principles (GAAP).\n\n\nWithin these sections, financial data is organized as a list of items, each with specific attributes:\n\nConcept: Represents a financial measure or item (e.g., “Assets”) with an associated label and data type.\nFacts: Actual numerical values associated with the concept, with attributes like “value,” “unitRef,” and “contextRef.”\nAttributes: Additional attributes providing context for the data, such as reporting period, currency unit, or data precision.\n\nEffectively analyzing this data involves selecting relevant concepts and Fact, potentially transforming or pivoting the data for further processing and visualization.\n\n\n\nLet’s start by exploring the structure of company_data:\n\n\nShow the code\n# Visualize structure of the company_data \nstr(company_data, max.level = 1) \n\n\nList of 3\n $ company_Metadata:List of 22\n $ company_Facts   :List of 3\n $ company_Concept :List of 7\n\n\nThe output reveals that company_data structure comprises three lists with nested lists, such as company_Metadata with 22 lists.\n\n\n\n\n\n\n\nNote\n\n\nIn R, a list is a powerful data structure that can hold elements of different data types. This flexibility allows each element to be unique and cater to specific data requirements. For the company_data object, the list structure plays a crucial role in organizing various pieces of information, including financial data, company descriptions, and filing details. This heterogeneous nature of the data necessitates a flexible data structure like a list to accommodate these diverse data types. Understanding the organization and structure of the company_data list is essential for effective navigation and extraction of specific information. By grasping the relationships between the list elements, users can efficiently retrieve the desired data elements for analysis and interpretation.\n\n\n\n\nTo access the lists we use the symbol $ in after the object e.g. company_data$company_Metadata.\nNext, we split the company_data into separate lists: company_Metadata, company_Facts, company_Concept.\n\n\nShow the code\n# Split the lists in company_data\ncompany_Metadata &lt;- company_data$company_Metadata\ncompany_Facts &lt;- company_data$company_Facts\ncompany_Concept &lt;- company_data$company_Concept\n\n\nNow, let’s examine the structures and content of these lists:\n\n\nLet’s start with company_Metadata which includes 22 elements: characters, integer, sub-list (or nested list), etc.\n\n\nShow the code\n# Visualize structure of the company_Metadata\nstr(company_Metadata, max.level = 1)\n\n\nList of 22\n $ cik                              : chr \"1009829\"\n $ entityType                       : chr \"operating\"\n $ sic                              : chr \"3944\"\n $ sicDescription                   : chr \"Games, Toys & Children's Vehicles (No Dolls & Bicycles)\"\n $ insiderTransactionForOwnerExists : int 0\n $ insiderTransactionForIssuerExists: int 1\n $ name                             : chr \"JAKKS PACIFIC INC\"\n $ tickers                          : chr [1:2] \"JAKK\" \"JAKP\"\n $ exchanges                        : chr [1:2] \"Nasdaq\" \"OTC\"\n $ ein                              : chr \"954527222\"\n $ description                      : chr \"\"\n $ website                          : chr \"\"\n $ investorWebsite                  : chr \"\"\n $ category                         : chr \"Accelerated filer&lt;br&gt;Smaller reporting company\"\n $ fiscalYearEnd                    : chr \"1231\"\n $ stateOfIncorporation             : chr \"DE\"\n $ stateOfIncorporationDescription  : chr \"DE\"\n $ addresses                        :List of 2\n $ phone                            : chr \"424-268-9444\"\n $ flags                            : chr \"\"\n $ formerNames                      : list()\n $ filings                          :List of 2\n\n\nFor our purpose, the most relevant information of company_Metadata are:\n\ncik, as described above.\nsic, standard industrial classification. The SIC codes were used to classify companies into specific industry segments based on their primary business activities. Each four-digit SIC code represented a different industry or sector.\nsicDescription the description of the standard industrial classification\nname, name of the company\ntickers, identifier a publicly traded company’s stock on a particular stock market\nfiling which includes the filing attributes.\n\nHere the structure of company_Metadata:\n\n\nShow the code\n# Visualize structure of the company_Metadata\nstr(company_Metadata$filing, max.level = 2)\n\n\nList of 2\n $ recent:List of 14\n  ..$ accessionNumber      : chr [1:1003] \"0001185185-24-000477\" \"0001185185-24-000433\" \"9999999995-24-000892\" \"0001185185-24-000367\" ...\n  ..$ filingDate           : chr [1:1003] \"2024-05-08\" \"2024-04-25\" \"2024-04-08\" \"2024-04-08\" ...\n  ..$ reportDate           : chr [1:1003] \"2024-03-31\" \"2024-04-24\" \"\" \"2024-03-29\" ...\n  ..$ acceptanceDateTime   : chr [1:1003] \"2024-05-08T08:20:35.000Z\" \"2024-04-25T15:35:51.000Z\" \"2024-04-09T00:15:13.000Z\" \"2024-04-08T17:15:44.000Z\" ...\n  ..$ act                  : chr [1:1003] \"34\" \"34\" \"33\" \"34\" ...\n  ..$ form                 : chr [1:1003] \"10-Q\" \"8-K\" \"EFFECT\" \"8-K\" ...\n  ..$ fileNumber           : chr [1:1003] \"001-35448\" \"001-35448\" \"333-278220\" \"001-35448\" ...\n  ..$ filmNumber           : chr [1:1003] \"24924366\" \"24875827\" \"24831031\" \"24830448\" ...\n  ..$ items                : chr [1:1003] \"\" \"2.02,9.01\" \"S-3,,2024-04-08 16:15:00\" \"5.02\" ...\n  ..$ size                 : int [1:1003] 5719341 656430 1732 176775 7831 9913 190682 43835 220773 11376283 ...\n  ..$ isXBRL               : int [1:1003] 1 1 0 1 0 0 0 0 0 1 ...\n  ..$ isInlineXBRL         : int [1:1003] 1 1 0 1 0 0 0 0 0 1 ...\n  ..$ primaryDocument      : chr [1:1003] \"jakkspacif20240331_10q.htm\" \"jakkspacif20240424_8k.htm\" \"xslEFFECTX01/primary_doc.xml\" \"jakkspacif20240408_8k.htm\" ...\n  ..$ primaryDocDescription: chr [1:1003] \"FORM 10-Q\" \"FORM 8-K\" \"\" \"FORM 8-K\" ...\n $ files :'data.frame': 1 obs. of  4 variables:\n  ..$ name       : chr \"CIK0001009829-submissions-001.json\"\n  ..$ filingCount: int 140\n  ..$ filingFrom : chr \"1996-06-07\"\n  ..$ filingTo   : chr \"2003-07-02\"\n\n\nThe format of the dataset as printed is not very useful. We see that there are useful information on the forms (e.g. 10K) and dates (e.g. filing dates).\nFor now we will keep it as is and we will come back later on how to improve the readability\n\n\n\ncompany_Facts is relatively simple and is a list of 3 elements.\n\n\nShow the code\n# Visualize structure of the company_Facts\nstr(company_Facts, max.level = 1)\n\n\nList of 3\n $ cik       : int 1009829\n $ entityName: chr \"JAKKS Pacific, Inc.\"\n $ facts     :List of 2\n\n\nFor our purpose, the last element company_Facts$facts is the most relevant one.\n\n\nShow the code\n# Visualize structure of the company_Facts\nstr(company_Facts$facts, max.level = 1)\n\n\nList of 2\n $ dei    :List of 2\n $ us-gaap:List of 508\n\n\nThe us-gaap list includes relevant Facts, containing 487 nested elements. Let’s examine the first five.\n\n\nShow the code\n# Visualize structure of the company_Facts\nFacts_us_gaap &lt;- str(company_Facts$facts$`us-gaap`[1:5], max.level = 1)\n\n\nList of 5\n $ AccountsPayableCurrent        :List of 3\n $ AccountsReceivableNetCurrent  :List of 3\n $ AccruedAdvertisingCurrent     :List of 3\n $ AccruedBonusesCurrent         :List of 3\n $ AccruedEmployeeBenefitsCurrent:List of 3\n\n\nThese elements, to which we will refer as us_gaap_reference, include essential fundamentals of the company and are themselves nested lists. Let’s explore the structure of the first one.\n\n\nShow the code\n# Visualize structure of the company_Facts\nstr(company_Facts$facts$`us-gaap`[1], max.level = 4)\n\n\nList of 1\n $ AccountsPayableCurrent:List of 3\n  ..$ label      : chr \"Accounts Payable, Current\"\n  ..$ description: chr \"Carrying value as of the balance sheet date of liabilities incurred (and for which invoices have typically been\"| __truncated__\n  ..$ units      :List of 1\n  .. ..$ USD:'data.frame':  106 obs. of  8 variables:\n  .. .. ..$ end  : chr [1:106] \"2010-12-31\" \"2010-12-31\" \"2010-12-31\" \"2011-06-30\" ...\n  .. .. ..$ val  : int [1:106] 35886000 35886000 35886000 51537000 85352000 26430000 26430000 26430000 26430000 26430000 ...\n  .. .. ..$ accn : chr [1:106] \"0001157523-11-004475\" \"0001157523-11-006668\" \"0001157523-12-001404\" \"0001157523-11-004475\" ...\n  .. .. ..$ fy   : int [1:106] 2011 2011 2011 2011 2011 2011 2012 2012 2012 2012 ...\n  .. .. ..$ fp   : chr [1:106] \"Q2\" \"Q3\" \"FY\" \"Q2\" ...\n  .. .. ..$ form : chr [1:106] \"10-Q\" \"10-Q\" \"10-K\" \"10-Q\" ...\n  .. .. ..$ filed: chr [1:106] \"2011-08-01\" \"2011-11-09\" \"2012-03-15\" \"2011-08-01\" ...\n  .. .. ..$ frame: chr [1:106] NA NA \"CY2010Q4I\" \"CY2011Q2I\" ...\n\n\nThe output presents the structure of the information related to the first element: AccountsPayable\n\nAccountsPayable: Represents a financial concept within the us-gaap section, specifically referring to “Accounts Payable (Deprecated 2009-01-31).”\n\nlabel: This column represents the financial concept or measure, such as “Accounts Payable (Deprecated 2009-01-31).”\ndescription: A detailed explanation of the concept, providing insight into the carrying value as of the balance sheet date.\nunits: A data frame with 2 observations and 8 variables. The variables include information such as:\n\nend: Indicates the end date of the reporting period associated with the financial data.\nval: Represents the numerical value associated with the financial concept. It includes the unit of measure (e.g., million - “M”).\naccn: Stands for accession number, a unique identifier assigned by the SEC to each submission.\nfy: Represents the fiscal year associated with the financial data\nfp: Represents the fiscal period (e.g., Q3 for the third quarter, FY for the full fiscal year).\nform: Indicates the type of form filed with the SEC (e.g., 10-Q for quarterly reports, 10-K for annual reports).\nfiled: Represents the date on which the form was filed with the SEC.\nframe Provides information about the frame, and in this case, it appears to be a combination of calendar year, fiscal quarter, and an additional identifier. For instance “CY2008Q3I” suggests a possible combination of calendar year (CY), year (2008), fiscal quarter (Q3), and possibly an additional identifier (“I”)\n\n\n\nThis hierarchical structure provides a detailed view of the financial concept “Accounts Payable (Deprecated 2009-01-31)” within the us-gaap section, including its label, description, and historical data with unit details.\n\n\nMost of the SEC data required for fundamentals analysis is included in a structure of nested lists. We will see in the next section how to properly retrieve this data.\n\n\n\n\n\nFinally, let’s examine the structure associated with the company’s Concept.\n\n\nShow the code\n# Visualize structure of the company_Concepts\nstr(company_Concept, max.level = 3)\n\n\nList of 7\n $ cik        : int 1009829\n $ taxonomy   : chr \"us-gaap\"\n $ tag        : chr \"Assets\"\n $ label      : chr \"Assets\"\n $ description: chr \"Sum of the carrying amounts as of the balance sheet date of all assets that are recognized. Assets are probable\"| __truncated__\n $ entityName : chr \"JAKKS Pacific, Inc.\"\n $ units      :List of 1\n  ..$ USD:'data.frame': 107 obs. of  8 variables:\n  .. ..$ end  : chr [1:107] \"2010-12-31\" \"2010-12-31\" \"2010-12-31\" \"2011-06-30\" ...\n  .. ..$ val  : int [1:107] 633406000 633406000 633406000 614892000 707611000 615234000 615234000 615234000 615234000 615234000 ...\n  .. ..$ accn : chr [1:107] \"0001157523-11-004475\" \"0001157523-11-006668\" \"0001157523-12-001404\" \"0001157523-11-004475\" ...\n  .. ..$ fy   : int [1:107] 2011 2011 2011 2011 2011 2011 2012 2012 2012 2012 ...\n  .. ..$ fp   : chr [1:107] \"Q2\" \"Q3\" \"FY\" \"Q2\" ...\n  .. ..$ form : chr [1:107] \"10-Q\" \"10-Q\" \"10-K\" \"10-Q\" ...\n  .. ..$ filed: chr [1:107] \"2011-08-01\" \"2011-11-09\" \"2012-03-15\" \"2011-08-01\" ...\n  .. ..$ frame: chr [1:107] NA NA \"CY2010Q4I\" \"CY2011Q2I\" ...\n\n\nThe output shows the structure associated with the Asset of the company under the taxonomy of us-gaap.\nFor the purpose of our analysis, we will use company_Facts which includes also the us_gaap_reference.",
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      "**Basics**",
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    "title": "Explore data retrieved from SEC",
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    "text": "XBRL (eXtensible Business Reporting Language): XBRL is a structured, machine-readable format ensuring consistency and comparability across companies and filings. As specialized language for business and financial data, XBRL enables standardized communication and presentation of financial information. It uses XML (eXtensible Markup Language) to tag financial data with labels that provide context and meaning. This tagging allows for easier analysis, comparability, and extraction of data by both humans and machines.\n\n\n\nConsistency: XBRL ensures consistency in financial reporting by providing a standardized set of tags for financial concepts, making it easier to compare data across different companies and periods.\nEfficiency: The use of XBRL streamlines the process of collecting, analyzing, and disseminating financial information, reducing the need for manual data entry and interpretation.\nTransparency: XBRL enhances the transparency of financial data, as each financial concept is tagged with a specific label, providing clear identification and context.\n\n\n\n\nWithin the SEC data retrieved through the API, XBRL is utilized to structure financial information.\nA basic understanding XBRL1 is necessary for navigating and interpreting the structured financial data retrieved from the SEC. It ensures a standardized approach to financial reporting, facilitating meaningful analysis and comparison.\nFirst, we load the required libraries and files.\n\n\nShow the code\nsource(\"setup.qmd\")          \n\n\nNow, let’s retrieve the necessary objects for data exploration:\n\n\nShow the code\n# Load company_data\ncompany_data &lt;- readRDS(\"company_data.RDS\")\ncik &lt;- readRDS(\"cik.RDS\")\n\n\nThe data retrieved from the SEC API is structured financial data compliant with SEC reporting standards.\nTo navigate through this structure for analysis, consider the following key elements:\n\ncik: The Central Index Key (CIK) is a unique identifier assigned to each company filing reports with the U.S. Securities and Exchange Commission (SEC).\nentityName: This is the name of the company, in our case “JAKKS Pacific, Inc.”\nfacts: The main container for financial data, housing two critical sections:\n\ndei: Contains Document and Entity Information (DEI), providing basic company details.\nus-gaap: Holds financial data following the U.S. Generally Accepted Accounting Principles (GAAP).\n\n\nWithin these sections, financial data is organized as a list of items, each with specific attributes:\n\nConcept: Represents a financial measure or item (e.g., “Assets”) with an associated label and data type.\nFacts: Actual numerical values associated with the concept, with attributes like “value,” “unitRef,” and “contextRef.”\nAttributes: Additional attributes providing context for the data, such as reporting period, currency unit, or data precision.\n\nEffectively analyzing this data involves selecting relevant concepts and Fact, potentially transforming or pivoting the data for further processing and visualization.\n\n\n\nLet’s start by exploring the structure of company_data:\n\n\nShow the code\n# Visualize structure of the company_data \nstr(company_data, max.level = 1) \n\n\nList of 3\n $ company_Metadata:List of 22\n $ company_Facts   :List of 3\n $ company_Concept :List of 7\n\n\nThe output reveals that company_data structure comprises three lists with nested lists, such as company_Metadata with 22 lists.\n\n\n\n\n\n\n\nNote\n\n\nIn R, a list is a powerful data structure that can hold elements of different data types. This flexibility allows each element to be unique and cater to specific data requirements. For the company_data object, the list structure plays a crucial role in organizing various pieces of information, including financial data, company descriptions, and filing details. This heterogeneous nature of the data necessitates a flexible data structure like a list to accommodate these diverse data types. Understanding the organization and structure of the company_data list is essential for effective navigation and extraction of specific information. By grasping the relationships between the list elements, users can efficiently retrieve the desired data elements for analysis and interpretation.\n\n\n\n\nTo access the lists we use the symbol $ in after the object e.g. company_data$company_Metadata.\nNext, we split the company_data into separate lists: company_Metadata, company_Facts, company_Concept.\n\n\nShow the code\n# Split the lists in company_data\ncompany_Metadata &lt;- company_data$company_Metadata\ncompany_Facts &lt;- company_data$company_Facts\ncompany_Concept &lt;- company_data$company_Concept\n\n\nNow, let’s examine the structures and content of these lists:\n\n\nLet’s start with company_Metadata which includes 22 elements: characters, integer, sub-list (or nested list), etc.\n\n\nShow the code\n# Visualize structure of the company_Metadata\nstr(company_Metadata, max.level = 1)\n\n\nList of 22\n $ cik                              : chr \"1009829\"\n $ entityType                       : chr \"operating\"\n $ sic                              : chr \"3944\"\n $ sicDescription                   : chr \"Games, Toys & Children's Vehicles (No Dolls & Bicycles)\"\n $ insiderTransactionForOwnerExists : int 0\n $ insiderTransactionForIssuerExists: int 1\n $ name                             : chr \"JAKKS PACIFIC INC\"\n $ tickers                          : chr [1:2] \"JAKK\" \"JAKP\"\n $ exchanges                        : chr [1:2] \"Nasdaq\" \"OTC\"\n $ ein                              : chr \"954527222\"\n $ description                      : chr \"\"\n $ website                          : chr \"\"\n $ investorWebsite                  : chr \"\"\n $ category                         : chr \"Accelerated filer&lt;br&gt;Smaller reporting company\"\n $ fiscalYearEnd                    : chr \"1231\"\n $ stateOfIncorporation             : chr \"DE\"\n $ stateOfIncorporationDescription  : chr \"DE\"\n $ addresses                        :List of 2\n $ phone                            : chr \"424-268-9444\"\n $ flags                            : chr \"\"\n $ formerNames                      : list()\n $ filings                          :List of 2\n\n\nFor our purpose, the most relevant information of company_Metadata are:\n\ncik, as described above.\nsic, standard industrial classification. The SIC codes were used to classify companies into specific industry segments based on their primary business activities. Each four-digit SIC code represented a different industry or sector.\nsicDescription the description of the standard industrial classification\nname, name of the company\ntickers, identifier a publicly traded company’s stock on a particular stock market\nfiling which includes the filing attributes.\n\nHere the structure of company_Metadata:\n\n\nShow the code\n# Visualize structure of the company_Metadata\nstr(company_Metadata$filing, max.level = 2)\n\n\nList of 2\n $ recent:List of 14\n  ..$ accessionNumber      : chr [1:1003] \"0001185185-24-000477\" \"0001185185-24-000433\" \"9999999995-24-000892\" \"0001185185-24-000367\" ...\n  ..$ filingDate           : chr [1:1003] \"2024-05-08\" \"2024-04-25\" \"2024-04-08\" \"2024-04-08\" ...\n  ..$ reportDate           : chr [1:1003] \"2024-03-31\" \"2024-04-24\" \"\" \"2024-03-29\" ...\n  ..$ acceptanceDateTime   : chr [1:1003] \"2024-05-08T08:20:35.000Z\" \"2024-04-25T15:35:51.000Z\" \"2024-04-09T00:15:13.000Z\" \"2024-04-08T17:15:44.000Z\" ...\n  ..$ act                  : chr [1:1003] \"34\" \"34\" \"33\" \"34\" ...\n  ..$ form                 : chr [1:1003] \"10-Q\" \"8-K\" \"EFFECT\" \"8-K\" ...\n  ..$ fileNumber           : chr [1:1003] \"001-35448\" \"001-35448\" \"333-278220\" \"001-35448\" ...\n  ..$ filmNumber           : chr [1:1003] \"24924366\" \"24875827\" \"24831031\" \"24830448\" ...\n  ..$ items                : chr [1:1003] \"\" \"2.02,9.01\" \"S-3,,2024-04-08 16:15:00\" \"5.02\" ...\n  ..$ size                 : int [1:1003] 5719341 656430 1732 176775 7831 9913 190682 43835 220773 11376283 ...\n  ..$ isXBRL               : int [1:1003] 1 1 0 1 0 0 0 0 0 1 ...\n  ..$ isInlineXBRL         : int [1:1003] 1 1 0 1 0 0 0 0 0 1 ...\n  ..$ primaryDocument      : chr [1:1003] \"jakkspacif20240331_10q.htm\" \"jakkspacif20240424_8k.htm\" \"xslEFFECTX01/primary_doc.xml\" \"jakkspacif20240408_8k.htm\" ...\n  ..$ primaryDocDescription: chr [1:1003] \"FORM 10-Q\" \"FORM 8-K\" \"\" \"FORM 8-K\" ...\n $ files :'data.frame': 1 obs. of  4 variables:\n  ..$ name       : chr \"CIK0001009829-submissions-001.json\"\n  ..$ filingCount: int 140\n  ..$ filingFrom : chr \"1996-06-07\"\n  ..$ filingTo   : chr \"2003-07-02\"\n\n\nThe format of the dataset as printed is not very useful. We see that there are useful information on the forms (e.g. 10K) and dates (e.g. filing dates).\nFor now we will keep it as is and we will come back later on how to improve the readability\n\n\n\ncompany_Facts is relatively simple and is a list of 3 elements.\n\n\nShow the code\n# Visualize structure of the company_Facts\nstr(company_Facts, max.level = 1)\n\n\nList of 3\n $ cik       : int 1009829\n $ entityName: chr \"JAKKS Pacific, Inc.\"\n $ facts     :List of 2\n\n\nFor our purpose, the last element company_Facts$facts is the most relevant one.\n\n\nShow the code\n# Visualize structure of the company_Facts\nstr(company_Facts$facts, max.level = 1)\n\n\nList of 2\n $ dei    :List of 2\n $ us-gaap:List of 508\n\n\nThe us-gaap list includes relevant Facts, containing 487 nested elements. Let’s examine the first five.\n\n\nShow the code\n# Visualize structure of the company_Facts\nFacts_us_gaap &lt;- str(company_Facts$facts$`us-gaap`[1:5], max.level = 1)\n\n\nList of 5\n $ AccountsPayableCurrent        :List of 3\n $ AccountsReceivableNetCurrent  :List of 3\n $ AccruedAdvertisingCurrent     :List of 3\n $ AccruedBonusesCurrent         :List of 3\n $ AccruedEmployeeBenefitsCurrent:List of 3\n\n\nThese elements, to which we will refer as us_gaap_reference, include essential fundamentals of the company and are themselves nested lists. Let’s explore the structure of the first one.\n\n\nShow the code\n# Visualize structure of the company_Facts\nstr(company_Facts$facts$`us-gaap`[1], max.level = 4)\n\n\nList of 1\n $ AccountsPayableCurrent:List of 3\n  ..$ label      : chr \"Accounts Payable, Current\"\n  ..$ description: chr \"Carrying value as of the balance sheet date of liabilities incurred (and for which invoices have typically been\"| __truncated__\n  ..$ units      :List of 1\n  .. ..$ USD:'data.frame':  106 obs. of  8 variables:\n  .. .. ..$ end  : chr [1:106] \"2010-12-31\" \"2010-12-31\" \"2010-12-31\" \"2011-06-30\" ...\n  .. .. ..$ val  : int [1:106] 35886000 35886000 35886000 51537000 85352000 26430000 26430000 26430000 26430000 26430000 ...\n  .. .. ..$ accn : chr [1:106] \"0001157523-11-004475\" \"0001157523-11-006668\" \"0001157523-12-001404\" \"0001157523-11-004475\" ...\n  .. .. ..$ fy   : int [1:106] 2011 2011 2011 2011 2011 2011 2012 2012 2012 2012 ...\n  .. .. ..$ fp   : chr [1:106] \"Q2\" \"Q3\" \"FY\" \"Q2\" ...\n  .. .. ..$ form : chr [1:106] \"10-Q\" \"10-Q\" \"10-K\" \"10-Q\" ...\n  .. .. ..$ filed: chr [1:106] \"2011-08-01\" \"2011-11-09\" \"2012-03-15\" \"2011-08-01\" ...\n  .. .. ..$ frame: chr [1:106] NA NA \"CY2010Q4I\" \"CY2011Q2I\" ...\n\n\nThe output presents the structure of the information related to the first element: AccountsPayable\n\nAccountsPayable: Represents a financial concept within the us-gaap section, specifically referring to “Accounts Payable (Deprecated 2009-01-31).”\n\nlabel: This column represents the financial concept or measure, such as “Accounts Payable (Deprecated 2009-01-31).”\ndescription: A detailed explanation of the concept, providing insight into the carrying value as of the balance sheet date.\nunits: A data frame with 2 observations and 8 variables. The variables include information such as:\n\nend: Indicates the end date of the reporting period associated with the financial data.\nval: Represents the numerical value associated with the financial concept. It includes the unit of measure (e.g., million - “M”).\naccn: Stands for accession number, a unique identifier assigned by the SEC to each submission.\nfy: Represents the fiscal year associated with the financial data\nfp: Represents the fiscal period (e.g., Q3 for the third quarter, FY for the full fiscal year).\nform: Indicates the type of form filed with the SEC (e.g., 10-Q for quarterly reports, 10-K for annual reports).\nfiled: Represents the date on which the form was filed with the SEC.\nframe Provides information about the frame, and in this case, it appears to be a combination of calendar year, fiscal quarter, and an additional identifier. For instance “CY2008Q3I” suggests a possible combination of calendar year (CY), year (2008), fiscal quarter (Q3), and possibly an additional identifier (“I”)\n\n\n\nThis hierarchical structure provides a detailed view of the financial concept “Accounts Payable (Deprecated 2009-01-31)” within the us-gaap section, including its label, description, and historical data with unit details.\n\n\nMost of the SEC data required for fundamentals analysis is included in a structure of nested lists. We will see in the next section how to properly retrieve this data.\n\n\n\n\n\nFinally, let’s examine the structure associated with the company’s Concept.\n\n\nShow the code\n# Visualize structure of the company_Concepts\nstr(company_Concept, max.level = 3)\n\n\nList of 7\n $ cik        : int 1009829\n $ taxonomy   : chr \"us-gaap\"\n $ tag        : chr \"Assets\"\n $ label      : chr \"Assets\"\n $ description: chr \"Sum of the carrying amounts as of the balance sheet date of all assets that are recognized. Assets are probable\"| __truncated__\n $ entityName : chr \"JAKKS Pacific, Inc.\"\n $ units      :List of 1\n  ..$ USD:'data.frame': 107 obs. of  8 variables:\n  .. ..$ end  : chr [1:107] \"2010-12-31\" \"2010-12-31\" \"2010-12-31\" \"2011-06-30\" ...\n  .. ..$ val  : int [1:107] 633406000 633406000 633406000 614892000 707611000 615234000 615234000 615234000 615234000 615234000 ...\n  .. ..$ accn : chr [1:107] \"0001157523-11-004475\" \"0001157523-11-006668\" \"0001157523-12-001404\" \"0001157523-11-004475\" ...\n  .. ..$ fy   : int [1:107] 2011 2011 2011 2011 2011 2011 2012 2012 2012 2012 ...\n  .. ..$ fp   : chr [1:107] \"Q2\" \"Q3\" \"FY\" \"Q2\" ...\n  .. ..$ form : chr [1:107] \"10-Q\" \"10-Q\" \"10-K\" \"10-Q\" ...\n  .. ..$ filed: chr [1:107] \"2011-08-01\" \"2011-11-09\" \"2012-03-15\" \"2011-08-01\" ...\n  .. ..$ frame: chr [1:107] NA NA \"CY2010Q4I\" \"CY2011Q2I\" ...\n\n\nThe output shows the structure associated with the Asset of the company under the taxonomy of us-gaap.\nFor the purpose of our analysis, we will use company_Facts which includes also the us_gaap_reference.",
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    "text": "Footnotes\n\n\nThe definitions provided on this website are crafted for non-practitioners and may lack the rigor and precision required by experts. For a more thorough understanding of XBRL financial reporting, we recommend referring to XBRL-based structured digital financial reporting where you can find a comprehensive and rigorous explanation. To delve deeper into the subject, we suggest reading the following authoritative texts: Essentials of XBRL-based Digital Financial Reporting and Mastering XBRL-based Digital Financial Reporting by C. Hoffman.↩︎",
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    "text": "Welcome to the first chapter of our journey into SEC data analysis! In this section, we embark on the exciting process of retrieving financial data from the U.S. Securities and Exchange Commission (SEC) filings using the power of R.\n\n\n\nThis financial data retrieval code is provided for informational purposes only, and we make no warranties regarding the accuracy, completeness, or timeliness of the data. It should not be considered financial advice, and users should consult with qualified professionals for personalized guidance. Data is obtained from various sources, including the SEC, and we do not guarantee its accuracy or availability. Users are responsible for assessing and managing risks associated with the financial data. We are not liable for any damages arising from the use of this data or code. Redistribution, resale, or republication of the data without authorization is prohibited. This disclaimer is subject to change, and users are responsible for staying updated. It is not legal advice, and compliance with applicable laws and regulations is the user’s responsibility.",
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    "text": "Welcome to the first chapter of our journey into SEC data analysis! In this section, we embark on the exciting process of retrieving financial data from the U.S. Securities and Exchange Commission (SEC) filings using the power of R.",
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    "text": "This financial data retrieval code is provided for informational purposes only, and we make no warranties regarding the accuracy, completeness, or timeliness of the data. It should not be considered financial advice, and users should consult with qualified professionals for personalized guidance. Data is obtained from various sources, including the SEC, and we do not guarantee its accuracy or availability. Users are responsible for assessing and managing risks associated with the financial data. We are not liable for any damages arising from the use of this data or code. Redistribution, resale, or republication of the data without authorization is prohibited. This disclaimer is subject to change, and users are responsible for staying updated. It is not legal advice, and compliance with applicable laws and regulations is the user’s responsibility.",
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    "text": "First, we load the required libraries and files.\n\n\nShow the code\nsource(\"setup.qmd\")          \n\n\nNow, let’s retrieve the necessary objects for data exploration:\n\n\nShow the code\n# Load company_data\ncompany_data &lt;- readRDS(\"company_data.RDS\")\ncik &lt;- readRDS(\"cik.RDS\")\n\n# Split the lists in company_data\ncompany_Metadata &lt;- company_data$company_Metadata\ncompany_Facts &lt;- company_data$company_Facts\ncompany_Concept &lt;- company_data$company_Concept\n\n\n\n\nThe use of specific labels to indicate financial report items is regulated by accounting standards set forth by authoritative bodies. In the United States, the Financial Accounting Standards Board (FASB) establishes generally accepted accounting principles (GAAP), which provide guidelines for the preparation of financial statements, including the standardization of labels and concepts.\nDifferent companies may use different reporting styles to indicate Facts in different ways. The use of different labels however affect our ability to efficiently retrieve the appropriate financial data.\nThe objective here is to generate standardized financial reports of Balance sheet, Income Statement, Cash Flow so that we can use the same label to perform specific calculation across all companies.\nLet’s create now a dataframe including the data retrieved from company_Facts$facts$`us-gaap`.\n\n\nThe first step is un-nest the dataset, in particular the financial data, in company_Facts, nested in various sub-lists.\nThe following code can be used to un-nest the list within company_Facts and create a dataframe easy to visualize and useful for our purpose1.\n\n\nShow the code\ndf_Facts &lt;- Fundamentals_to_Dataframe(company_data)\n\n# Select the columns to print out and present the output with wrapped text and formatted numbers\ndf_Facts %&gt;% select(-c(description,accn)) %&gt;% \n  head() %&gt;% as.data.frame() %&gt;% \n  kable(\"html\") %&gt;% \n  kable_styling(full_width = FALSE)\n\n\n\n\n\nend\nval\nfy\nfp\nform\nfiled\nframe\nlabel\nus_gaap_reference\nstart\ncik\nentityName\nsic\nsicDescription\ntickers\n\n\n\n\n2010-12-31\n35.886\n2011\nQ2\n10-Q\n2011-08-01\nNA\nAccounts Payable, Current\nAccountsPayableCurrent\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2010-12-31\n35.886\n2011\nQ3\n10-Q\n2011-11-09\nNA\nAccounts Payable, Current\nAccountsPayableCurrent\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2010-12-31\n35.886\n2011\nFY\n10-K\n2012-03-15\nCY2010Q4I\nAccounts Payable, Current\nAccountsPayableCurrent\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2011-06-30\n51.537\n2011\nQ2\n10-Q\n2011-08-01\nCY2011Q2I\nAccounts Payable, Current\nAccountsPayableCurrent\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2011-09-30\n85.352\n2011\nQ3\n10-Q\n2011-11-09\nCY2011Q3I\nAccounts Payable, Current\nAccountsPayableCurrent\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2011-12-31\n26.430\n2011\nFY\n10-K\n2012-03-15\nNA\nAccounts Payable, Current\nAccountsPayableCurrent\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n\n\n\n\n\nNote that df_Facts$val is expressed in million.\nThe data in this dataframe is organized to facilitate analysis and comparison of financial information over different periods. Each row corresponds to a specific financial Concept (e.g. Accounts Payable) reported by the company, and the columns provide details about the reporting period, values, and other relevant attributes.\nTo recreate a financial statement from the data in df_Facts of JAKKS Pacific Inc., we need to extract the values in df_Fact$val of the various Concepts and corresponding date in df_Fact$end.\ndf_Fact has a long list of Concepts for multiple fiscal periods. The following code shows the large number of Concepts included in df_Fact, related to all financial reports.\n\n\nShow the code\n# Print the size in human-readable format\ncat(\"df_Facts includes:\", format(nrow(df_Facts), units = \"auto\"), \"records \\n\")\n\n\ndf_Facts includes: 16046 records \n\n\nFrom an extract of the df_Facts above, we would see repeated Concepts. Each of them is associated with a different fiscal period. The code next provides number of unique Concepts used historically JAKKS Pacific Inc. in their financial reports.\n\n\nShow the code\n# Print the number of unique records of df_Facts\ndf_Facts_distinct &lt;- df_Facts %&gt;% select(label,description) %&gt;% distinct()\n\ncat(\"df_Facts includes:\", format(nrow(df_Facts_distinct), units = \"auto\"), \"distinct Concepts \\n\")\n\n\ndf_Facts includes: 442 distinct Concepts \n\n\nBy arranging these records by date indicated in df_Fact$end we can see the the full financial reports for each period in a data frame format.\n\n\nShow the code\n# Group the df_Fact by date in df_Fact$end\ndf_Facts &lt;- df_Facts %&gt;% arrange(desc(end))\n\n# Show first rows of df_Facts_BS \ndf_Facts %&gt;%  select(-c(description,accn)) %&gt;% \n  head() %&gt;% as.data.frame() %&gt;% \n  kable( \"html\") %&gt;% \n  kable_styling(full_width = FALSE) %&gt;% \n  column_spec(1,width = \"250px\")\n\n\n\n\n\nend\nval\nfy\nfp\nform\nfiled\nframe\nlabel\nus_gaap_reference\nstart\ncik\nentityName\nsic\nsicDescription\ntickers\n\n\n\n\n2024-03-31\n31.683\n2024\nQ1\n10-Q\n2024-05-08\nCY2024Q1I\nAccounts Payable, Current\nAccountsPayableCurrent\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2024-03-31\n79.875\n2024\nQ1\n10-Q\n2024-05-08\nCY2024Q1I\nAccounts Receivable, after Allowance for Credit Loss, Current\nAccountsReceivableNetCurrent\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2024-03-31\n3.295\n2024\nQ1\n10-Q\n2024-05-08\nCY2024Q1I\nAccrued Income Taxes, Noncurrent\nAccruedIncomeTaxesNoncurrent\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2024-03-31\n37.201\n2024\nQ1\n10-Q\n2024-05-08\nCY2024Q1I\nAccrued Liabilities, Current\nAccruedLiabilitiesCurrent\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2024-03-31\n122.694\n2024\nQ1\n10-Q\n2024-05-08\nCY2024Q1I\nAccumulated Depreciation, Depletion and Amortization, Property, Plant, and Equipment\nAccumulatedDepreciationDepletionAndAmortizationPropertyPlantAndEquipment\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2024-03-31\n-16.192\n2024\nQ1\n10-Q\n2024-05-08\nCY2024Q1I\nAccumulated Other Comprehensive Income (Loss), Net of Tax\nAccumulatedOtherComprehensiveIncomeLossNetOfTax\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n\n\n\n\n\nThe next step is to filter the relevant Concepts associated with each key financial statement: Balance Sheet (BS), Income Statement (IS) and Cash Flow (CF).\n\n\nNote\nAs mentioned in the previous chapter, the df_Facts dataframe contains financial data along with corresponding reporting information, such as df_Facts$end, df_Facts$fy, df_Facts$fp, and df_Facts$form. However, there are instances where a filing (e.g., 10-K) for a specific fiscal period (fy and fp) includes a comparison with previous fiscal periods. In these cases, the financial data may actually refer to a different period, as indicated by df_Facts$end, rather than the period specified by fy and fp.\nTo handle this scenario, we construct a dataframe of financial data based on the end date (df_Facts$end) of the reporting period and remove the remaining attributes such as fy, fp, etc. This ensures that we focus on the actual reporting period for the financial data.\n\n\n\n\n\nThe following code will generate a standardized Balance Sheet (df_std_BS) based on a matching table in Excel (standardized_BS.xlsx). The standardized Balance Sheet includes Concepts that may not be present in the filings (e.g., 10-K) of all companies. If financial values (Facts) are missing, they will be estimated.\n\n\nShow the code\n# Retrieve balance sheet of JAKKS Pacific Inc. in standardized format\ndf_std_BS &lt;- BS_std(df_Facts)\n\n# Format numeric columns to 2 decimal places\ndf_std_BS &lt;- df_std_BS %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n\n# Print the standardized balancesheet\ndf_std_BS %&gt;% head() %&gt;% as.data.frame() %&gt;%\n  head() %&gt;% as.data.frame() %&gt;%\n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1,width = \"250px\")\n\n\n\n\n\nend\nCash & Cash Equivalent\nMarketable Securities Current\nTotal Accounts Receivable\nTotal Inventory\nPrepaid Expenses\nOther Current Assets\nTotal Current Assets\nMarketable Securities Non Current\nProperty Plant and Equipment\nIntangible Assets (excl. goodwill)\nGoodwill\nOther Non Current Assets\nTotal Non Current Assets\nTotal Assets\nAccounts Payable\nTax Payable\nCurrent Debts\nOperating Lease Liability Current\nOther Current Liabilities\nTotal Current Liabilities\nNon Current Debts\nOperating Lease Liability Non Current\nOther Non Current Liabilities\nTotal Non Current Liabilities\nTotal Liabilities\nPreferred Stock\nRetained Earnings or Accumulated Deficit\nAccumulated other comprehensive income (loss)\nMinority interest\nTotal Stockholders Equity\nTotal Liabilities & Stockholders Equity\ncik\nentityName\nsic\nsicDescription\ntickers\n\n\n\n\n2024-03-31\n35.29\nNA\n79.88\n46.34\n3.84\n1.46\n180.79\nNA\n122.15\nNA\n35.00\n2.06\n143.54\n324.33\n31.68\n0.00\nNA\n8.24\n73.75\n113.67\nNA\n15.96\n6.48\n22.44\n136.11\nNA\n-88.12\nNA\n0.50\n188.23\n324.33\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-12-31\n72.35\nNA\n123.80\n52.65\n1.72\n0.24\n255.37\nNA\n120.40\nNA\n35.08\n2.16\n143.58\n398.95\n42.18\n3.79\nNA\n7.38\n95.89\n149.23\nNA\n16.67\n2.70\n53.60\n202.84\nNA\n-73.61\nNA\n0.71\n190.12\n398.95\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-09-30\n96.25\nNA\n206.75\n68.83\n1.93\n0.19\n378.75\nNA\n119.14\nNA\n35.08\n2.22\n135.53\n514.28\n94.41\n17.42\nNA\n6.42\n137.10\n255.34\nNA\n19.28\n35.33\n54.61\n309.96\nNA\n-62.74\nNA\n0.71\n198.72\n514.28\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-06-30\n32.23\nNA\n132.48\n65.06\n4.43\n0.44\n241.20\nNA\n117.47\nNA\n35.08\n2.33\n127.74\n368.94\n57.77\n5.81\nNA\n9.23\n102.91\n175.71\nNA\n6.22\n30.76\n36.98\n212.70\nNA\n-110.88\nNA\n0.72\n151.01\n368.94\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-03-31\n38.30\nNA\n85.17\n63.99\n4.48\n0.12\n200.31\nNA\n114.10\nNA\n35.08\n2.39\n129.08\n329.39\n27.71\n6.24\nNA\n10.01\n78.57\n122.53\nNA\n8.10\n51.68\n59.78\n182.31\nNA\n-117.33\nNA\n1.00\n142.22\n329.39\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2022-12-31\n85.49\nNA\n102.77\n80.62\n0.99\n0.12\n275.21\nNA\n113.71\nNA\n35.08\n2.47\n130.13\n405.34\n33.69\n8.16\nNA\n10.75\n125.22\n177.82\nNA\n9.86\n66.47\n76.33\n254.15\nNA\n-112.02\nNA\n1.00\n146.70\n405.34\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n\n\n\n\n\n\n\n\nThe following code will create a standardized Income Statement (df_std_IS) based on a matching table in Excel (standardized_IS.xlsx).\nHere few relevant remarks regarding the standardized Income Statement:\n\nThe financial data are presented on a quarterly basis only.\nIn cases where quarterly not all Facts are available, these are estimated as the difference between the yearly value and the existing quarterly values of that year, divided equally by the number of quarters that are missing.\n\n\n\nShow the code\n# Retrieve Income Statement of JAKKS Pacific Inc. in standardized format\ndf_std_IS &lt;- IS_std(df_Facts)\n\n# Format numeric columns to 2 decimal places\ndf_std_IS &lt;- df_std_IS %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized income statement\ndf_std_IS %&gt;% head() %&gt;% as.data.frame() %&gt;%\n  head() %&gt;% as.data.frame() %&gt;%\n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1,width = \"250px\")\n\n\n\n\n\nend\nRevenue\nCost of Revenue\nGross Profit\nResearch and development\nSales general and administrative costs\nOther Non Operating Income (Loss) Net\nOperating Income\nInterest Income\nInterest Expense\nOther income (expense) Net\nIncome Before Income Tax\nProvision for (benefit) Income Tax\nNet Income (loss) (continous operations)\ncik\nentityName\nsic\nsicDescription\ntickers\n\n\n\n\n2024-03-31\n90.08\n69.02\n21.05\nNA\n42.38\nNA\n-21.32\n0.38\n0.14\n-0.89\n-20.95\n-6.73\n-14.22\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-12-31\n127.40\n93.66\n33.73\nNA\n49.07\nNA\n-15.34\n0.76\n0.71\n-0.29\n-16.52\n-5.64\n-10.87\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-09-30\n309.74\n202.76\n106.98\nNA\n44.59\nNA\n62.40\n0.38\n1.44\n0.08\n60.50\n12.38\n48.12\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-06-30\n166.93\n115.74\n51.20\nNA\n34.75\nNA\n16.45\n0.09\n1.30\n7.40\n7.66\n1.48\n6.18\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-03-31\n107.48\n76.05\n31.44\nNA\n35.84\nNA\n-4.40\n0.12\n3.00\n-0.82\n-6.70\n-1.38\n-5.32\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2022-12-31\n131.89\n103.32\n28.57\nNA\n44.26\nNA\n-15.70\n0.06\n2.29\n-1.83\n-16.22\n-54.33\n38.11\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n\n\n\n\n\n\n\n\nSimilarly to the Income Statement, the following code will create a standardized Cash Flow Statement (df_std_CF) based on a matching table in Excel (standardized_CF.xlsx).\n\n\nShow the code\n# Retrieve Cash Flow statement of JAKKS Pacific Inc. in standardized format\ndf_std_CF &lt;- CF_std(df_Facts)\n\n# Format numeric columns to 2 decimal places\ndf_std_CF &lt;- df_std_CF %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized cash flow\ndf_std_CF %&gt;% head() %&gt;% as.data.frame() %&gt;%\n  head() %&gt;% as.data.frame() %&gt;%\n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1,width = \"250px\")\n\n\n\n\n\nend\n(Operating Activities) Cash Flow Depreciation, Depletion, Ammortization\n(Operating Activities) Change in Accounts Receivable\n(Operating Activities) Change in Inventory\n(Operating Activities) Change in Prepaid expenses and other assets\n(Operating Activities) Change in Accounts Payable\n(Operating Activities) Change in Accounts Taxes Payable\n(Operating Activities) Change in Reserve for Sales Return and allowances\n(Operating Activities) Deferred Income Tax\n(Operating Activities) Stock-based Compensation\n(Operating Activities) Cash Flow from Operating Activities\n(Investing Activities) Purchase of Property, Plant and Equipment\n(Investing Activities) Proceeds from Asset Sales\n(Investing Activities) Purchase of Businesses\n(Investing Activities) Purchase of Marketable Securities and Investment\n(Investing Activities) Proceeds from sale or maturity of Marketable Securities and Investment\n(Investing Activities) Proceeds from maturities of Marketable Securities and Investment\n(Investing Activities) Cash Flow from Investing Activities\n(Financing Activities) Proceeds from Issuance of Stock\n(Financing Activities) Payment for Repurchase of Stock\n(Financing Activities) Proceeds from Issuance of Debt\n(Financing Activities) Payment of Debt\n(Financing Activities) Cash for Dividends\n(Financing Activities) Cash Flow from Financing Activities\nEffect of Exchange Rate on Cash & Cash Equivalent\nChange in Cash, Cash Equivalents\ncik\nentityName\nsic\nsicDescription\ntickers\n\n\n\n\n2024-03-31\n1.60\n-42.80\n-6.31\n11.20\n-14.13\n-3.73\nNA\nNA\n2.58\nNA\n2.23\n0.00\nNA\nNA\nNA\nNA\n-3.63\nNA\nNA\nNA\nNA\nNA\n-20.00\n-0.56\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-12-31\n2.44\n-83.21\n-16.18\n-0.37\n-67.04\n-13.39\nNA\n-2.58\n2.06\nNA\n3.19\n0.04\nNA\nNA\nNA\nNA\n-3.23\nNA\nNA\nNA\nNA\nNA\n-0.58\n1.18\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-09-30\n2.73\n75.07\n3.77\n-4.54\n46.79\n11.64\nNA\nNA\n1.99\nNA\n0.80\n0.00\nNA\nNA\nNA\nNA\n-0.78\nNA\nNA\nNA\nNA\nNA\n-1.28\n-0.79\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-06-30\n2.49\n47.12\n1.07\n-1.60\n38.54\n-0.40\nNA\nNA\n1.86\nNA\n1.43\n-0.02\nNA\nNA\nNA\nNA\n-1.42\nNA\nNA\nNA\nNA\nNA\n-30.50\n1.13\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2023-03-31\n1.29\n-17.22\n-16.63\n6.52\n-6.78\n-1.91\nNA\nNA\n2.09\nNA\n3.49\n0.02\nNA\nNA\nNA\nNA\n-3.47\nNA\nNA\nNA\nNA\nNA\n-39.93\n0.33\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n2022-12-31\n2.31\n-102.21\n-28.55\n-4.76\n-60.82\n-3.06\nNA\n-57.86\n1.65\nNA\n2.30\n0.00\nNA\nNA\nNA\nNA\n-2.30\nNA\nNA\nNA\nNA\nNA\n-0.76\n1.11\nNA\n0001009829\nJAKKS Pacific, Inc.\n3944\nGames, Toys & Children's Vehicles (No Dolls & Bicycles)\nJAKK\n\n\n\n\n\n\n\n\n\n\n\nFinally, we can transpose the dataframes of the financial statements to improve the readability.\nBalance Sheet\n\n\nShow the code\nlibrary(kableExtra)\n\n# Transpose the Balanche Sheet statement in standardized format\ndf_std_BS_t &lt;- transpose_df_standardized(df_std_BS, \"standardized_BS\")\n\n# Format numeric columns to 2 decimal places\ndf_std_BS_t &lt;- df_std_BS_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Balance Sheet in standardized format\ndf_std_BS_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item ($ in Million)\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2012-01-03\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n2008-12-31\n\n\n\n\nCash & Cash Equivalent\n35.29\n72.35\n96.25\n32.23\n38.30\n85.49\n76.60\n62.28\n39.23\n45.33\n26.70\n38.34\n84.06\n92.69\n79.82\n52.69\n44.03\n66.29\n75.89\n37.05\n47.41\n58.20\n57.14\n62.99\n46.78\n64.98\n48.81\n67.60\n68.03\n86.06\n48.16\n96.63\n118.91\n102.53\n81.21\n110.27\n105.10\n71.53\n88.62\n162.71\n113.36\n117.07\n51.52\n69.72\n165.36\n189.32\n140.76\n221.65\n254.56\n257.26\n257.26\n232.24\n246.85\n274.47\n278.35\n218.59\n248.75\n254.84\n169.52\n\n\nMarketable Securities Current\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.21\nNA\n0.21\n0.21\n0.21\nNA\n0.21\nNA\nNA\nNA\nNA\n\n\nTotal Accounts Receivable\n79.88\n123.80\n206.75\n132.48\n85.17\n102.77\n204.86\n164.02\n103.73\n147.39\n209.19\n107.90\n79.66\n102.25\n166.79\n69.00\n64.76\n117.94\n200.79\n85.12\n67.79\n122.28\n205.41\n100.28\n93.93\n142.46\n224.10\n110.48\n98.49\n173.60\n272.26\n132.89\n85.47\n163.39\n292.86\n117.15\n104.32\n234.52\n304.34\n109.34\n65.37\n101.22\n257.96\n94.92\n64.98\n105.46\n242.64\n121.60\n58.40\nNA\n103.64\n239.68\n109.33\nNA\n122.48\nNA\nNA\nNA\nNA\n\n\nTotal Inventory\n46.34\n52.65\n68.83\n65.06\n63.99\n80.62\n109.17\n123.67\n85.31\n83.95\n89.80\n60.58\n36.65\n38.64\n54.58\n57.68\n48.23\n54.26\n65.30\n53.52\n44.69\n53.88\n64.45\n62.16\n54.00\n58.43\n80.14\n81.22\n67.47\n75.44\n75.06\n71.47\n53.47\n60.54\n81.40\n91.89\n79.47\n78.83\n88.78\n65.15\n42.20\n46.78\n59.12\n56.67\n52.05\n59.69\n73.23\n60.80\n45.00\nNA\n47.02\n55.84\n55.26\nNA\n43.23\nNA\nNA\nNA\nNA\n\n\nPrepaid Expenses\n3.84\n1.72\n1.93\n4.43\n4.48\n0.99\n5.01\n7.33\n6.78\n4.15\n4.18\n5.33\n5.05\n2.49\nNA\nNA\nNA\n3.61\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOther Current Assets\n1.46\n0.24\n0.19\n0.44\n0.12\n0.12\n0.12\n0.12\n0.12\n0.19\n0.25\n0.00\n0.12\n0.00\n22.12\n28.45\n18.80\n0.00\n18.50\n28.52\n28.03\n15.78\n26.49\n24.68\n20.81\n16.80\n18.26\n30.12\n33.58\n18.28\n51.20\n51.54\n56.92\n55.91\n58.05\n63.44\n57.53\n52.51\n57.65\n62.64\n61.20\n55.63\n54.72\n58.64\n62.98\n51.37\n84.73\n91.80\n93.13\n0.00\n89.36\n67.50\n76.86\n0.00\n67.90\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Current Assets\n180.79\n255.37\n378.75\n241.20\n200.31\n275.21\n401.75\n364.49\n245.67\n287.56\n338.06\n239.31\n223.85\n250.83\n323.32\n207.82\n175.82\n260.38\n360.47\n204.21\n187.91\n250.14\n353.49\n250.11\n215.52\n282.67\n371.32\n289.42\n267.57\n353.38\n446.68\n352.52\n314.78\n382.37\n513.52\n382.96\n346.64\n437.59\n539.60\n400.06\n282.34\n320.93\n423.54\n280.16\n345.60\n406.06\n541.56\n496.06\n451.30\n0.00\n497.48\n595.47\n488.50\n0.00\n512.16\n0.00\n0.00\n0.00\n0.00\n\n\nMarketable Securities Non Current\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nProperty Plant and Equipment\n122.15\n120.40\n119.14\n117.47\n114.10\n113.71\n113.14\n110.03\n105.43\n103.10\n102.10\n99.99\n96.26\n95.37\n95.81\n94.34\n103.49\n103.33\n109.77\n108.25\n104.42\n108.32\n115.82\n113.91\n116.92\n115.38\n111.70\n109.89\n104.67\n103.13\n99.90\n95.48\n89.01\n86.31\n95.43\n19.32\n13.11\n87.36\n10.55\n14.28\n10.84\n11.10\n12.09\n14.96\n16.24\n15.83\n15.13\n18.79\n17.55\nNA\n16.19\n17.58\n20.66\nNA\n16.95\nNA\nNA\nNA\nNA\n\n\nIntangible Assets (excl. goodwill)\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n42.75\n45.31\n53.53\n54.96\n57.48\n59.72\n61.93\n65.58\n63.56\n63.82\n66.24\n67.33\n69.50\n70.98\n70.29\n23.77\n21.29\nNA\n26.15\n16.36\n20.23\nNA\n23.44\nNA\nNA\nNA\nNA\n\n\nGoodwill\n35.00\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.20\n35.27\n35.59\n35.38\n35.34\n43.48\n43.27\n43.21\n43.46\n43.63\n44.02\n44.20\n44.34\n44.57\n44.21\n44.49\n44.78\n45.09\n44.94\n44.88\n44.74\n48.50\n48.49\n48.84\n50.77\n24.73\n24.73\nNA\n24.02\n6.99\n6.99\nNA\n6.99\nNA\nNA\nNA\nNA\n\n\nOther Non Current Assets\n2.06\n2.16\n2.22\n2.33\n2.39\n2.47\n2.52\n2.73\n2.92\n2.99\n3.08\n3.57\n2.09\n3.22\n6.92\n10.06\n17.69\n18.93\n18.98\n17.26\n17.27\n19.10\n18.94\n18.97\n18.50\n6.58\n2.11\n2.49\n2.31\n2.16\n2.42\n2.66\n2.83\n3.12\n9.78\n9.49\n9.85\n10.39\n10.97\n11.74\n7.48\n6.18\n6.34\n3.07\n4.13\n4.58\n4.94\n3.90\n3.47\n0.00\n3.67\n8.24\n15.51\n0.00\n12.64\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Non Current Assets\n143.54\n143.58\n135.53\n127.74\n129.08\n130.13\n75.37\n79.15\n70.10\n69.49\n71.05\n75.82\n74.56\n78.54\n84.27\n92.60\n101.09\n104.84\n4.75\n124.53\n124.06\n92.70\n94.10\n98.77\n98.38\n87.68\n81.94\n108.96\n108.78\n110.92\n113.44\n117.37\n115.80\n117.25\n126.03\n127.74\n123.69\n124.19\n126.15\n134.06\n128.43\n128.91\n133.56\n141.92\n148.26\n148.77\n197.02\n119.86\n119.84\n0.00\n117.75\n112.14\n126.39\n0.00\n121.24\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Assets\n324.33\n398.95\n514.28\n368.94\n329.39\n405.34\n477.11\n443.64\n315.77\n357.05\n409.11\n315.13\n298.40\n329.37\n407.59\n300.42\n276.91\n365.22\n365.22\n328.74\n311.98\n342.84\n447.59\n348.88\n313.89\n370.35\n453.26\n398.38\n376.34\n464.30\n560.12\n469.89\n430.57\n499.62\n639.56\n510.70\n470.34\n561.78\n665.76\n534.12\n410.78\n449.84\n557.09\n422.09\n493.86\n554.82\n738.59\n615.92\n571.14\nNA\n615.23\n707.61\n614.89\nNA\n633.41\nNA\nNA\nNA\nNA\n\n\nAccounts Payable\n31.68\n42.18\n94.41\n57.77\n27.71\n33.69\n77.13\n86.66\n36.44\n50.24\n105.27\n68.81\n31.31\n30.35\n95.53\n53.10\n22.78\n61.20\n136.18\n64.39\n27.91\n57.57\n142.61\n68.12\n39.07\n49.92\n98.39\n67.00\n30.14\n51.74\n102.58\n73.72\n28.13\n34.99\n94.63\n59.22\n24.24\n56.11\n115.62\n60.55\n21.34\n25.27\n89.78\n56.03\n30.40\n37.79\n105.91\n64.34\n20.06\nNA\n26.43\n85.35\n51.54\nNA\n35.89\nNA\nNA\nNA\nNA\n\n\nTax Payable\n0.00\n3.79\n17.42\n5.81\n6.24\n8.16\n14.08\n2.33\n1.21\n1.00\n0.64\n0.70\n0.17\n0.48\n1.62\n0.50\n0.35\n2.49\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nCurrent Debts\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n1.77\n1.91\n1.91\n6.90\n1.89\nNA\n27.21\nNA\nNA\nNA\n21.20\n21.20\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n38.91\n38.63\nNA\n38.10\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOperating Lease Liability Current\n8.24\n7.38\n6.42\n9.23\n10.01\n10.75\n10.52\n10.24\n11.01\n10.48\n10.41\n10.48\n10.11\n9.93\n9.66\n9.63\n9.59\n9.45\n9.37\n9.18\n8.82\n0.00\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOther Current Liabilities\n73.75\n95.89\n137.10\n102.91\n78.57\n125.22\n163.71\n148.54\n87.96\n111.35\n107.79\n113.45\n74.45\n97.51\n110.65\n57.50\n53.80\n77.88\n98.37\n58.13\n75.99\n59.32\n98.17\n97.02\n73.61\n64.64\n69.73\n31.45\n39.19\n65.07\n96.53\n62.33\n59.70\n92.41\n147.32\n91.72\n88.20\n135.24\n134.67\n102.43\n140.59\n121.22\n138.51\n107.10\n156.86\n181.68\n178.12\n78.19\n76.53\n0.00\n96.40\n108.75\n64.12\n0.00\n89.02\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Current Liabilities\n113.67\n149.23\n255.34\n175.71\n122.53\n177.82\n265.44\n247.78\n136.62\n173.07\n224.10\n193.44\n116.04\n138.27\n217.46\n122.51\n88.43\n152.92\n250.81\n133.59\n112.72\n144.10\n240.79\n165.14\n112.68\n135.76\n189.32\n98.45\n69.33\n116.81\n199.10\n136.05\n87.83\n127.40\n241.95\n150.94\n112.44\n191.35\n289.20\n201.61\n161.93\n184.60\n228.29\n163.13\n187.26\n219.48\n284.03\n142.53\n96.59\nNA\n122.83\n194.11\n115.66\nNA\n124.91\nNA\nNA\nNA\nNA\n\n\nNon Current Debts\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n174.16\n169.40\n174.96\n170.81\n160.66\nNA\n139.79\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n215.00\n215.00\n215.00\n215.00\n215.00\n215.00\nNA\n100.00\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOperating Lease Liability Non Current\n15.96\n16.67\n19.28\n6.22\n8.10\n9.86\n12.55\n15.41\n7.40\n8.04\n9.95\n12.28\n14.47\n16.88\n18.39\n20.74\n23.12\n25.63\n27.86\n29.83\n29.63\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOther Non Current Liabilities\n6.48\n2.70\n35.33\n30.76\n51.68\n66.47\n88.66\n98.62\n115.13\n114.96\n17.08\n16.98\n15.44\n8.06\n5.87\n3.33\n3.32\n5.41\n5.04\n0.14\n0.13\n4.41\n4.36\n4.35\n4.43\n4.54\n4.62\n4.74\n4.91\n5.00\n5.21\n5.17\n5.30\n5.16\n4.23\n3.90\n0.91\n1.87\n7.25\n7.38\n7.43\n7.02\n13.18\n18.37\n18.45\n18.34\n27.33\n1.83\n1.86\n0.00\n1.63\n1.57\n1.58\n0.00\n1.62\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Non Current Liabilities\n22.44\n53.60\n54.61\n36.98\n59.78\n76.33\n101.22\n114.02\n122.53\n123.00\n121.26\n125.33\n185.94\n176.42\n176.82\n199.96\n197.53\n207.79\n206.61\n193.52\n175.06\n147.09\n151.20\n143.45\n141.25\n140.08\n140.08\n160.95\n173.74\n212.29\n217.73\n217.32\n217.50\n218.81\n227.41\n227.09\n222.29\n225.35\n231.92\n232.05\n116.35\n116.56\n164.45\n129.45\n128.84\n128.13\n125.49\n99.93\n99.28\n0.00\n98.81\n97.79\n96.90\n0.00\n96.09\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Liabilities\n136.11\n202.84\n309.96\n212.70\n182.31\n254.15\n366.66\n361.80\n259.14\n296.07\n345.35\n318.77\n301.99\n314.69\n394.28\n322.47\n285.96\n360.72\n457.42\n327.11\n287.78\n291.19\n391.99\n308.59\n253.93\n275.84\n329.40\n259.40\n243.07\n329.10\n416.84\n353.37\n305.33\n346.21\n469.36\n378.03\n334.73\n416.70\n521.12\n433.66\n278.28\n301.16\n392.74\n292.58\n316.10\n347.60\n409.52\n242.46\n195.87\nNA\n221.64\n291.90\n212.56\nNA\n221.00\nNA\nNA\nNA\nNA\n\n\nPreferred Stock\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nRetained Earnings or Accumulated Deficit\n-88.12\n-73.61\n-62.74\n-110.88\n-117.33\n-112.02\n-149.99\n-180.68\n-207.24\n-203.43\n-200.26\n-236.59\n-221.51\n-197.42\n-186.08\n-218.46\n-195.19\n-183.15\n-162.86\n-179.30\n-156.76\n-127.60\n-124.35\n-140.04\n-121.48\n-85.23\n-54.82\n-37.21\n-20.46\n-2.15\n5.44\n-25.18\n-20.81\n-3.39\n5.94\n-39.91\n-34.23\n-26.64\n-29.44\n-73.51\n-64.46\n-48.15\n-32.09\n-68.68\n-20.27\n8.84\n130.46\n102.20\n104.59\nNA\n123.17\n145.78\n113.55\nNA\n119.88\nNA\nNA\nNA\nNA\n\n\nAccumulated other comprehensive income (loss)\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nMinority interest\n0.50\n0.71\n0.71\n0.72\n1.00\n1.00\n0.86\n0.88\n1.23\n1.33\n1.31\n1.27\n1.25\n1.21\n1.18\n1.13\n1.12\n1.08\n0.97\n1.00\n0.94\n0.91\n1.01\n0.99\n1.02\n0.97\n1.04\n1.00\n0.94\n0.91\n0.58\n0.66\n0.44\n0.41\n0.46\n0.44\n0.49\n0.49\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nTotal Stockholders Equity\n188.23\n190.12\n198.72\n151.01\n142.22\n146.70\n106.33\n78.07\n53.21\n57.90\n61.02\n-6.04\n-5.65\n12.94\n11.90\n-23.15\n-9.84\n4.02\n22.04\n1.63\n24.19\n51.65\n55.60\n40.30\n59.96\n94.51\n123.86\n138.98\n133.27\n135.20\n143.28\n116.52\n125.24\n153.41\n170.20\n132.68\n135.61\n145.08\n144.63\n100.45\n132.50\n148.68\n164.35\n129.51\n177.75\n207.22\n329.06\n373.46\n375.28\n0.00\n393.59\n415.72\n402.33\n0.00\n412.41\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Liabilities & Stockholders Equity\n324.33\n398.95\n514.28\n368.94\n329.39\n405.34\n477.11\n443.64\n315.77\n357.05\n409.11\n315.13\n298.40\n329.37\n407.59\n300.42\n276.91\n365.22\n479.64\n328.74\n311.98\n342.84\n447.59\n348.88\n313.89\n370.35\n453.26\n398.38\n376.34\n464.30\n560.12\n469.89\n430.57\n499.62\n639.56\n510.70\n470.34\n561.78\n665.76\n534.12\n410.78\n449.84\n557.09\n422.09\n493.86\n554.82\n738.59\n615.92\n571.14\nNA\n615.23\n707.61\n614.89\nNA\n633.41\nNA\nNA\nNA\nNA\n\n\n\n\n\n\n\nIncome Statement\n\n\nShow the code\n# Transpose the Income Statement  in standardized format\ndf_std_IS_t &lt;- transpose_df_standardized(df_std_IS, \"standardized_IS\")\n\n# Format numeric columns to 2 decimal places\ndf_std_IS_t &lt;- df_std_IS_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_IS_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item ($ in Million)\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-09-03\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\nRevenue\n90.08\n127.40\n309.74\n166.93\n107.48\n131.89\n323.00\n220.42\n120.88\n187.96\n236.96\n112.35\n83.84\n128.97\n242.29\n78.76\n66.56\n149.66\n280.13\n95.18\n70.83\n141.95\n236.70\n105.78\n93.00\n136.63\n262.41\n119.56\n94.50\n167.03\n207.86\n161.81\n140.98\n95.81\n186.44\n337.03\n131.11\n114.20\n202.51\n349.36\n124.17\n82.51\n80.44\n310.89\n106.23\n78.07\n80.19\n314.49\n145.36\n73.40\n95.95\n332.42\n131.93\n72.32\n197.99\n348.68\n100.30\n200.93\n\n\nCost of Revenue\n69.02\n93.66\n202.76\n115.74\n76.05\n103.32\n231.09\n159.53\n90.96\n137.92\n162.03\n80.46\n57.75\n86.24\n167.67\n61.99\n50.21\n106.11\n199.27\n77.44\n56.49\n91.84\n172.37\n77.84\n70.04\n114.36\n200.63\n85.85\n64.48\n114.92\n207.86\n111.68\n96.18\n64.63\n113.83\n232.70\n91.82\n78.82\n174.32\n254.62\n86.35\n58.95\n98.96\n219.50\n103.99\n54.69\n102.74\n217.78\n98.47\n49.84\n122.12\n226.75\n86.84\n48.05\n132.46\n237.72\n66.07\n150.19\n\n\nGross Profit\n21.05\n33.73\n106.98\n51.20\n31.44\n28.57\n91.91\n60.89\n29.92\n50.04\n74.92\n31.90\n26.09\n37.44\n74.62\n16.77\n16.35\n39.84\n80.86\n17.75\n14.34\n38.93\n64.33\n27.94\n22.96\n38.92\n61.78\n33.72\n30.02\n52.10\nNA\n50.13\n44.80\n31.18\n57.14\n104.33\n39.29\n35.38\n58.95\n94.74\n37.82\n23.56\n38.94\n91.39\n2.24\n23.38\n49.48\n96.71\n46.89\n23.57\n48.50\n105.67\n45.09\n24.27\n65.53\n110.96\n34.23\n50.73\n\n\nResearch and development\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nSales general and administrative costs\n42.38\n49.07\n44.59\n34.75\n35.84\n44.26\n38.17\n36.93\n30.65\n47.12\n38.18\n30.08\n28.82\n40.90\n36.96\n24.66\n32.34\n-14.14\n44.59\n33.87\n35.27\n42.59\n44.18\n39.75\n58.62\n55.66\n55.99\n47.83\n45.74\n54.50\n60.52\nNA\n45.90\n45.00\n56.47\n59.70\n42.30\n39.58\n72.44\n50.92\n42.64\n38.48\n54.82\n51.74\n46.53\n47.22\n61.98\n59.42\n46.79\n42.98\n54.95\n55.60\n43.09\n39.06\n54.56\n59.38\n40.41\n56.76\n\n\nOther Non Operating Income (Loss) Net\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n14.62\nNA\nNA\n-6.96\nNA\n0.00\n0.00\n-21.32\nNA\n0.00\n0.00\nNA\n0.00\n0.00\n0.00\n-9.19\n0.00\n0.00\n0.00\nNA\n0.00\n0.00\n0.00\nNA\n0.00\n0.00\nNA\n\n\nOperating Income\n-21.32\n-15.34\n62.40\n16.45\n-4.40\n-15.70\n53.74\n23.66\n-0.73\n2.93\n36.74\n1.82\n-2.72\n3.23\n37.51\n-9.75\n-15.99\n-4.45\n35.66\n-18.65\n-24.04\n-8.04\n20.04\n-12.14\n-35.66\n-16.04\n-7.75\n-14.11\n-15.72\n-2.39\nNA\n35.51\n-1.10\n-13.82\n7.63\n44.63\n-3.01\n-4.20\n7.83\n43.81\n-4.82\n-14.92\n-11.13\n39.65\n-44.29\n-23.84\n-3.31\n37.30\n0.11\n-19.41\n0.32\n50.07\n2.00\n-14.79\n10.97\n51.58\n-6.18\n-113.11\n\n\nInterest Income\n0.38\n0.76\n0.38\n0.09\n0.12\n0.06\n0.06\n0.01\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.01\n0.02\n0.02\n0.02\n0.03\n0.02\n0.02\n0.01\n0.01\n0.01\n0.01\n0.01\n0.00\n0.00\n0.01\nNA\n0.02\n0.02\n0.01\n0.02\n0.02\n0.02\n0.02\n0.03\n0.03\n0.03\n0.03\n0.09\n0.13\n0.07\n0.06\n0.10\n0.31\n0.20\n0.08\n0.10\n0.12\n0.10\n0.08\n0.10\n0.08\n0.08\n\n\nInterest Expense\n0.14\n0.71\n1.44\n1.30\n3.00\n2.29\n4.35\n2.34\n2.20\n2.20\n2.66\n4.37\n4.88\n4.91\n5.57\n5.54\n5.55\n5.38\n4.62\n2.92\n3.02\n3.01\n3.10\n2.20\n1.94\n2.33\n2.03\n2.54\n2.93\n3.51\n3.02\nNA\n3.22\n3.23\n3.21\n3.11\n3.11\n2.97\n3.30\n3.97\n2.98\n2.21\n2.74\n2.30\n2.06\n2.85\n3.14\n2.02\n2.04\n2.04\n2.07\n2.06\n2.02\n2.04\n0.98\n1.55\n2.10\n1.98\n\n\nOther income (expense) Net\n-0.89\n-0.29\n0.08\n7.40\n-0.82\n-1.83\n7.09\n-6.22\n0.55\n3.94\n-2.59\n12.61\n16.36\n1.67\n-0.22\n7.70\n-9.82\n3.52\n13.60\n0.31\n2.29\n-1.21\n-0.72\n2.15\n0.92\n1.97\n6.87\n-0.28\n-0.03\n-0.06\n-34.64\n35.51\n-0.90\n-0.11\n-2.24\n41.51\n-6.13\n-7.19\n4.51\n39.81\n-7.83\n-17.16\n-13.90\n37.26\n-46.48\n-26.77\n-6.51\n35.18\n-2.24\n-21.64\n-1.83\n47.90\n-0.15\n-16.93\n9.91\n49.93\n-8.36\n-115.17\n\n\nIncome Before Income Tax\n-20.95\n-16.52\n60.50\n7.66\n-6.70\n-16.22\n42.25\n27.54\n-3.49\n-3.21\n36.67\n-15.16\n-23.96\n-3.35\n32.16\n-23.00\n-11.72\n-13.37\n17.43\n-21.90\n-29.37\n-9.87\n17.65\n-16.50\n-38.53\n-20.36\n-16.65\n-16.37\n-18.63\n-5.84\n31.61\nNA\n-3.44\n-16.95\n6.65\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nProvision for (benefit) Income Tax\n-6.73\n-5.64\n12.38\n1.48\n-1.38\n-54.33\n11.57\n1.33\n0.42\n-0.06\n0.30\n-0.10\n0.09\n0.45\n-0.27\n0.27\n0.28\n0.55\n1.02\n0.59\n-0.24\n1.24\n1.95\n2.09\n-2.34\n0.72\n0.92\n-0.33\n0.30\n1.91\n1.08\nNA\n0.70\n0.43\n0.31\n1.38\n1.31\n0.43\n1.18\n1.74\n1.28\n-0.48\n2.18\n0.28\n-0.14\n0.30\n85.29\n5.98\n0.07\n-5.19\n-17.97\n13.26\n1.85\n-6.14\n1.15\n9.77\n-4.11\n-22.67\n\n\nNet Income (loss) (continous operations)\n-14.22\n-10.87\n48.12\n6.18\n-5.32\n38.11\n30.68\n26.21\n-3.91\n-3.15\n36.38\n-15.06\n-24.05\n-3.54\n32.43\n-23.27\n-12.00\n-13.84\n16.41\n-22.48\n-29.13\n-10.61\n15.70\n-18.59\n-36.19\n-30.49\n-17.57\n-16.69\n-18.28\n-7.75\n30.53\nNA\n-4.14\n-17.38\n-9.39\n45.86\n-5.73\n-7.58\n2.80\n44.07\n-12.68\nNA\n-13.48\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n\n\n\n\n\nCash Flow Statement\n\n\nShow the code\n# Transpose the Cash Flow Statement of JAKKS Pacific Inc. in standardized format\ndf_std_CF_t &lt;- transpose_df_standardized(df_std_CF, \"standardized_CF\")\n\n# Format numeric columns to 2 decimal places\ndf_std_CF_t &lt;- df_std_CF_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Cash Flow Statement in standardized format\ndf_std_CF_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item ($ in Million)\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-06-09\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\n(Operating Activities) Cash Flow Depreciation, Depletion, Ammortization\n1.60\n2.44\n2.73\n2.49\n1.29\n2.31\n4.63\n3.13\n2.41\n1.99\n4.90\n3.38\n2.40\n-0.38\n4.53\n5.16\n3.76\n-4.78\n14.00\n8.48\n6.47\n6.18\n13.13\n8.66\n6.19\n5.18\n16.60\n11.47\n8.76\n12.09\n16.41\n9.31\n8.07\n9.28\n14.76\n7.61\n6.08\n5.67\n17.26\n8.65\nNA\n6.35\n12.21\n18.63\n8.79\n6.39\n5.28\n25.21\n10.19\n5.47\n10.93\n10.80\n5.93\n3.88\n12.15\n12.02\n5.40\n8.99\n\n\n(Operating Activities) Change in Accounts Receivable\n-42.80\n-83.21\n75.07\n47.12\n-17.22\n-102.21\n40.99\n60.54\n-43.70\n-62.31\n101.90\n27.53\n-23.37\n-64.71\n99.16\n4.89\n-53.41\n-82.58\n116.52\n17.17\n-54.58\n-85.08\n104.19\n5.03\n-34.74\n-80.86\n121.75\n14.88\n-75.11\n-98.66\n139.36\n47.42\n-77.92\n-129.47\n175.71\n12.83\n-130.20\n-69.82\n195.00\n43.98\nNA\n-35.86\n-156.74\n163.05\n29.93\n-40.47\n-137.18\n117.97\n63.19\n-45.23\n-145.02\n130.35\n51.90\n-65.04\n-164.89\n184.51\n-13.54\n-4.41\n\n\n(Operating Activities) Change in Inventory\n-6.31\n-16.18\n3.77\n1.07\n-16.63\n-28.55\n-14.49\n38.36\n1.35\n-5.84\n29.22\n23.93\n-1.99\n-15.94\n-3.10\n9.45\n-6.03\n-11.04\n11.78\n8.84\n-9.20\n-10.57\n2.29\n8.16\n-4.43\n-21.71\n-1.08\n13.75\n-7.97\n0.37\n3.60\n18.00\n-7.07\n-20.86\n-10.48\n12.41\n0.65\n-9.95\n23.63\n22.94\nNA\n-4.58\n-12.34\n2.44\n4.62\n-7.64\n-13.54\n10.43\n15.80\n-2.02\n-9.59\n0.58\n10.10\n1.93\n-17.23\n13.07\n6.46\n-12.71\n\n\n(Operating Activities) Change in Prepaid expenses and other assets\n11.20\n-0.37\n-4.54\n-1.60\n6.52\n-4.76\n-3.53\n-3.00\n6.54\n-1.50\n-20.15\n9.13\n5.20\n-8.49\n-9.37\n2.10\n-4.24\n3.46\n-9.35\n0.49\n11.59\n-10.77\n1.93\n3.91\n15.93\n2.72\n-12.23\n-3.26\n15.60\n-33.60\n-0.42\n-4.87\n0.87\n1.22\n-4.64\n5.90\n5.03\n-4.55\n-4.98\n2.09\nNA\n4.92\n4.02\n-3.92\n-5.35\n11.61\n-8.21\n-5.86\n-1.45\n3.72\n-1.00\n-14.11\n5.95\n6.23\n4.77\n-8.95\n0.82\n0.14\n\n\n(Operating Activities) Change in Accounts Payable\n-14.13\n-67.04\n46.79\n38.54\n-6.78\n-60.82\n-23.80\n75.87\n-14.72\n-38.79\n25.38\n35.60\n-8.73\n-48.27\n42.74\n29.21\n-38.45\n-74.49\n72.58\n35.22\n-28.44\n-84.49\n75.51\n28.43\n-9.93\n-47.90\n32.20\n34.58\n-19.26\n-51.27\n29.50\n41.09\n-8.76\n-59.51\n35.36\n34.99\n-31.88\n-59.96\n55.07\n39.21\nNA\n-3.94\n-64.89\n34.13\n25.63\n-7.39\n-68.12\n40.71\n44.28\n-4.70\n-69.71\n33.81\n29.51\n-10.31\n-87.45\n65.91\n8.14\n-4.95\n\n\n(Operating Activities) Change in Accounts Taxes Payable\n-3.73\n-13.39\n11.64\n-0.40\n-1.91\n-3.06\n11.60\n1.13\n0.20\n0.37\n-0.07\n-0.20\n-0.31\n-1.14\n0.58\n0.17\n-2.24\n2.59\n-0.01\n0.01\n0.00\n0.46\n0.00\n-0.33\n0.07\n0.07\n-0.01\n-0.52\nNA\n-22.87\n0.86\n0.31\n0.67\n-3.73\n-0.51\n1.02\n0.20\n-1.88\n2.27\n1.89\nNA\n0.64\n2.13\n-1.46\n-0.17\n5.26\n-2.30\n7.24\n0.12\n5.14\n-19.55\n12.55\n1.71\n1.02\n-10.21\n4.07\n0.25\n1.23\n\n\n(Operating Activities) Change in Reserve for Sales Return and allowances\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Operating Activities) Deferred Income Tax\nNA\n-2.58\nNA\nNA\nNA\n-57.86\n0.00\nNA\nNA\n-0.07\n0.00\nNA\nNA\n0.03\nNA\nNA\nNA\n-0.98\n0.00\nNA\nNA\n0.21\n0.00\nNA\nNA\n-1.25\n0.00\nNA\nNA\n-0.23\n-0.03\n0.10\n-0.09\n-0.25\nNA\n0.00\nNA\n1.04\nNA\nNA\nNA\n-1.22\n-0.03\nNA\nNA\nNA\n82.40\n0.35\n-0.11\n-0.24\n-7.74\n7.42\n0.00\n-0.31\n15.48\n-19.52\n-3.06\n-22.17\n\n\n(Operating Activities) Stock-based Compensation\n2.58\n2.06\n1.99\n1.86\n2.09\n1.65\n1.15\n1.16\n0.87\n0.71\n0.46\n0.38\n0.38\n0.80\n0.50\n0.71\n0.25\n1.00\n0.86\n0.40\n0.62\n0.69\n0.76\n0.31\n0.67\n0.86\n0.79\n0.71\n0.75\n0.37\n0.17\n0.46\n0.62\n0.11\n0.51\n0.44\n0.50\n0.48\n0.36\n0.36\nNA\n0.28\n0.52\n0.17\n0.18\n0.21\n-0.07\n0.38\n0.47\n0.34\n0.05\n0.43\n0.27\n0.85\n0.78\n1.53\n1.04\n1.09\n\n\n(Operating Activities) Cash Flow from Operating Activities\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-11.39\n17.60\n-19.44\n3.31\n9.93\n37.38\n-39.37\n-14.67\n33.38\n56.93\n-41.38\n11.46\n38.79\n26.16\n-72.55\n-21.58\nNA\n-11.05\n-5.61\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Property, Plant and Equipment\n2.23\n3.19\n0.80\n1.43\n3.49\n2.30\n2.81\n3.46\n1.82\n1.85\n2.65\n2.25\n1.47\n2.10\n1.84\n2.75\n1.58\n1.79\n2.42\n2.75\n2.46\n2.22\n3.04\n3.94\n2.57\n4.46\n2.85\n3.24\n4.37\n3.53\n5.13\n2.29\n3.82\n3.49\n3.17\n8.10\n3.08\n1.81\n1.82\n5.70\nNA\n1.20\n2.16\n2.06\n3.93\n1.98\n1.25\n4.23\n4.36\n3.22\n0.83\n2.99\n5.41\n3.22\n1.99\n3.04\n3.29\n4.08\n\n\n(Investing Activities) Proceeds from Asset Sales\n0.00\n0.04\n0.00\n-0.02\n0.02\n0.00\n0.00\n0.05\n0.00\n0.00\n0.00\n0.01\n0.06\n-0.17\n-0.01\n0.12\n0.00\n-0.01\n0.01\n0.00\n0.06\n-0.01\n0.08\n0.03\n0.00\n0.05\n0.00\n0.02\n0.00\n-0.01\nNA\nNA\n0.00\n-0.07\n0.00\n0.01\nNA\n0.00\n0.00\n-0.03\nNA\n0.01\n-0.86\n0.00\n-1.10\nNA\n-0.04\n0.00\n0.00\n-0.02\n-0.45\n0.00\n-0.04\n0.03\n-0.11\n0.00\n0.02\n-0.83\n\n\n(Investing Activities) Purchase of Businesses\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Marketable Securities and Investment\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n0.00\n0.00\nNA\n0.00\n0.00\n0.00\nNA\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n\n\n(Investing Activities) Proceeds from sale or maturity of Marketable Securities and Investment\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n0.07\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from maturities of Marketable Securities and Investment\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Cash Flow from Investing Activities\n-3.63\n-3.23\n-0.78\n-1.42\n-3.47\n-2.30\n-2.81\n-3.46\n-1.82\n-1.85\n-2.65\n-2.24\n-1.45\n-2.07\n-1.85\n-2.68\n-1.58\n-1.79\n-2.41\n-2.75\n-2.46\n-2.20\n-2.93\n-3.94\n-2.57\n-4.34\n-2.85\n-3.79\nNA\n-3.77\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-5.58\nNA\nNA\nNA\n-0.86\n-2.35\n-3.19\n-1.28\n-3.94\n-9.97\n-51.57\n-4.96\n-6.24\n-19.64\n-2.81\n-5.35\n-8.50\n-3.78\n0.31\n-4.86\n-7.62\n\n\n(Financing Activities) Proceeds from Issuance of Stock\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\n0.00\n9.66\nNA\n0.00\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment for Repurchase of Stock\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\n1.56\n2.10\n9.84\n6.20\n2.33\nNA\nNA\n0.00\n8.00\n24.00\n24\nNA\nNA\nNA\nNA\nNA\n0.00\n26.67\nNA\nNA\n0.00\n19.31\n0.00\n5.05\n5.64\n1.52\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Debt\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment of Debt\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash for Dividends\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n0.00\n1.54\n1.55\n2.16\n2.19\n2.60\n2.59\n2.59\n0.86\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash Flow from Financing Activities\n-20.00\n-0.58\n-1.28\n-30.50\n-39.93\n-0.76\n-18.76\n-10.62\n-0.89\n-0.25\n-0.09\n-32.29\n-0.16\n-15.07\n0.00\n4.30\n-0.17\n-5.00\n7.17\n-0.19\n-7.75\n7.69\n-13.18\n18.55\n-10.17\n5.87\n4.00\n-15.41\n-24.06\n2.03\n-1.56\n-2.79\n-12.62\n-31.21\n18.01\n-0.17\n-0.01\n-23.90\n-0.01\n76.16\nNA\n16.82\n-0.07\n69.64\n-96.34\n-14.35\n15.07\n-29.26\n-2.59\n-2.60\n-2.17\n-22.04\n0.13\n-4.98\n-5.78\n-4.61\n-10.19\n4.26\n\n\nEffect of Exchange Rate on Cash & Cash Equivalent\n-0.56\n1.18\n-0.79\n1.13\n0.33\n1.11\n-2.83\n-2.15\n-0.66\n-0.34\n-0.48\n0.38\n-0.06\n2.40\n1.13\n0.08\n-1.63\n1.47\n-0.90\n0.43\nNA\n-0.62\nNA\nNA\nNA\n0.92\nNA\nNA\nNA\n-1.54\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nChange in Cash, Cash Equivalents\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-6.02\nNA\nNA\nNA\n-11.01\nNA\nNA\nNA\nNA\n-19.04\n6.11\nNA\nNA\n-18.50\n46.76\n-41.22\n-32.22\n16.39\n21.02\n-29.06\n5.17\n33.57\n-17.48\n-74.10\n49.36\nNA\n-3.72\n65.62\n-18.20\n-95.64\n-23.96\n48.57\n-80.89\n-32.91\n-2.70\n25.01\n-14.60\n-27.62\n-3.88\n59.75\n-30.16\n-3.04\n21.33\n\n\n\n\n\n\n\n\n\n\nFinally, we will calculate the multiple trailing month value of the Income Statement and Cash Flow. These are easily comparable with the filing on SEC website.\n\n\nIncome Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_IS_12TM &lt;- calculate_trailing_months(df_std_IS,12)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_IS_12TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_IS_12TM_t &lt;- transpose_df(df_std_IS_12TM, order_df)\n\n# Format numeric columns to 2 decimal places\ndf_std_IS_12TM_t &lt;- df_std_IS_12TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_IS_12TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-09-03\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\nRevenue_12m\n694.15\n711.55\n716.04\n729.30\n782.79\n796.19\n852.26\n766.22\n658.15\n621.11\n562.12\n567.45\n533.86\n516.58\n537.27\n575.11\n591.53\n595.80\n588.09\n544.66\n555.26\n577.43\n572.11\n597.82\n611.60\n613.10\n643.50\n588.95\n631.20\n677.68\n606.46\n585.04\n760.26\n750.39\n768.78\n784.85\n797.18\n790.24\n758.55\n636.48\n598.01\n580.07\n575.63\n575.38\n578.98\n618.11\n613.44\n629.20\n647.13\n633.70\n632.62\n734.66\n750.92\n719.29\n847.90\nNA\nNA\nNA\n\n\nCost of Revenue_12m\n481.18\n488.21\n497.87\n526.20\n569.99\n584.90\n619.50\n550.44\n471.37\n438.16\n386.48\n392.12\n373.65\n366.11\n385.98\n417.58\n433.03\n439.31\n425.04\n398.14\n398.54\n412.09\n434.61\n462.87\n470.88\n465.32\n465.88\n473.11\n498.94\n530.64\n480.35\n386.32\n507.34\n502.98\n517.17\n577.66\n599.58\n594.11\n574.24\n498.88\n463.76\n481.40\n477.14\n480.92\n479.20\n473.68\n468.83\n488.21\n497.18\n485.55\n483.76\n494.10\n505.07\n484.30\n586.44\nNA\nNA\nNA\n\n\nGross Profit_12m\n212.96\n223.35\n218.19\n203.12\n212.81\n211.29\n232.76\n215.77\n186.78\n182.95\n170.35\n170.05\n154.92\n145.18\n147.58\n153.82\n154.80\n152.79\n151.88\n135.35\n145.54\n154.16\n154.15\n151.60\n157.38\n164.44\n177.62\nNA\nNA\nNA\nNA\n183.25\n237.45\n231.94\n236.14\n237.95\n228.36\n226.89\n215.07\n195.06\n191.71\n156.13\n155.95\n166.49\n171.81\n216.46\n216.65\n215.67\n224.63\n222.83\n223.53\n240.56\n245.85\n234.99\n261.45\nNA\nNA\nNA\n\n\nResearch and development_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nSales general and administrative costs_12m\n170.79\n164.25\n159.44\n153.02\n155.20\n150.01\n152.87\n152.88\n146.03\n144.20\n137.98\n136.76\n131.34\n134.86\n79.82\n87.45\n96.66\n99.59\n156.32\n155.91\n161.79\n185.14\n198.21\n210.02\n218.10\n205.22\n204.06\n208.59\nNA\nNA\nNA\nNA\n207.07\n203.47\n198.05\n214.02\n205.24\n205.58\n204.48\n186.86\n187.68\n191.57\n200.31\n207.47\n215.15\n215.41\n211.17\n204.14\n200.32\n196.62\n192.70\n192.31\n196.09\n193.41\n211.11\nNA\nNA\nNA\n\n\nOther Non Operating Income (Loss) Net_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-9.19\n-9.19\n-9.19\n-9.19\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOperating Income_12m\n42.19\n59.11\n58.75\n50.09\n57.30\n60.97\n79.60\n62.60\n40.76\n38.77\n39.07\n39.84\n28.27\n15.00\n7.32\n5.47\n-3.43\n-11.48\n-15.07\n-30.69\n-24.18\n-35.80\n-43.80\n-71.59\n-73.56\n-53.62\n-39.97\nNA\nNA\nNA\nNA\n28.22\n37.34\n35.43\n45.05\n45.25\n44.43\n42.62\n31.90\n12.94\n8.78\n-30.69\n-39.61\n-31.79\n-34.14\n10.26\n14.69\n18.32\n31.09\n32.98\n37.60\n48.25\n49.76\n41.58\n-56.74\nNA\nNA\nNA\n\n\nInterest Income_12m\n1.61\n1.35\n0.65\n0.33\n0.25\n0.13\n0.07\n0.01\n0.00\n0.00\n0.00\n0.00\n0.00\n0.01\n0.03\n0.05\n0.07\n0.09\n0.09\n0.09\n0.08\n0.06\n0.05\n0.04\n0.04\n0.03\n0.02\n0.02\nNA\nNA\nNA\nNA\n0.07\n0.07\n0.07\n0.08\n0.09\n0.10\n0.11\n0.12\n0.18\n0.28\n0.32\n0.35\n0.36\n0.54\n0.67\n0.69\n0.69\n0.50\n0.40\n0.40\n0.40\n0.36\n0.34\nNA\nNA\nNA\n\n\nInterest Expense_12m\n3.59\n6.45\n8.03\n10.94\n11.98\n11.18\n11.09\n9.40\n11.43\n14.11\n16.82\n19.73\n20.90\n21.57\n22.04\n21.09\n18.47\n15.94\n13.57\n12.05\n11.33\n10.25\n9.57\n8.50\n8.84\n9.83\n11.01\n12.00\nNA\nNA\nNA\nNA\n12.77\n12.66\n12.40\n12.49\n13.35\n13.22\n12.46\n11.90\n10.23\n9.31\n9.95\n10.35\n10.07\n10.05\n9.24\n8.17\n8.21\n8.19\n8.19\n7.10\n6.59\n6.67\n6.61\nNA\nNA\nNA\n\n\nOther income (expense) Net_12m\n6.30\n6.37\n4.83\n11.84\n-1.78\n-0.41\n5.36\n-4.32\n14.51\n30.32\n28.05\n30.42\n25.51\n-0.67\n1.18\n15.00\n7.61\n19.72\n14.99\n0.67\n2.51\n1.14\n4.32\n11.91\n9.48\n8.53\n6.50\n-35.01\n0.78\n-0.09\n-0.14\n32.26\n38.26\n33.03\n25.95\n32.70\n31.00\n29.30\n19.33\n0.92\n-1.63\n-40.28\n-49.89\n-42.50\n-44.58\n-0.34\n4.79\n9.47\n22.19\n24.28\n28.99\n40.73\n42.76\n34.55\n-63.69\nNA\nNA\nNA\n\n\nIncome Before Income Tax_12m\n30.69\n44.94\n45.24\n26.99\n46.87\n50.08\n63.09\n57.51\n14.81\n-5.66\n-5.80\n-10.31\n-18.15\n-5.91\n-15.93\n-30.66\n-29.56\n-47.21\n-43.71\n-43.49\n-38.09\n-47.25\n-57.74\n-92.04\n-91.91\n-72.01\n-57.49\n-9.23\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nProvision for (benefit) Income Tax_12m\n1.49\n6.84\n-41.85\n-42.66\n-42.81\n-41.01\n13.26\n1.99\n0.56\n0.23\n0.74\n0.17\n0.54\n0.73\n0.83\n2.12\n2.44\n1.92\n2.61\n3.54\n5.04\n2.94\n2.42\n1.39\n-1.03\n1.61\n2.80\n2.96\nNA\nNA\nNA\nNA\n2.82\n3.43\n3.43\n4.30\n4.66\n4.63\n3.72\n4.72\n3.26\n1.84\n2.62\n85.73\n91.43\n91.64\n86.15\n-17.11\n-9.83\n-8.05\n-9.00\n10.12\n6.63\n0.67\n-15.86\nNA\nNA\nNA\n\n\nNet Income (loss) (continous operations)_12m\n29.21\n38.11\n87.09\n69.65\n89.68\n91.09\n49.83\n55.53\n14.26\n-5.88\n-6.27\n-10.22\n-18.43\n-6.38\n-16.68\n-32.70\n-31.91\n-49.04\n-45.81\n-46.52\n-42.63\n-49.69\n-69.57\n-102.84\n-100.94\n-83.03\n-60.29\n-12.19\nNA\nNA\nNA\nNA\n14.95\n13.36\n23.16\n35.35\n33.56\n26.61\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n\n\n\n\n\nCash Flow Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_CF_12TM &lt;- calculate_trailing_months(df_std_CF,12)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_CF_12TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_CF_12TM_t &lt;- transpose_df(df_std_CF_12TM, order_df)\n\n# Format numeric columns to 2 decimal places\ndf_std_CF_12TM_t &lt;- df_std_CF_12TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_CF_12TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-06-09\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\n(Operating Activities) Cash Flow Depreciation, Depletion, Ammortization_12m\n9.26\n8.95\n8.82\n10.72\n11.36\n12.48\n12.16\n12.43\n12.68\n12.67\n10.30\n9.93\n11.71\n13.07\n8.67\n18.14\n21.46\n24.17\n35.13\n34.26\n34.44\n34.16\n33.16\n36.63\n39.44\n42.01\n48.92\n48.73\n46.57\n45.88\n43.07\n41.42\n39.72\n37.73\n34.12\n36.62\n37.66\nNA\nNA\nNA\nNA\n45.98\n46.02\n39.09\n45.67\n47.07\n46.15\n51.80\n37.39\n33.13\n31.54\n32.76\n33.98\n33.45\n38.56\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Receivable_12m\n-3.82\n21.76\n2.76\n-31.32\n-17.90\n-44.38\n-4.48\n56.43\n23.42\n43.75\n41.35\n38.61\n15.97\n-14.07\n-31.94\n-14.58\n-2.30\n-3.47\n-5.97\n-18.30\n-30.44\n-10.60\n-6.38\n11.18\n21.03\n-19.34\n-37.14\n-19.53\n13.01\n10.20\n-20.61\n15.74\n-18.85\n-71.13\n-11.48\n7.81\n38.96\nNA\nNA\nNA\nNA\n0.38\n-4.23\n15.33\n-29.75\n3.51\n-1.25\n-9.09\n3.29\n-8.00\n-27.81\n-47.68\n6.48\n-58.96\n1.67\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Inventory_12m\n-17.65\n-27.97\n-40.34\n-58.60\n-21.31\n-3.33\n19.38\n63.09\n48.66\n45.32\n35.22\n2.90\n-11.58\n-15.62\n-10.72\n4.16\n3.55\n0.38\n0.85\n-8.64\n-9.32\n-4.55\n-15.69\n-19.06\n-13.47\n-17.01\n5.07\n9.75\n14.00\n14.90\n-6.33\n-20.41\n-26.00\n-18.28\n-7.37\n26.74\n37.27\nNA\nNA\nNA\nNA\n-9.86\n-12.92\n-14.12\n-6.13\n5.05\n10.67\n14.62\n4.77\n-0.93\n3.02\n-4.62\n7.87\n4.23\n-10.41\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Prepaid expenses and other assets_12m\n4.69\n0.01\n-4.38\n-3.37\n-4.77\n-4.75\n-1.49\n-18.11\n-5.98\n-7.32\n-14.31\n-3.53\n-10.56\n-20.00\n-8.05\n-8.03\n-9.64\n6.19\n-8.04\n3.24\n6.66\n11.00\n24.49\n10.33\n3.16\n2.83\n-33.49\n-21.68\n-23.29\n-38.02\n-3.20\n-7.42\n3.35\n7.51\n1.74\n1.40\n-2.41\nNA\nNA\nNA\nNA\n-0.33\n6.36\n-5.87\n-7.81\n-3.91\n-11.80\n-4.59\n-12.84\n-5.44\n-2.93\n2.84\n8.00\n2.87\n-3.22\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Payable_12m\n4.16\n11.51\n17.73\n-52.86\n-15.53\n-23.47\n-1.44\n47.74\n7.47\n13.46\n3.98\n21.34\n14.95\n-14.77\n-40.99\n-11.15\n-5.14\n4.87\n-5.13\n-2.20\n-8.99\n9.52\n46.11\n2.80\n8.95\n-0.38\n-3.75\n-6.45\n0.06\n10.56\n2.32\n8.18\n2.08\n-21.04\n-21.49\n-1.78\n2.44\nNA\nNA\nNA\nNA\n-9.07\n-12.52\n-15.75\n-9.17\n9.48\n12.17\n10.58\n3.68\n-11.09\n-16.70\n-34.44\n-2.34\n-23.71\n-18.35\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Taxes Payable_12m\n-5.88\n-4.06\n6.27\n6.23\n7.76\n9.87\n13.30\n1.63\n0.30\n-0.21\n-1.72\n-1.07\n-0.70\n-2.63\n1.10\n0.51\n0.35\n2.59\n0.46\n0.47\n0.13\n0.20\n-0.19\n-0.20\n-0.39\nNA\nNA\nNA\nNA\n-21.03\n-1.89\n-3.26\n-2.55\n-3.02\n-1.17\n1.61\n2.48\nNA\nNA\nNA\nNA\n1.14\n5.76\n1.33\n10.03\n10.32\n10.20\n-7.05\n-1.74\n-0.15\n-4.27\n5.07\n-3.41\n-4.87\n-4.66\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Reserve for Sales Return and allowances_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Operating Activities) Deferred Income Tax_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-0.25\n-0.27\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n82.40\n-7.74\n-0.67\n-0.56\n-0.63\n22.59\n-4.35\n-7.41\n-29.27\nNA\nNA\nNA\n\n\n(Operating Activities) Stock-based Compensation_12m\n8.49\n8.00\n7.59\n6.75\n6.05\n4.83\n3.89\n3.20\n2.42\n1.93\n2.02\n2.06\n2.39\n2.26\n2.46\n2.82\n2.51\n2.88\n2.57\n2.47\n2.38\n2.43\n2.60\n2.63\n3.03\n3.11\n2.62\n2.00\n1.75\n1.62\n1.36\n1.70\n1.68\n1.56\n1.93\n1.78\n1.70\nNA\nNA\nNA\nNA\n1.15\n1.08\n0.49\n0.70\n0.99\n1.12\n1.24\n1.29\n1.09\n1.60\n2.33\n3.43\n4.20\n4.44\nNA\nNA\nNA\n\n\n(Operating Activities) Cash Flow from Operating Activities_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-9.92\n11.40\n31.18\n11.25\n-6.73\n16.72\n36.27\n34.26\n60.39\n65.80\n35.03\n3.86\n-29.18\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Property, Plant and Equipment_12m\n7.65\n8.91\n8.02\n10.03\n12.06\n10.39\n9.94\n9.78\n8.57\n8.22\n8.47\n7.66\n8.16\n8.27\n7.96\n8.54\n8.54\n9.42\n9.85\n10.47\n11.66\n11.77\n14.01\n13.82\n13.12\n14.92\n13.99\n16.27\n15.32\n14.77\n14.73\n12.77\n18.58\n17.84\n16.16\n14.81\n12.41\nNA\nNA\nNA\nNA\n9.35\n10.13\n9.22\n11.39\n11.82\n13.06\n12.64\n11.40\n12.45\n12.45\n13.61\n13.66\n11.54\n12.40\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from Asset Sales_12m\n0.02\n0.04\n0.00\n0.00\n0.07\n0.05\n0.05\n0.05\n0.01\n0.07\n-0.10\n-0.11\n0.00\n-0.06\n0.10\n0.12\n0.00\n0.06\n0.06\n0.13\n0.16\n0.10\n0.16\n0.08\n0.07\n0.07\n0.01\nNA\nNA\nNA\nNA\nNA\n-0.06\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-1.95\nNA\nNA\nNA\nNA\n-0.06\n-0.47\n-0.47\n-0.51\n-0.46\n-0.12\n-0.12\n-0.06\n-0.92\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Businesses_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Marketable Securities and Investment_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n0.00\n0.00\n0.00\n0.00\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from sale or maturity of Marketable Securities and Investment_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from maturities of Marketable Securities and Investment_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Cash Flow from Investing Activities_12m\n-9.06\n-8.90\n-7.97\n-10.00\n-12.04\n-10.39\n-9.94\n-9.78\n-8.56\n-8.19\n-8.41\n-7.61\n-8.05\n-8.18\n-7.90\n-8.46\n-8.53\n-9.41\n-9.82\n-10.34\n-11.53\n-11.64\n-13.78\n-13.70\n-13.55\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-7.68\n-10.76\n-18.38\n-66.76\n-70.44\n-72.74\n-82.41\n-33.65\n-34.04\n-36.30\n-20.44\n-17.32\n-16.83\n-15.95\nNA\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Stock_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment for Repurchase of Stock_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n13.50\n19.70\n20.47\nNA\nNA\nNA\nNA\nNA\n56\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n24.36\n30.00\n12.21\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Debt_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment of Debt_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash for Dividends_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n3.09\n5.25\n7.44\n8.50\n9.54\n9.97\n8.64\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash Flow from Financing Activities_12m\n-52.36\n-72.29\n-72.47\n-89.95\n-70.07\n-31.03\n-30.52\n-11.85\n-33.52\n-32.79\n-47.61\n-47.52\n-10.93\n-10.94\n-0.87\n6.30\n1.81\n-5.77\n6.92\n-13.43\n5.31\n2.89\n1.07\n18.25\n-15.71\n-29.60\n-33.44\n-39.00\n-26.38\n-14.94\n-48.18\n-28.61\n-25.99\n-13.38\n-6.07\n-24.09\n52.24\nNA\nNA\nNA\nNA\n-9.95\n-41.12\n-25.98\n-124.88\n-31.13\n-19.38\n-36.62\n-29.40\n-26.68\n-29.06\n-32.67\n-15.24\n-25.56\n-16.32\nNA\nNA\nNA\n\n\nEffect of Exchange Rate on Cash & Cash Equivalent_12m\n0.96\n1.85\n1.78\n-0.26\n-3.54\n-4.53\n-5.98\n-3.63\n-1.10\n-0.50\n2.24\n3.85\n3.55\n1.98\n1.05\n-0.98\n-0.63\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nChange in Cash, Cash Equivalents_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-45.18\n-10.29\n-36.03\n-23.87\n13.52\n30.70\n-7.80\n-52.84\n-8.65\nNA\nNA\nNA\nNA\n-51.94\n-72.18\n-89.23\n-151.92\n-89.19\n-67.93\n-91.49\n-25.20\n-19.91\n-21.09\n13.65\n-1.91\n22.67\n47.88\nNA\nNA\nNA\n\n\n\n\n\n\n\n\n\n\nIncome Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_IS_9TM &lt;- calculate_trailing_months(df_std_IS,9)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_IS_9TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_IS_9TM_t &lt;- transpose_df(df_std_IS_9TM, order_df)\n\n# Format numeric columns to 2 decimal places\ndf_std_IS_9TM_t &lt;- df_std_IS_9TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_IS_9TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-09-03\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\nRevenue_9m\n527.22\n604.07\n584.15\n406.30\n562.37\n675.31\n664.30\n529.26\n545.80\n537.27\n433.15\n325.16\n455.10\n450.02\n387.61\n294.98\n496.35\n524.97\n446.14\n307.96\n449.48\n484.43\n435.48\n335.41\n492.04\n518.60\n476.47\n381.09\n469.39\n536.70\n510.65\n398.60\n423.23\n619.28\n654.58\n582.34\n447.82\n666.07\n676.04\n556.04\n287.12\n473.84\n497.56\n495.19\n264.49\n472.75\n540.04\n533.25\n314.71\n501.77\n560.30\n536.67\n402.24\n618.99\n646.97\n649.91\nNA\nNA\n\n\nCost of Revenue_9m\n365.44\n412.16\n394.55\n295.11\n410.46\n493.94\n481.58\n388.41\n390.91\n380.41\n300.24\n224.45\n311.66\n315.90\n279.87\n218.31\n355.59\n382.82\n333.20\n225.77\n320.70\n342.05\n320.25\n262.24\n385.03\n400.84\n350.96\n265.25\n387.26\n434.46\n415.72\n272.49\n274.64\n411.16\n438.35\n403.34\n344.96\n507.76\n515.29\n399.92\n244.26\n377.41\n422.45\n378.18\n261.42\n375.21\n418.99\n366.09\n270.43\n398.71\n435.71\n361.64\n267.35\n418.23\n436.25\n453.98\nNA\nNA\n\n\nGross Profit_9m\n161.76\n191.91\n189.62\n111.21\n151.92\n181.37\n182.72\n140.85\n154.88\n156.86\n132.91\n95.43\n138.15\n128.83\n107.74\n72.96\n137.05\n138.45\n112.95\n71.02\n117.60\n131.20\n115.23\n89.82\n123.66\n134.42\n125.52\n115.84\nNA\nNA\nNA\n126.11\n133.12\n192.65\n200.76\n179.00\n133.62\n189.07\n191.51\n156.12\n100.32\n153.89\n132.57\n117.01\n75.10\n169.57\n193.08\n167.17\n118.96\n177.74\n199.26\n175.03\n134.89\n200.76\n210.72\n195.92\nNA\nNA\n\n\nResearch and development_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nSales general and administrative costs_9m\n136.04\n128.41\n115.18\n114.85\n118.27\n119.36\n105.75\n114.70\n115.95\n115.38\n97.08\n99.80\n106.68\n102.52\n93.96\n42.86\n62.79\n64.32\n113.73\n111.73\n122.04\n126.52\n142.55\n154.03\n170.27\n159.48\n149.56\n148.07\n160.76\nNA\nNA\nNA\n147.37\n161.17\n158.47\n141.58\n154.32\n162.94\n166.00\n132.04\n135.94\n145.04\n153.09\n145.49\n155.73\n168.62\n168.19\n149.19\n144.72\n153.53\n153.64\n137.75\n136.71\n153.00\n154.35\n156.55\nNA\nNA\n\n\nOther Non Operating Income (Loss) Net_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-21.32\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n-9.19\n-9.19\n-9.19\n0.00\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOperating Income_9m\n25.74\n63.51\n74.45\n-3.65\n33.64\n61.70\n76.67\n25.86\n38.94\n41.49\n35.84\n2.33\n38.02\n30.99\n11.77\n-30.19\n15.22\n12.56\n-7.03\n-50.73\n-12.04\n-0.14\n-27.76\n-63.84\n-59.45\n-37.90\n-37.58\n-32.22\nNA\nNA\nNA\n20.59\n-7.29\n38.44\n49.25\n37.42\n0.62\n47.44\n46.82\n24.07\n-30.87\n13.60\n-15.77\n-28.48\n-71.44\n10.15\n34.10\n18.00\n-18.98\n30.98\n52.39\n37.28\n-1.82\n47.76\n56.37\n-67.71\nNA\nNA\n\n\nInterest Income_9m\n1.52\n1.23\n0.59\n0.27\n0.24\n0.13\n0.07\n0.01\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.01\n0.03\n0.05\n0.06\n0.07\n0.07\n0.07\n0.05\n0.04\n0.03\n0.03\n0.03\n0.02\n0.01\n0.01\nNA\nNA\nNA\n0.05\n0.05\n0.05\n0.06\n0.06\n0.07\n0.08\n0.09\n0.09\n0.15\n0.25\n0.29\n0.26\n0.23\n0.47\n0.61\n0.59\n0.38\n0.30\n0.32\n0.30\n0.28\n0.26\n0.26\nNA\nNA\n\n\nInterest Expense_9m\n2.29\n3.45\n5.74\n6.59\n9.64\n8.98\n8.89\n6.74\n7.06\n9.23\n11.91\n14.16\n15.36\n16.02\n16.66\n16.47\n15.55\n12.92\n10.56\n8.95\n9.13\n8.31\n7.24\n6.47\n6.30\n6.90\n7.50\n8.98\n9.46\nNA\nNA\nNA\n9.66\n9.55\n9.43\n9.19\n9.38\n10.24\n10.25\n9.16\n7.93\n7.25\n7.10\n7.21\n8.05\n8.01\n7.20\n6.10\n6.15\n6.17\n6.15\n6.12\n5.04\n4.57\n4.63\n5.63\nNA\nNA\n\n\nOther income (expense) Net_9m\n-1.10\n7.19\n6.66\n4.75\n4.44\n-0.96\n1.42\n-1.73\n1.90\n13.96\n26.38\n30.64\n17.81\n9.15\n-2.34\n1.40\n7.30\n17.43\n16.20\n1.39\n0.36\n0.22\n2.35\n5.04\n9.76\n8.56\n6.56\n-0.37\n-34.73\n0.81\n-0.03\n34.50\n-3.25\n39.16\n33.14\n28.19\n-8.81\n37.13\n36.49\n14.82\n-38.89\n6.20\n-23.12\n-35.99\n-79.76\n1.90\n26.43\n11.30\n-25.71\n24.43\n45.92\n30.82\n-7.17\n42.91\n51.48\n-73.60\nNA\nNA\n\n\nIncome Before Income Tax_9m\n23.03\n51.64\n61.46\n-15.26\n19.33\n53.57\n66.30\n20.84\n29.97\n18.30\n-2.45\n-42.47\n4.85\n5.81\n-2.56\n-48.09\n-7.66\n-17.84\n-33.84\n-61.14\n-21.59\n-8.72\n-37.38\n-75.39\n-75.54\n-53.38\n-51.65\n-40.84\n7.14\nNA\nNA\nNA\n-13.74\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nProvision for (benefit) Income Tax_9m\n0.01\n8.22\n12.48\n-54.23\n-44.14\n-41.43\n13.32\n1.69\n0.66\n0.14\n0.29\n0.44\n0.27\n0.45\n0.28\n1.10\n1.85\n2.16\n1.37\n1.59\n2.95\n5.28\n1.70\n0.47\n-0.70\n1.31\n0.89\n1.88\n3.29\nNA\nNA\nNA\n1.44\n2.12\n3.00\n3.12\n2.92\n3.35\n4.20\n2.54\n2.98\n1.98\n2.32\n0.44\n85.45\n91.57\n91.34\n0.86\n-23.09\n-9.90\n-2.86\n8.97\n-3.14\n4.78\n6.81\n-17.01\nNA\nNA\n\n\nNet Income (loss) (continous operations)_9m\n23.03\n43.43\n48.98\n38.97\n63.47\n95.00\n52.98\n19.15\n29.32\n18.17\n-2.73\n-42.65\n4.84\n5.62\n-2.84\n-49.11\n-9.43\n-19.91\n-35.20\n-62.22\n-24.04\n-13.50\n-39.08\n-85.27\n-84.25\n-64.75\n-52.54\n-42.72\n4.50\nNA\nNA\nNA\n-30.91\n19.09\n30.74\n32.55\n-10.51\n39.29\n34.19\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n\n\n\n\n\nCash Flow Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_CF_9TM &lt;- calculate_trailing_months(df_std_CF,9)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_CF_9TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_CF_9TM_t &lt;- transpose_df(df_std_CF_9TM, order_df)\n\n\n# Format numeric columns to 2 decimal places\ndf_std_CF_9TM_t &lt;- df_std_CF_9TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_CF_9TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-06-09\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\n(Operating Activities) Cash Flow Depreciation, Depletion, Ammortization_9m\n6.77\n7.66\n6.51\n6.09\n8.23\n10.07\n10.17\n7.53\n9.30\n10.27\n10.68\n5.40\n6.55\n9.31\n13.45\n4.14\n12.98\n17.70\n28.95\n21.13\n25.78\n27.97\n27.98\n20.03\n27.97\n33.25\n36.83\n32.32\n37.26\n37.81\n33.79\n26.66\n32.11\n31.65\n28.45\n19.36\n29.01\n31.58\nNA\nNA\nNA\n37.19\n39.63\n33.81\n20.46\n36.88\n40.68\n40.87\n26.59\n27.20\n27.66\n20.61\n21.96\n28.05\n29.57\n26.41\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Receivable_9m\n-50.94\n38.98\n104.97\n-72.31\n-78.44\n-0.68\n57.83\n-45.47\n-4.11\n67.12\n106.06\n-60.55\n11.08\n39.34\n50.64\n-131.10\n-19.47\n51.11\n79.11\n-122.49\n-35.47\n24.14\n74.48\n-110.57\n6.15\n55.77\n61.52\n-158.89\n-34.41\n88.12\n108.86\n-159.97\n-31.68\n59.07\n58.34\n-187.19\n-5.02\n169.16\nNA\nNA\nNA\n-29.55\n36.24\n152.51\n-147.72\n-59.68\n43.98\n135.93\n-127.06\n-59.90\n37.23\n117.21\n-178.03\n-45.42\n6.08\n166.56\nNA\nNA\n\n\n(Operating Activities) Change in Inventory_9m\n-18.72\n-11.34\n-11.79\n-44.11\n-59.67\n-4.68\n25.22\n33.87\n24.73\n47.31\n51.16\n6.00\n-21.03\n-9.59\n0.32\n-7.62\n-5.29\n9.58\n11.42\n-10.93\n-17.48\n-0.12\n6.02\n-17.98\n-27.22\n-9.04\n4.70\n6.15\n-4.00\n21.97\n14.53\n-9.93\n-38.41\n-18.93\n2.58\n3.11\n14.33\n36.62\nNA\nNA\nNA\n-14.48\n-5.28\n-0.58\n-16.56\n-10.75\n12.69\n24.21\n4.19\n-11.03\n1.09\n12.61\n-5.20\n-2.23\n2.30\n6.82\nNA\nNA\n\n\n(Operating Activities) Change in Prepaid expenses and other assets_9m\n6.29\n-6.51\n0.38\n0.16\n-1.77\n-11.29\n0.01\n2.04\n-15.11\n-12.52\n-5.82\n5.84\n-12.66\n-15.76\n-11.51\n1.32\n-10.13\n-5.40\n2.73\n1.31\n2.75\n-4.93\n21.77\n22.56\n6.42\n-12.77\n0.11\n-21.26\n-18.42\n-38.89\n-4.42\n-2.78\n-2.55\n2.48\n6.29\n6.38\n-4.50\n-7.44\nNA\nNA\nNA\n5.02\n-5.25\n2.34\n-1.95\n-2.46\n-15.52\n-3.59\n1.27\n-11.39\n-9.16\n-1.93\n16.95\n2.05\n-3.36\n-7.99\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Payable_9m\n-34.38\n18.29\n78.55\n-29.06\n-91.40\n-8.75\n37.35\n22.36\n-28.13\n22.19\n52.25\n-21.40\n-14.26\n23.68\n33.50\n-83.73\n-40.36\n33.31\n79.36\n-77.71\n-37.42\n19.45\n94.01\n-29.40\n-25.63\n18.88\n47.52\n-35.95\n-41.03\n19.32\n61.83\n-27.18\n-32.91\n10.84\n38.47\n-56.85\n-36.77\n34.32\nNA\nNA\nNA\n-34.70\n-5.13\n52.37\n-49.88\n-34.80\n16.87\n80.29\n-30.13\n-40.60\n-6.39\n53.01\n-68.25\n-31.85\n-13.40\n69.10\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Taxes Payable_9m\n-5.48\n-2.15\n9.33\n-5.37\n6.63\n9.67\n12.93\n1.70\n0.50\n0.10\n-0.58\n-1.65\n-0.87\n-0.39\n-1.49\n0.52\n0.34\n2.59\n0.00\n0.47\n0.46\n0.13\n-0.26\n-0.19\n0.13\n-0.46\nNA\nNA\nNA\n-21.70\n1.84\n-2.75\n-3.57\n-3.22\n0.71\n-0.66\n0.59\n2.28\nNA\nNA\nNA\n1.31\n0.50\n3.63\n2.79\n10.20\n5.06\n12.50\n-14.29\n-1.86\n-5.29\n15.28\n-7.48\n-5.12\n-5.89\n5.55\nNA\nNA\n\n\n(Operating Activities) Change in Reserve for Sales Return and allowances_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Operating Activities) Deferred Income Tax_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-0.16\n-0.02\n-0.24\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n82.64\n0.00\n-8.09\n-0.56\n-0.32\n7.11\n15.17\n-4.35\n-7.10\n-44.75\nNA\nNA\n\n\n(Operating Activities) Stock-based Compensation_9m\n6.63\n5.91\n5.94\n5.60\n4.89\n3.96\n3.18\n2.74\n2.04\n1.55\n1.22\n1.56\n1.68\n2.01\n1.46\n1.96\n2.11\n2.26\n1.88\n1.71\n2.07\n1.76\n1.74\n1.84\n2.32\n2.36\n2.25\n1.83\n1.29\n1.00\n1.25\n1.19\n1.24\n1.06\n1.45\n1.42\n1.34\n1.20\nNA\nNA\nNA\n0.97\n0.87\n0.56\n0.32\n0.52\n0.78\n1.19\n0.86\n0.82\n0.75\n1.55\n1.90\n3.16\n3.35\n3.66\nNA\nNA\n\n\n(Operating Activities) Cash Flow from Operating Activities_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-13.23\n1.47\n-6.20\n50.62\n7.94\n-16.66\n-20.66\n75.64\n48.93\n27.01\n8.87\n76.41\n-7.60\n-67.97\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Property, Plant and Equipment_9m\n6.22\n5.42\n5.72\n7.22\n8.60\n8.57\n8.09\n7.13\n6.32\n6.75\n6.37\n5.82\n5.41\n6.69\n6.17\n6.12\n5.79\n6.96\n7.63\n7.43\n7.72\n9.20\n9.55\n10.97\n9.88\n10.55\n10.46\n11.14\n13.03\n10.95\n11.24\n9.60\n10.48\n14.76\n14.35\n12.99\n6.71\n9.33\nNA\nNA\nNA\n5.42\n8.15\n7.97\n7.16\n7.46\n9.84\n11.81\n8.41\n7.04\n9.23\n11.62\n10.62\n8.25\n8.32\n10.41\nNA\nNA\n\n\n(Investing Activities) Proceeds from Asset Sales_9m\n0.04\n0.02\n0.00\n0.00\n0.02\n0.05\n0.05\n0.05\n0.00\n0.01\n0.07\n-0.10\n-0.12\n-0.06\n0.11\n0.11\n0.00\n0.00\n0.07\n0.05\n0.13\n0.10\n0.11\n0.08\n0.05\n0.07\n0.02\n0.01\nNA\nNA\nNA\nNA\n-0.07\n-0.06\nNA\nNA\nNA\n-0.03\nNA\nNA\nNA\n-0.85\n-1.96\nNA\nNA\nNA\n-0.04\n-0.02\n-0.47\n-0.47\n-0.49\n-0.01\n-0.12\n-0.08\n-0.09\n-0.81\nNA\nNA\n\n\n(Investing Activities) Purchase of Businesses_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Marketable Securities and Investment_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\nNA\nNA\n\n\n(Investing Activities) Proceeds from sale or maturity of Marketable Securities and Investment_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from maturities of Marketable Securities and Investment_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Cash Flow from Investing Activities_9m\n-7.64\n-5.43\n-5.67\n-7.19\n-8.58\n-8.57\n-8.09\n-7.13\n-6.32\n-6.74\n-6.34\n-5.76\n-5.37\n-6.60\n-6.11\n-6.05\n-5.78\n-6.95\n-7.62\n-7.41\n-7.59\n-9.07\n-9.44\n-10.85\n-9.76\n-10.98\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-6.40\n-6.82\n-8.41\n-15.19\n-65.48\n-66.50\n-62.77\n-30.84\n-28.69\n-27.80\n-16.66\n-17.63\n-11.97\n-8.33\n-12.17\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Stock_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n9.66\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment for Repurchase of Stock_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n3.66\n13.50\n18.14\n18.37\nNA\nNA\nNA\nNA\n32.00\n56\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n19.31\n24.36\n10.69\n12.21\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Debt_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment of Debt_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash for Dividends_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n1.54\n3.09\n5.25\n5.90\n6.95\n7.38\n7.78\n6.04\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash Flow from Financing Activities_9m\n-21.86\n-32.36\n-71.71\n-71.19\n-59.45\n-30.14\n-30.27\n-11.76\n-1.23\n-32.63\n-32.54\n-47.52\n-15.23\n-10.77\n4.13\n-0.87\n2.00\n1.98\n-0.77\n-0.25\n-13.24\n13.06\n-4.80\n14.25\n-0.30\n-5.54\n-35.47\n-37.44\n-23.59\n-2.32\n-16.97\n-46.62\n-25.82\n-13.37\n17.83\n-24.08\n-23.92\n52.25\nNA\nNA\nNA\n86.39\n-26.77\n-41.05\n-95.62\n-28.54\n-16.78\n-34.45\n-7.36\n-26.81\n-24.08\n-26.89\n-10.63\n-15.37\n-20.58\n-10.54\nNA\nNA\n\n\nEffect of Exchange Rate on Cash & Cash Equivalent_9m\n-0.17\n1.52\n0.67\n2.57\n-1.39\n-3.87\n-5.64\n-3.15\n-1.48\n-0.44\n-0.16\n2.72\n3.47\n3.61\n-0.42\n-0.08\n-1.06\n1.00\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nChange in Cash, Cash Equivalents_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-12.96\n-26.68\n-57.05\n5.19\n8.35\n-2.87\n9.68\n21.26\n-58.01\n-42.22\nNA\nNA\nNA\n43.70\n-48.22\n-137.80\n-71.03\n-56.28\n-65.23\n-116.50\n-10.60\n7.71\n-17.21\n-46.10\n28.25\n25.71\n26.55\n-11.87\nNA\nNA\n\n\n\n\n\n\n\n\n\n\nIncome Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_IS_6TM &lt;- calculate_trailing_months(df_std_IS,6)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_IS_6TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_IS_6TM_t &lt;- transpose_df(df_std_IS_6TM, order_df)\n\n\n# Format numeric columns to 2 decimal places\ndf_std_IS_6TM_t &lt;- df_std_IS_6TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_IS_6TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-09-03\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\nRevenue_6m\n217.48\n437.14\n476.67\n274.41\n239.37\n454.89\n543.42\n341.30\n308.84\n424.92\n349.31\n196.19\n212.81\n371.26\n321.05\n145.32\n216.22\n429.79\n375.31\n166.01\n212.78\n378.65\n342.48\n198.78\n229.63\n399.04\n381.97\n214.06\n261.53\n374.89\n369.67\n302.79\n236.79\n282.25\n523.47\n468.14\n245.31\n316.71\n551.87\n473.53\n206.68\n162.95\n391.33\n417.12\n184.30\n158.26\n394.68\n459.85\n218.76\n169.35\n428.37\n464.35\n204.25\n270.31\n546.67\n448.98\n301.23\nNA\n\n\nCost of Revenue_6m\n162.68\n296.42\n318.50\n191.79\n179.37\n334.41\n390.62\n250.49\n228.88\n299.95\n242.49\n138.21\n143.99\n253.91\n229.66\n112.20\n156.32\n305.38\n276.71\n133.93\n148.33\n264.21\n250.21\n147.88\n184.40\n314.99\n286.48\n150.33\n179.40\n322.78\n319.54\n207.86\n160.81\n178.46\n346.53\n324.52\n170.64\n253.14\n428.94\n340.97\n145.30\n157.91\n318.46\n323.49\n158.68\n157.43\n320.52\n316.25\n148.31\n171.96\n348.87\n313.59\n134.89\n180.51\n370.18\n303.79\n216.26\nNA\n\n\nGross Profit_6m\n54.78\n140.71\n158.18\n82.64\n60.01\n120.48\n152.80\n90.81\n79.96\n124.96\n106.82\n57.99\n63.53\n112.06\n91.39\n33.12\n56.19\n120.70\n98.61\n32.09\n53.27\n103.26\n92.27\n50.90\n61.88\n100.70\n95.50\n63.74\n82.12\nNA\nNA\n94.93\n75.98\n88.32\n161.47\n143.62\n74.67\n94.33\n153.69\n132.56\n61.38\n62.50\n130.33\n93.63\n25.62\n72.86\n146.19\n143.60\n70.46\n72.07\n154.17\n150.76\n69.36\n89.80\n176.49\n145.19\n84.96\nNA\n\n\nResearch and development_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nSales general and administrative costs_6m\n91.45\n93.66\n79.34\n70.59\n80.10\n82.43\n75.10\n67.58\n77.77\n85.30\n68.26\n58.90\n69.72\n77.86\n61.62\n57.00\n18.20\n30.45\n78.46\n69.14\n77.86\n86.77\n83.93\n98.37\n114.28\n111.65\n103.82\n93.57\n100.24\n115.02\nNA\nNA\n90.90\n101.47\n116.17\n102.00\n81.88\n112.02\n123.36\n93.56\n81.12\n93.30\n106.56\n98.27\n93.75\n109.20\n121.40\n106.21\n89.77\n97.93\n110.55\n98.69\n82.15\n93.62\n113.94\n99.79\n97.17\nNA\n\n\nOther Non Operating Income (Loss) Net_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n-21.32\nNA\nNA\n0.00\nNA\nNA\n0.00\n0.00\n-9.19\n-9.19\n0.00\n0.00\nNA\nNA\n0.00\n0.00\nNA\nNA\n0.00\nNA\nNA\n\n\nOperating Income_6m\n-36.66\n47.06\n78.85\n12.05\n-20.10\n38.04\n77.40\n22.93\n2.20\n39.67\n38.56\n-0.90\n0.51\n40.74\n27.76\n-25.74\n-20.44\n31.21\n17.01\n-42.69\n-32.08\n12.00\n7.90\n-47.80\n-51.70\n-23.79\n-21.86\n-29.83\n-18.11\nNA\nNA\n34.41\n-14.92\n-6.19\n52.26\n41.62\n-7.21\n3.63\n51.64\n38.99\n-19.74\n-26.05\n28.52\n-4.64\n-68.13\n-27.15\n33.99\n37.41\n-19.30\n-19.09\n50.39\n52.07\n-12.79\n-3.82\n62.55\n45.40\n-119.29\nNA\n\n\nInterest Income_6m\n1.14\n1.14\n0.47\n0.21\n0.18\n0.12\n0.07\n0.01\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.01\n0.03\n0.04\n0.04\n0.05\n0.05\n0.04\n0.03\n0.02\n0.02\n0.02\n0.02\n0.01\n0.00\n0.01\nNA\nNA\n0.04\n0.03\n0.03\n0.04\n0.04\n0.04\n0.05\n0.06\n0.06\n0.06\n0.12\n0.22\n0.20\n0.13\n0.16\n0.41\n0.51\n0.28\n0.18\n0.22\n0.22\n0.18\n0.18\n0.18\n0.16\nNA\n\n\nInterest Expense_6m\n0.85\n2.15\n2.74\n4.30\n5.29\n6.64\n6.69\n4.54\n4.40\n4.86\n7.03\n9.25\n9.79\n10.48\n11.11\n11.09\n10.93\n10.00\n7.54\n5.94\n6.03\n6.11\n5.30\n4.14\n4.27\n4.36\n4.57\n5.47\n6.44\n6.53\nNA\nNA\n6.45\n6.44\n6.32\n6.22\n6.08\n6.27\n7.27\n6.95\n5.19\n4.95\n5.04\n4.36\n4.91\n5.99\n5.16\n4.06\n4.08\n4.11\n4.13\n4.08\n4.06\n3.02\n2.53\n3.65\n4.08\nNA\n\n\nOther income (expense) Net_6m\n-1.18\n-0.21\n7.48\n6.58\n-2.65\n5.26\n0.87\n-5.67\n4.49\n1.35\n10.02\n28.97\n18.03\n1.45\n7.48\n-2.12\n-6.30\n17.12\n13.91\n2.60\n1.08\n-1.93\n1.43\n3.07\n2.89\n8.84\n6.59\n-0.31\n-0.09\n-34.70\n0.87\n34.61\n-1.01\n-2.35\n39.27\n35.38\n-13.32\n-2.68\n44.32\n31.98\n-24.99\n-31.06\n23.36\n-9.22\n-73.25\n-33.28\n28.67\n32.94\n-23.88\n-23.47\n46.07\n47.75\n-17.08\n-7.02\n59.84\n41.57\n-123.53\nNA\n\n\nIncome Before Income Tax_6m\n-37.47\n43.98\n68.16\n0.96\n-22.92\n26.03\n69.79\n24.05\n-6.70\n33.46\n21.51\n-39.12\n-27.31\n28.81\n9.16\n-34.72\n-25.09\n4.06\n-4.47\n-51.27\n-39.24\n7.78\n1.15\n-55.03\n-58.89\n-37.01\n-33.02\n-35.00\n-24.47\n25.77\nNA\nNA\n-20.39\n-10.30\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nProvision for (benefit) Income Tax_6m\n-12.37\n6.74\n13.86\n0.10\n-55.71\n-42.76\n12.90\n1.75\n0.36\n0.24\n0.20\n-0.01\n0.54\n0.18\n0.00\n0.55\n0.83\n1.57\n1.61\n0.35\n1.00\n3.19\n4.04\n-0.25\n-1.62\n1.64\n0.59\n-0.03\n2.21\n2.99\nNA\nNA\n1.13\n0.74\n1.69\n2.69\n1.74\n1.61\n2.92\n3.02\n0.80\n1.70\n2.46\n0.14\n0.16\n85.59\n91.27\n6.05\n-5.12\n-23.16\n-4.71\n15.11\n-4.29\n-4.99\n10.92\n5.66\n-26.78\nNA\n\n\nNet Income (loss) (continous operations)_6m\n-25.09\n37.25\n54.30\n0.86\n32.79\n68.79\n56.89\n22.30\n-7.06\n33.23\n21.32\n-39.11\n-27.59\n28.89\n9.16\n-35.27\n-25.84\n2.57\n-6.07\n-51.61\n-39.74\n5.09\n-2.89\n-54.78\n-66.68\n-48.06\n-34.26\n-34.97\n-26.03\n22.78\nNA\nNA\n-21.52\n-26.77\n36.47\n40.13\n-13.31\n-4.78\n46.87\n31.39\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n\n\n\n\n\nCash Flow Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_CF_6TM &lt;- calculate_trailing_months(df_std_CF,6)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_CF_6TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_CF_6TM_t &lt;- transpose_df(df_std_CF_6TM, order_df)\n\n# Format numeric columns to 2 decimal places\ndf_std_CF_6TM_t &lt;- df_std_CF_6TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_CF_6TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-06-09\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\n(Operating Activities) Cash Flow Depreciation, Depletion, Ammortization_6m\n4.04\n5.17\n5.22\n3.78\n3.60\n6.94\n7.76\n5.54\n4.40\n6.89\n8.28\n5.78\n2.02\n4.15\n9.69\n8.92\n-1.02\n9.22\n22.48\n14.95\n12.65\n19.31\n21.79\n14.85\n11.37\n21.78\n28.07\n20.23\n20.85\n28.50\n25.72\n17.38\n17.35\n24.04\n22.37\n13.69\n11.75\n22.93\n25.91\nNA\nNA\n18.56\n30.84\n27.42\n15.18\n11.67\n30.49\n35.40\n15.66\n16.40\n21.73\n16.73\n9.81\n16.03\n24.17\n17.42\n14.39\nNA\n\n\n(Operating Activities) Change in Accounts Receivable_6m\n-126.01\n-8.14\n122.19\n29.90\n-119.43\n-61.22\n101.53\n16.84\n-106.01\n39.59\n129.43\n4.16\n-88.08\n34.45\n104.05\n-48.52\n-135.99\n33.94\n133.69\n-37.41\n-139.66\n19.11\n109.22\n-29.71\n-115.60\n40.89\n136.63\n-60.23\n-173.77\n40.70\n186.78\n-30.50\n-207.39\n46.24\n188.54\n-117.37\n-200.02\n125.18\n238.98\nNA\nNA\n-192.60\n6.31\n192.98\n-10.54\n-177.65\n-19.21\n181.16\n17.96\n-190.25\n-14.67\n182.25\n-13.14\n-229.93\n19.62\n170.97\n-17.95\nNA\n\n\n(Operating Activities) Change in Inventory_6m\n-22.49\n-12.41\n4.84\n-15.56\n-45.18\n-43.04\n23.87\n39.71\n-4.49\n23.38\n53.15\n21.94\n-17.93\n-19.04\n6.35\n3.42\n-17.07\n0.74\n20.62\n-0.36\n-19.77\n-8.28\n10.45\n3.73\n-26.14\n-22.79\n12.67\n5.78\n-7.60\n3.97\n21.60\n10.93\n-27.93\n-31.34\n1.93\n13.06\n-9.30\n13.68\n46.57\nNA\nNA\n-16.92\n-9.90\n7.06\n-3.02\n-21.18\n-3.11\n26.23\n13.78\n-11.61\n-9.01\n10.68\n12.03\n-15.30\n-4.16\n19.53\n-6.25\nNA\n\n\n(Operating Activities) Change in Prepaid expenses and other assets_6m\n10.83\n-4.91\n-6.14\n4.92\n1.76\n-8.29\n-6.53\n3.54\n5.04\n-21.65\n-11.02\n14.33\n-3.29\n-17.86\n-7.27\n-2.14\n-0.78\n-5.89\n-8.86\n12.08\n0.82\n-8.84\n5.84\n19.84\n18.65\n-9.51\n-15.49\n12.34\n-18.00\n-34.02\n-5.29\n-4.00\n2.09\n-3.42\n1.26\n10.93\n0.48\n-9.53\n-2.89\nNA\nNA\n8.94\n0.10\n-9.27\n6.26\n3.40\n-14.07\n-7.31\n2.27\n2.72\n-15.11\n-8.16\n12.18\n11.00\n-4.18\n-8.13\n0.96\nNA\n\n\n(Operating Activities) Change in Accounts Payable_6m\n-81.17\n-20.25\n85.33\n31.76\n-67.60\n-84.62\n52.07\n61.15\n-53.51\n-13.41\n60.98\n26.87\n-57.00\n-5.53\n71.95\n-9.24\n-112.94\n-1.91\n107.80\n6.78\n-112.93\n-8.98\n103.94\n18.50\n-57.83\n-15.70\n66.78\n15.32\n-70.53\n-21.77\n70.59\n32.33\n-68.27\n-24.15\n70.35\n3.11\n-91.84\n-4.89\n94.28\nNA\nNA\n-68.83\n-30.76\n59.76\n18.24\n-75.51\n-27.41\n84.99\n39.58\n-74.41\n-35.90\n63.32\n19.20\n-97.76\n-21.54\n74.05\n3.19\nNA\n\n\n(Operating Activities) Change in Accounts Taxes Payable_6m\n-17.12\n-1.75\n11.24\n-2.31\n-4.97\n8.54\n12.73\n1.33\n0.57\n0.30\n-0.27\n-0.51\n-1.45\n-0.56\n0.75\n-2.07\n0.35\n2.58\n0.00\n0.01\n0.46\n0.46\n-0.33\n-0.26\n0.14\n0.06\n-0.53\nNA\nNA\n-22.01\n1.17\n0.98\n-3.06\n-4.24\n0.51\n1.22\n-1.68\n0.39\n4.16\nNA\nNA\n2.77\n0.67\n-1.63\n5.09\n2.96\n4.94\n7.36\n5.26\n-14.41\n-7.00\n14.26\n2.73\n-9.19\n-6.14\n4.32\n1.48\nNA\n\n\n(Operating Activities) Change in Reserve for Sales Return and allowances_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Operating Activities) Deferred Income Tax_6m\nNA\nNA\nNA\nNA\nNA\n-57.86\nNA\nNA\nNA\n-0.07\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-0.98\nNA\nNA\nNA\n0.21\nNA\nNA\nNA\n-1.25\nNA\nNA\nNA\n-0.26\n0.07\n0.01\n-0.34\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-1.25\nNA\nNA\nNA\nNA\n82.75\n0.24\n-0.35\n-7.98\n-0.32\n7.42\n-0.31\n15.17\n-4.04\n-22.58\n-25.23\nNA\n\n\n(Operating Activities) Stock-based Compensation_6m\n4.64\n4.05\n3.85\n3.95\n3.74\n2.80\n2.31\n2.03\n1.58\n1.17\n0.84\n0.76\n1.18\n1.30\n1.21\n0.96\n1.25\n1.86\n1.26\n1.02\n1.31\n1.45\n1.07\n0.98\n1.53\n1.65\n1.50\n1.46\n1.12\n0.54\n0.63\n1.08\n0.73\n0.62\n0.95\n0.94\n0.98\n0.84\n0.72\nNA\nNA\n0.80\n0.69\n0.35\n0.39\n0.14\n0.31\n0.85\n0.81\n0.39\n0.48\n0.70\n1.12\n1.63\n2.31\n2.57\n2.13\nNA\n\n\n(Operating Activities) Cash Flow from Operating Activities_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n6.21\n-1.84\n-16.13\n13.24\n47.31\n-1.99\n-54.04\n18.71\n90.31\n15.55\n-29.92\n50.25\n64.95\n-46.39\n-94.13\nNA\nNA\n-16.66\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Property, Plant and Equipment_6m\n5.42\n3.99\n2.23\n4.92\n5.79\n5.11\n6.27\n5.28\n3.67\n4.50\n4.90\n3.72\n3.57\n3.94\n4.59\n4.33\n3.37\n4.21\n5.17\n5.21\n4.68\n5.26\n6.98\n6.51\n7.03\n7.31\n6.09\n7.61\n7.90\n8.66\n7.42\n6.11\n7.31\n6.66\n11.27\n11.18\n4.89\n3.63\n7.52\nNA\nNA\n3.36\n4.22\n5.99\n5.91\n3.23\n5.48\n8.59\n7.58\n4.05\n3.82\n8.40\n8.63\n5.21\n5.03\n6.33\n7.37\nNA\n\n\n(Investing Activities) Proceeds from Asset Sales_6m\n0.04\n0.04\n-0.02\n0.00\n0.02\n0.00\n0.05\n0.05\n0.00\n0.00\n0.01\n0.07\n-0.11\n-0.18\n0.11\n0.12\n-0.01\n0.00\n0.01\n0.06\n0.05\n0.07\n0.11\n0.03\n0.05\n0.05\n0.02\n0.02\n-0.01\nNA\nNA\nNA\n-0.07\n-0.07\n0.01\nNA\nNA\n0.00\n-0.03\nNA\nNA\n-0.85\n-0.86\n-1.10\nNA\nNA\n-0.04\n0.00\n-0.02\n-0.47\n-0.45\n-0.04\n-0.01\n-0.08\n-0.11\n0.02\n-0.81\nNA\n\n\n(Investing Activities) Purchase of Businesses_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Marketable Securities and Investment_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n0.00\nNA\nNA\n0.00\n0.00\nNA\nNA\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\nNA\n\n\n(Investing Activities) Proceeds from sale or maturity of Marketable Securities and Investment_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.07\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from maturities of Marketable Securities and Investment_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Cash Flow from Investing Activities_6m\n-6.86\n-4.01\n-2.20\n-4.89\n-5.77\n-5.11\n-6.27\n-5.28\n-3.67\n-4.50\n-4.89\n-3.69\n-3.52\n-3.92\n-4.53\n-4.26\n-3.37\n-4.20\n-5.16\n-5.21\n-4.66\n-5.13\n-6.87\n-6.51\n-6.91\n-7.19\n-6.64\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-3.21\n-5.54\n-4.47\n-5.22\n-13.91\n-61.54\n-56.53\n-11.20\n-25.88\n-22.45\n-8.16\n-13.85\n-12.28\n-3.47\n-4.55\n-12.48\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Stock_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n9.66\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment for Repurchase of Stock_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n1.56\n3.66\n11.94\n16.04\n8.53\nNA\nNA\nNA\n8.00\n32.00\n48\nNA\nNA\nNA\nNA\nNA\nNA\n26.67\nNA\nNA\nNA\n19.31\n19.31\n5.05\n10.69\n7.16\nNA\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Debt_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment of Debt_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash for Dividends_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n1.54\n3.09\n3.71\n4.35\n4.79\n5.19\n5.18\n3.45\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash Flow from Financing Activities_6m\n-20.58\n-1.86\n-31.78\n-70.43\n-40.69\n-19.52\n-29.38\n-11.51\n-1.14\n-0.34\n-32.38\n-32.45\n-15.23\n-15.07\n4.30\n4.13\n-5.17\n2.17\n6.98\n-7.94\n-0.06\n-5.49\n5.37\n8.38\n-4.30\n9.87\n-11.41\n-39.47\n-22.03\n0.47\n-4.35\n-15.41\n-43.83\n-13.20\n17.84\n-0.18\n-23.91\n-23.91\n76.15\nNA\nNA\n16.75\n69.57\n-26.70\n-110.69\n0.72\n-14.19\n-31.85\n-5.19\n-4.77\n-24.21\n-21.91\n-4.85\n-10.76\n-10.39\n-14.80\n-5.93\nNA\n\n\nEffect of Exchange Rate on Cash & Cash Equivalent_6m\n0.62\n0.39\n0.34\n1.46\n1.44\n-1.72\n-4.98\n-2.81\n-1.00\n-0.82\n-0.10\n0.32\n2.34\n3.53\n1.21\n-1.55\n-0.16\n0.57\n-0.47\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nChange in Cash, Cash Equivalents_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-12.93\nNA\nNA\nNA\n28.26\n5.54\n-73.44\n-15.83\n37.41\n-8.04\n-23.89\n38.74\n16.09\n-91.58\n-24.74\nNA\nNA\n61.90\n47.42\n-113.84\n-119.60\n24.61\n-32.32\n-113.80\n-35.61\n22.31\n10.41\n-42.22\n-31.50\n55.87\n29.59\n-33.20\n18.29\nNA",
    "crumbs": [
      "**Financial Analysis**",
      "Data Analysis"
    ]
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    "title": "Data Analysis",
    "section": "",
    "text": "Finally, we can transpose the dataframes of the financial statements to improve the readability.\nBalance Sheet\n\n\nShow the code\nlibrary(kableExtra)\n\n# Transpose the Balanche Sheet statement in standardized format\ndf_std_BS_t &lt;- transpose_df_standardized(df_std_BS, \"standardized_BS\")\n\n# Format numeric columns to 2 decimal places\ndf_std_BS_t &lt;- df_std_BS_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Balance Sheet in standardized format\ndf_std_BS_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item ($ in Million)\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2012-01-03\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n2008-12-31\n\n\n\n\nCash & Cash Equivalent\n35.29\n72.35\n96.25\n32.23\n38.30\n85.49\n76.60\n62.28\n39.23\n45.33\n26.70\n38.34\n84.06\n92.69\n79.82\n52.69\n44.03\n66.29\n75.89\n37.05\n47.41\n58.20\n57.14\n62.99\n46.78\n64.98\n48.81\n67.60\n68.03\n86.06\n48.16\n96.63\n118.91\n102.53\n81.21\n110.27\n105.10\n71.53\n88.62\n162.71\n113.36\n117.07\n51.52\n69.72\n165.36\n189.32\n140.76\n221.65\n254.56\n257.26\n257.26\n232.24\n246.85\n274.47\n278.35\n218.59\n248.75\n254.84\n169.52\n\n\nMarketable Securities Current\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.22\n0.21\nNA\n0.21\n0.21\n0.21\nNA\n0.21\nNA\nNA\nNA\nNA\n\n\nTotal Accounts Receivable\n79.88\n123.80\n206.75\n132.48\n85.17\n102.77\n204.86\n164.02\n103.73\n147.39\n209.19\n107.90\n79.66\n102.25\n166.79\n69.00\n64.76\n117.94\n200.79\n85.12\n67.79\n122.28\n205.41\n100.28\n93.93\n142.46\n224.10\n110.48\n98.49\n173.60\n272.26\n132.89\n85.47\n163.39\n292.86\n117.15\n104.32\n234.52\n304.34\n109.34\n65.37\n101.22\n257.96\n94.92\n64.98\n105.46\n242.64\n121.60\n58.40\nNA\n103.64\n239.68\n109.33\nNA\n122.48\nNA\nNA\nNA\nNA\n\n\nTotal Inventory\n46.34\n52.65\n68.83\n65.06\n63.99\n80.62\n109.17\n123.67\n85.31\n83.95\n89.80\n60.58\n36.65\n38.64\n54.58\n57.68\n48.23\n54.26\n65.30\n53.52\n44.69\n53.88\n64.45\n62.16\n54.00\n58.43\n80.14\n81.22\n67.47\n75.44\n75.06\n71.47\n53.47\n60.54\n81.40\n91.89\n79.47\n78.83\n88.78\n65.15\n42.20\n46.78\n59.12\n56.67\n52.05\n59.69\n73.23\n60.80\n45.00\nNA\n47.02\n55.84\n55.26\nNA\n43.23\nNA\nNA\nNA\nNA\n\n\nPrepaid Expenses\n3.84\n1.72\n1.93\n4.43\n4.48\n0.99\n5.01\n7.33\n6.78\n4.15\n4.18\n5.33\n5.05\n2.49\nNA\nNA\nNA\n3.61\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOther Current Assets\n1.46\n0.24\n0.19\n0.44\n0.12\n0.12\n0.12\n0.12\n0.12\n0.19\n0.25\n0.00\n0.12\n0.00\n22.12\n28.45\n18.80\n0.00\n18.50\n28.52\n28.03\n15.78\n26.49\n24.68\n20.81\n16.80\n18.26\n30.12\n33.58\n18.28\n51.20\n51.54\n56.92\n55.91\n58.05\n63.44\n57.53\n52.51\n57.65\n62.64\n61.20\n55.63\n54.72\n58.64\n62.98\n51.37\n84.73\n91.80\n93.13\n0.00\n89.36\n67.50\n76.86\n0.00\n67.90\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Current Assets\n180.79\n255.37\n378.75\n241.20\n200.31\n275.21\n401.75\n364.49\n245.67\n287.56\n338.06\n239.31\n223.85\n250.83\n323.32\n207.82\n175.82\n260.38\n360.47\n204.21\n187.91\n250.14\n353.49\n250.11\n215.52\n282.67\n371.32\n289.42\n267.57\n353.38\n446.68\n352.52\n314.78\n382.37\n513.52\n382.96\n346.64\n437.59\n539.60\n400.06\n282.34\n320.93\n423.54\n280.16\n345.60\n406.06\n541.56\n496.06\n451.30\n0.00\n497.48\n595.47\n488.50\n0.00\n512.16\n0.00\n0.00\n0.00\n0.00\n\n\nMarketable Securities Non Current\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nProperty Plant and Equipment\n122.15\n120.40\n119.14\n117.47\n114.10\n113.71\n113.14\n110.03\n105.43\n103.10\n102.10\n99.99\n96.26\n95.37\n95.81\n94.34\n103.49\n103.33\n109.77\n108.25\n104.42\n108.32\n115.82\n113.91\n116.92\n115.38\n111.70\n109.89\n104.67\n103.13\n99.90\n95.48\n89.01\n86.31\n95.43\n19.32\n13.11\n87.36\n10.55\n14.28\n10.84\n11.10\n12.09\n14.96\n16.24\n15.83\n15.13\n18.79\n17.55\nNA\n16.19\n17.58\n20.66\nNA\n16.95\nNA\nNA\nNA\nNA\n\n\nIntangible Assets (excl. goodwill)\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n42.75\n45.31\n53.53\n54.96\n57.48\n59.72\n61.93\n65.58\n63.56\n63.82\n66.24\n67.33\n69.50\n70.98\n70.29\n23.77\n21.29\nNA\n26.15\n16.36\n20.23\nNA\n23.44\nNA\nNA\nNA\nNA\n\n\nGoodwill\n35.00\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.08\n35.20\n35.27\n35.59\n35.38\n35.34\n43.48\n43.27\n43.21\n43.46\n43.63\n44.02\n44.20\n44.34\n44.57\n44.21\n44.49\n44.78\n45.09\n44.94\n44.88\n44.74\n48.50\n48.49\n48.84\n50.77\n24.73\n24.73\nNA\n24.02\n6.99\n6.99\nNA\n6.99\nNA\nNA\nNA\nNA\n\n\nOther Non Current Assets\n2.06\n2.16\n2.22\n2.33\n2.39\n2.47\n2.52\n2.73\n2.92\n2.99\n3.08\n3.57\n2.09\n3.22\n6.92\n10.06\n17.69\n18.93\n18.98\n17.26\n17.27\n19.10\n18.94\n18.97\n18.50\n6.58\n2.11\n2.49\n2.31\n2.16\n2.42\n2.66\n2.83\n3.12\n9.78\n9.49\n9.85\n10.39\n10.97\n11.74\n7.48\n6.18\n6.34\n3.07\n4.13\n4.58\n4.94\n3.90\n3.47\n0.00\n3.67\n8.24\n15.51\n0.00\n12.64\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Non Current Assets\n143.54\n143.58\n135.53\n127.74\n129.08\n130.13\n75.37\n79.15\n70.10\n69.49\n71.05\n75.82\n74.56\n78.54\n84.27\n92.60\n101.09\n104.84\n4.75\n124.53\n124.06\n92.70\n94.10\n98.77\n98.38\n87.68\n81.94\n108.96\n108.78\n110.92\n113.44\n117.37\n115.80\n117.25\n126.03\n127.74\n123.69\n124.19\n126.15\n134.06\n128.43\n128.91\n133.56\n141.92\n148.26\n148.77\n197.02\n119.86\n119.84\n0.00\n117.75\n112.14\n126.39\n0.00\n121.24\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Assets\n324.33\n398.95\n514.28\n368.94\n329.39\n405.34\n477.11\n443.64\n315.77\n357.05\n409.11\n315.13\n298.40\n329.37\n407.59\n300.42\n276.91\n365.22\n365.22\n328.74\n311.98\n342.84\n447.59\n348.88\n313.89\n370.35\n453.26\n398.38\n376.34\n464.30\n560.12\n469.89\n430.57\n499.62\n639.56\n510.70\n470.34\n561.78\n665.76\n534.12\n410.78\n449.84\n557.09\n422.09\n493.86\n554.82\n738.59\n615.92\n571.14\nNA\n615.23\n707.61\n614.89\nNA\n633.41\nNA\nNA\nNA\nNA\n\n\nAccounts Payable\n31.68\n42.18\n94.41\n57.77\n27.71\n33.69\n77.13\n86.66\n36.44\n50.24\n105.27\n68.81\n31.31\n30.35\n95.53\n53.10\n22.78\n61.20\n136.18\n64.39\n27.91\n57.57\n142.61\n68.12\n39.07\n49.92\n98.39\n67.00\n30.14\n51.74\n102.58\n73.72\n28.13\n34.99\n94.63\n59.22\n24.24\n56.11\n115.62\n60.55\n21.34\n25.27\n89.78\n56.03\n30.40\n37.79\n105.91\n64.34\n20.06\nNA\n26.43\n85.35\n51.54\nNA\n35.89\nNA\nNA\nNA\nNA\n\n\nTax Payable\n0.00\n3.79\n17.42\n5.81\n6.24\n8.16\n14.08\n2.33\n1.21\n1.00\n0.64\n0.70\n0.17\n0.48\n1.62\n0.50\n0.35\n2.49\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nCurrent Debts\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n1.77\n1.91\n1.91\n6.90\n1.89\nNA\n27.21\nNA\nNA\nNA\n21.20\n21.20\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n38.91\n38.63\nNA\n38.10\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOperating Lease Liability Current\n8.24\n7.38\n6.42\n9.23\n10.01\n10.75\n10.52\n10.24\n11.01\n10.48\n10.41\n10.48\n10.11\n9.93\n9.66\n9.63\n9.59\n9.45\n9.37\n9.18\n8.82\n0.00\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOther Current Liabilities\n73.75\n95.89\n137.10\n102.91\n78.57\n125.22\n163.71\n148.54\n87.96\n111.35\n107.79\n113.45\n74.45\n97.51\n110.65\n57.50\n53.80\n77.88\n98.37\n58.13\n75.99\n59.32\n98.17\n97.02\n73.61\n64.64\n69.73\n31.45\n39.19\n65.07\n96.53\n62.33\n59.70\n92.41\n147.32\n91.72\n88.20\n135.24\n134.67\n102.43\n140.59\n121.22\n138.51\n107.10\n156.86\n181.68\n178.12\n78.19\n76.53\n0.00\n96.40\n108.75\n64.12\n0.00\n89.02\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Current Liabilities\n113.67\n149.23\n255.34\n175.71\n122.53\n177.82\n265.44\n247.78\n136.62\n173.07\n224.10\n193.44\n116.04\n138.27\n217.46\n122.51\n88.43\n152.92\n250.81\n133.59\n112.72\n144.10\n240.79\n165.14\n112.68\n135.76\n189.32\n98.45\n69.33\n116.81\n199.10\n136.05\n87.83\n127.40\n241.95\n150.94\n112.44\n191.35\n289.20\n201.61\n161.93\n184.60\n228.29\n163.13\n187.26\n219.48\n284.03\n142.53\n96.59\nNA\n122.83\n194.11\n115.66\nNA\n124.91\nNA\nNA\nNA\nNA\n\n\nNon Current Debts\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n174.16\n169.40\n174.96\n170.81\n160.66\nNA\n139.79\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n215.00\n215.00\n215.00\n215.00\n215.00\n215.00\nNA\n100.00\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOperating Lease Liability Non Current\n15.96\n16.67\n19.28\n6.22\n8.10\n9.86\n12.55\n15.41\n7.40\n8.04\n9.95\n12.28\n14.47\n16.88\n18.39\n20.74\n23.12\n25.63\n27.86\n29.83\n29.63\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOther Non Current Liabilities\n6.48\n2.70\n35.33\n30.76\n51.68\n66.47\n88.66\n98.62\n115.13\n114.96\n17.08\n16.98\n15.44\n8.06\n5.87\n3.33\n3.32\n5.41\n5.04\n0.14\n0.13\n4.41\n4.36\n4.35\n4.43\n4.54\n4.62\n4.74\n4.91\n5.00\n5.21\n5.17\n5.30\n5.16\n4.23\n3.90\n0.91\n1.87\n7.25\n7.38\n7.43\n7.02\n13.18\n18.37\n18.45\n18.34\n27.33\n1.83\n1.86\n0.00\n1.63\n1.57\n1.58\n0.00\n1.62\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Non Current Liabilities\n22.44\n53.60\n54.61\n36.98\n59.78\n76.33\n101.22\n114.02\n122.53\n123.00\n121.26\n125.33\n185.94\n176.42\n176.82\n199.96\n197.53\n207.79\n206.61\n193.52\n175.06\n147.09\n151.20\n143.45\n141.25\n140.08\n140.08\n160.95\n173.74\n212.29\n217.73\n217.32\n217.50\n218.81\n227.41\n227.09\n222.29\n225.35\n231.92\n232.05\n116.35\n116.56\n164.45\n129.45\n128.84\n128.13\n125.49\n99.93\n99.28\n0.00\n98.81\n97.79\n96.90\n0.00\n96.09\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Liabilities\n136.11\n202.84\n309.96\n212.70\n182.31\n254.15\n366.66\n361.80\n259.14\n296.07\n345.35\n318.77\n301.99\n314.69\n394.28\n322.47\n285.96\n360.72\n457.42\n327.11\n287.78\n291.19\n391.99\n308.59\n253.93\n275.84\n329.40\n259.40\n243.07\n329.10\n416.84\n353.37\n305.33\n346.21\n469.36\n378.03\n334.73\n416.70\n521.12\n433.66\n278.28\n301.16\n392.74\n292.58\n316.10\n347.60\n409.52\n242.46\n195.87\nNA\n221.64\n291.90\n212.56\nNA\n221.00\nNA\nNA\nNA\nNA\n\n\nPreferred Stock\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nRetained Earnings or Accumulated Deficit\n-88.12\n-73.61\n-62.74\n-110.88\n-117.33\n-112.02\n-149.99\n-180.68\n-207.24\n-203.43\n-200.26\n-236.59\n-221.51\n-197.42\n-186.08\n-218.46\n-195.19\n-183.15\n-162.86\n-179.30\n-156.76\n-127.60\n-124.35\n-140.04\n-121.48\n-85.23\n-54.82\n-37.21\n-20.46\n-2.15\n5.44\n-25.18\n-20.81\n-3.39\n5.94\n-39.91\n-34.23\n-26.64\n-29.44\n-73.51\n-64.46\n-48.15\n-32.09\n-68.68\n-20.27\n8.84\n130.46\n102.20\n104.59\nNA\n123.17\n145.78\n113.55\nNA\n119.88\nNA\nNA\nNA\nNA\n\n\nAccumulated other comprehensive income (loss)\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nMinority interest\n0.50\n0.71\n0.71\n0.72\n1.00\n1.00\n0.86\n0.88\n1.23\n1.33\n1.31\n1.27\n1.25\n1.21\n1.18\n1.13\n1.12\n1.08\n0.97\n1.00\n0.94\n0.91\n1.01\n0.99\n1.02\n0.97\n1.04\n1.00\n0.94\n0.91\n0.58\n0.66\n0.44\n0.41\n0.46\n0.44\n0.49\n0.49\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nTotal Stockholders Equity\n188.23\n190.12\n198.72\n151.01\n142.22\n146.70\n106.33\n78.07\n53.21\n57.90\n61.02\n-6.04\n-5.65\n12.94\n11.90\n-23.15\n-9.84\n4.02\n22.04\n1.63\n24.19\n51.65\n55.60\n40.30\n59.96\n94.51\n123.86\n138.98\n133.27\n135.20\n143.28\n116.52\n125.24\n153.41\n170.20\n132.68\n135.61\n145.08\n144.63\n100.45\n132.50\n148.68\n164.35\n129.51\n177.75\n207.22\n329.06\n373.46\n375.28\n0.00\n393.59\n415.72\n402.33\n0.00\n412.41\n0.00\n0.00\n0.00\n0.00\n\n\nTotal Liabilities & Stockholders Equity\n324.33\n398.95\n514.28\n368.94\n329.39\n405.34\n477.11\n443.64\n315.77\n357.05\n409.11\n315.13\n298.40\n329.37\n407.59\n300.42\n276.91\n365.22\n479.64\n328.74\n311.98\n342.84\n447.59\n348.88\n313.89\n370.35\n453.26\n398.38\n376.34\n464.30\n560.12\n469.89\n430.57\n499.62\n639.56\n510.70\n470.34\n561.78\n665.76\n534.12\n410.78\n449.84\n557.09\n422.09\n493.86\n554.82\n738.59\n615.92\n571.14\nNA\n615.23\n707.61\n614.89\nNA\n633.41\nNA\nNA\nNA\nNA\n\n\n\n\n\n\n\nIncome Statement\n\n\nShow the code\n# Transpose the Income Statement  in standardized format\ndf_std_IS_t &lt;- transpose_df_standardized(df_std_IS, \"standardized_IS\")\n\n# Format numeric columns to 2 decimal places\ndf_std_IS_t &lt;- df_std_IS_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_IS_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item ($ in Million)\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-09-03\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\nRevenue\n90.08\n127.40\n309.74\n166.93\n107.48\n131.89\n323.00\n220.42\n120.88\n187.96\n236.96\n112.35\n83.84\n128.97\n242.29\n78.76\n66.56\n149.66\n280.13\n95.18\n70.83\n141.95\n236.70\n105.78\n93.00\n136.63\n262.41\n119.56\n94.50\n167.03\n207.86\n161.81\n140.98\n95.81\n186.44\n337.03\n131.11\n114.20\n202.51\n349.36\n124.17\n82.51\n80.44\n310.89\n106.23\n78.07\n80.19\n314.49\n145.36\n73.40\n95.95\n332.42\n131.93\n72.32\n197.99\n348.68\n100.30\n200.93\n\n\nCost of Revenue\n69.02\n93.66\n202.76\n115.74\n76.05\n103.32\n231.09\n159.53\n90.96\n137.92\n162.03\n80.46\n57.75\n86.24\n167.67\n61.99\n50.21\n106.11\n199.27\n77.44\n56.49\n91.84\n172.37\n77.84\n70.04\n114.36\n200.63\n85.85\n64.48\n114.92\n207.86\n111.68\n96.18\n64.63\n113.83\n232.70\n91.82\n78.82\n174.32\n254.62\n86.35\n58.95\n98.96\n219.50\n103.99\n54.69\n102.74\n217.78\n98.47\n49.84\n122.12\n226.75\n86.84\n48.05\n132.46\n237.72\n66.07\n150.19\n\n\nGross Profit\n21.05\n33.73\n106.98\n51.20\n31.44\n28.57\n91.91\n60.89\n29.92\n50.04\n74.92\n31.90\n26.09\n37.44\n74.62\n16.77\n16.35\n39.84\n80.86\n17.75\n14.34\n38.93\n64.33\n27.94\n22.96\n38.92\n61.78\n33.72\n30.02\n52.10\nNA\n50.13\n44.80\n31.18\n57.14\n104.33\n39.29\n35.38\n58.95\n94.74\n37.82\n23.56\n38.94\n91.39\n2.24\n23.38\n49.48\n96.71\n46.89\n23.57\n48.50\n105.67\n45.09\n24.27\n65.53\n110.96\n34.23\n50.73\n\n\nResearch and development\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nSales general and administrative costs\n42.38\n49.07\n44.59\n34.75\n35.84\n44.26\n38.17\n36.93\n30.65\n47.12\n38.18\n30.08\n28.82\n40.90\n36.96\n24.66\n32.34\n-14.14\n44.59\n33.87\n35.27\n42.59\n44.18\n39.75\n58.62\n55.66\n55.99\n47.83\n45.74\n54.50\n60.52\nNA\n45.90\n45.00\n56.47\n59.70\n42.30\n39.58\n72.44\n50.92\n42.64\n38.48\n54.82\n51.74\n46.53\n47.22\n61.98\n59.42\n46.79\n42.98\n54.95\n55.60\n43.09\n39.06\n54.56\n59.38\n40.41\n56.76\n\n\nOther Non Operating Income (Loss) Net\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n14.62\nNA\nNA\n-6.96\nNA\n0.00\n0.00\n-21.32\nNA\n0.00\n0.00\nNA\n0.00\n0.00\n0.00\n-9.19\n0.00\n0.00\n0.00\nNA\n0.00\n0.00\n0.00\nNA\n0.00\n0.00\nNA\n\n\nOperating Income\n-21.32\n-15.34\n62.40\n16.45\n-4.40\n-15.70\n53.74\n23.66\n-0.73\n2.93\n36.74\n1.82\n-2.72\n3.23\n37.51\n-9.75\n-15.99\n-4.45\n35.66\n-18.65\n-24.04\n-8.04\n20.04\n-12.14\n-35.66\n-16.04\n-7.75\n-14.11\n-15.72\n-2.39\nNA\n35.51\n-1.10\n-13.82\n7.63\n44.63\n-3.01\n-4.20\n7.83\n43.81\n-4.82\n-14.92\n-11.13\n39.65\n-44.29\n-23.84\n-3.31\n37.30\n0.11\n-19.41\n0.32\n50.07\n2.00\n-14.79\n10.97\n51.58\n-6.18\n-113.11\n\n\nInterest Income\n0.38\n0.76\n0.38\n0.09\n0.12\n0.06\n0.06\n0.01\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.01\n0.02\n0.02\n0.02\n0.03\n0.02\n0.02\n0.01\n0.01\n0.01\n0.01\n0.01\n0.00\n0.00\n0.01\nNA\n0.02\n0.02\n0.01\n0.02\n0.02\n0.02\n0.02\n0.03\n0.03\n0.03\n0.03\n0.09\n0.13\n0.07\n0.06\n0.10\n0.31\n0.20\n0.08\n0.10\n0.12\n0.10\n0.08\n0.10\n0.08\n0.08\n\n\nInterest Expense\n0.14\n0.71\n1.44\n1.30\n3.00\n2.29\n4.35\n2.34\n2.20\n2.20\n2.66\n4.37\n4.88\n4.91\n5.57\n5.54\n5.55\n5.38\n4.62\n2.92\n3.02\n3.01\n3.10\n2.20\n1.94\n2.33\n2.03\n2.54\n2.93\n3.51\n3.02\nNA\n3.22\n3.23\n3.21\n3.11\n3.11\n2.97\n3.30\n3.97\n2.98\n2.21\n2.74\n2.30\n2.06\n2.85\n3.14\n2.02\n2.04\n2.04\n2.07\n2.06\n2.02\n2.04\n0.98\n1.55\n2.10\n1.98\n\n\nOther income (expense) Net\n-0.89\n-0.29\n0.08\n7.40\n-0.82\n-1.83\n7.09\n-6.22\n0.55\n3.94\n-2.59\n12.61\n16.36\n1.67\n-0.22\n7.70\n-9.82\n3.52\n13.60\n0.31\n2.29\n-1.21\n-0.72\n2.15\n0.92\n1.97\n6.87\n-0.28\n-0.03\n-0.06\n-34.64\n35.51\n-0.90\n-0.11\n-2.24\n41.51\n-6.13\n-7.19\n4.51\n39.81\n-7.83\n-17.16\n-13.90\n37.26\n-46.48\n-26.77\n-6.51\n35.18\n-2.24\n-21.64\n-1.83\n47.90\n-0.15\n-16.93\n9.91\n49.93\n-8.36\n-115.17\n\n\nIncome Before Income Tax\n-20.95\n-16.52\n60.50\n7.66\n-6.70\n-16.22\n42.25\n27.54\n-3.49\n-3.21\n36.67\n-15.16\n-23.96\n-3.35\n32.16\n-23.00\n-11.72\n-13.37\n17.43\n-21.90\n-29.37\n-9.87\n17.65\n-16.50\n-38.53\n-20.36\n-16.65\n-16.37\n-18.63\n-5.84\n31.61\nNA\n-3.44\n-16.95\n6.65\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nProvision for (benefit) Income Tax\n-6.73\n-5.64\n12.38\n1.48\n-1.38\n-54.33\n11.57\n1.33\n0.42\n-0.06\n0.30\n-0.10\n0.09\n0.45\n-0.27\n0.27\n0.28\n0.55\n1.02\n0.59\n-0.24\n1.24\n1.95\n2.09\n-2.34\n0.72\n0.92\n-0.33\n0.30\n1.91\n1.08\nNA\n0.70\n0.43\n0.31\n1.38\n1.31\n0.43\n1.18\n1.74\n1.28\n-0.48\n2.18\n0.28\n-0.14\n0.30\n85.29\n5.98\n0.07\n-5.19\n-17.97\n13.26\n1.85\n-6.14\n1.15\n9.77\n-4.11\n-22.67\n\n\nNet Income (loss) (continous operations)\n-14.22\n-10.87\n48.12\n6.18\n-5.32\n38.11\n30.68\n26.21\n-3.91\n-3.15\n36.38\n-15.06\n-24.05\n-3.54\n32.43\n-23.27\n-12.00\n-13.84\n16.41\n-22.48\n-29.13\n-10.61\n15.70\n-18.59\n-36.19\n-30.49\n-17.57\n-16.69\n-18.28\n-7.75\n30.53\nNA\n-4.14\n-17.38\n-9.39\n45.86\n-5.73\n-7.58\n2.80\n44.07\n-12.68\nNA\n-13.48\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n\n\n\n\n\nCash Flow Statement\n\n\nShow the code\n# Transpose the Cash Flow Statement of JAKKS Pacific Inc. in standardized format\ndf_std_CF_t &lt;- transpose_df_standardized(df_std_CF, \"standardized_CF\")\n\n# Format numeric columns to 2 decimal places\ndf_std_CF_t &lt;- df_std_CF_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Cash Flow Statement in standardized format\ndf_std_CF_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item ($ in Million)\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-06-09\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\n(Operating Activities) Cash Flow Depreciation, Depletion, Ammortization\n1.60\n2.44\n2.73\n2.49\n1.29\n2.31\n4.63\n3.13\n2.41\n1.99\n4.90\n3.38\n2.40\n-0.38\n4.53\n5.16\n3.76\n-4.78\n14.00\n8.48\n6.47\n6.18\n13.13\n8.66\n6.19\n5.18\n16.60\n11.47\n8.76\n12.09\n16.41\n9.31\n8.07\n9.28\n14.76\n7.61\n6.08\n5.67\n17.26\n8.65\nNA\n6.35\n12.21\n18.63\n8.79\n6.39\n5.28\n25.21\n10.19\n5.47\n10.93\n10.80\n5.93\n3.88\n12.15\n12.02\n5.40\n8.99\n\n\n(Operating Activities) Change in Accounts Receivable\n-42.80\n-83.21\n75.07\n47.12\n-17.22\n-102.21\n40.99\n60.54\n-43.70\n-62.31\n101.90\n27.53\n-23.37\n-64.71\n99.16\n4.89\n-53.41\n-82.58\n116.52\n17.17\n-54.58\n-85.08\n104.19\n5.03\n-34.74\n-80.86\n121.75\n14.88\n-75.11\n-98.66\n139.36\n47.42\n-77.92\n-129.47\n175.71\n12.83\n-130.20\n-69.82\n195.00\n43.98\nNA\n-35.86\n-156.74\n163.05\n29.93\n-40.47\n-137.18\n117.97\n63.19\n-45.23\n-145.02\n130.35\n51.90\n-65.04\n-164.89\n184.51\n-13.54\n-4.41\n\n\n(Operating Activities) Change in Inventory\n-6.31\n-16.18\n3.77\n1.07\n-16.63\n-28.55\n-14.49\n38.36\n1.35\n-5.84\n29.22\n23.93\n-1.99\n-15.94\n-3.10\n9.45\n-6.03\n-11.04\n11.78\n8.84\n-9.20\n-10.57\n2.29\n8.16\n-4.43\n-21.71\n-1.08\n13.75\n-7.97\n0.37\n3.60\n18.00\n-7.07\n-20.86\n-10.48\n12.41\n0.65\n-9.95\n23.63\n22.94\nNA\n-4.58\n-12.34\n2.44\n4.62\n-7.64\n-13.54\n10.43\n15.80\n-2.02\n-9.59\n0.58\n10.10\n1.93\n-17.23\n13.07\n6.46\n-12.71\n\n\n(Operating Activities) Change in Prepaid expenses and other assets\n11.20\n-0.37\n-4.54\n-1.60\n6.52\n-4.76\n-3.53\n-3.00\n6.54\n-1.50\n-20.15\n9.13\n5.20\n-8.49\n-9.37\n2.10\n-4.24\n3.46\n-9.35\n0.49\n11.59\n-10.77\n1.93\n3.91\n15.93\n2.72\n-12.23\n-3.26\n15.60\n-33.60\n-0.42\n-4.87\n0.87\n1.22\n-4.64\n5.90\n5.03\n-4.55\n-4.98\n2.09\nNA\n4.92\n4.02\n-3.92\n-5.35\n11.61\n-8.21\n-5.86\n-1.45\n3.72\n-1.00\n-14.11\n5.95\n6.23\n4.77\n-8.95\n0.82\n0.14\n\n\n(Operating Activities) Change in Accounts Payable\n-14.13\n-67.04\n46.79\n38.54\n-6.78\n-60.82\n-23.80\n75.87\n-14.72\n-38.79\n25.38\n35.60\n-8.73\n-48.27\n42.74\n29.21\n-38.45\n-74.49\n72.58\n35.22\n-28.44\n-84.49\n75.51\n28.43\n-9.93\n-47.90\n32.20\n34.58\n-19.26\n-51.27\n29.50\n41.09\n-8.76\n-59.51\n35.36\n34.99\n-31.88\n-59.96\n55.07\n39.21\nNA\n-3.94\n-64.89\n34.13\n25.63\n-7.39\n-68.12\n40.71\n44.28\n-4.70\n-69.71\n33.81\n29.51\n-10.31\n-87.45\n65.91\n8.14\n-4.95\n\n\n(Operating Activities) Change in Accounts Taxes Payable\n-3.73\n-13.39\n11.64\n-0.40\n-1.91\n-3.06\n11.60\n1.13\n0.20\n0.37\n-0.07\n-0.20\n-0.31\n-1.14\n0.58\n0.17\n-2.24\n2.59\n-0.01\n0.01\n0.00\n0.46\n0.00\n-0.33\n0.07\n0.07\n-0.01\n-0.52\nNA\n-22.87\n0.86\n0.31\n0.67\n-3.73\n-0.51\n1.02\n0.20\n-1.88\n2.27\n1.89\nNA\n0.64\n2.13\n-1.46\n-0.17\n5.26\n-2.30\n7.24\n0.12\n5.14\n-19.55\n12.55\n1.71\n1.02\n-10.21\n4.07\n0.25\n1.23\n\n\n(Operating Activities) Change in Reserve for Sales Return and allowances\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Operating Activities) Deferred Income Tax\nNA\n-2.58\nNA\nNA\nNA\n-57.86\n0.00\nNA\nNA\n-0.07\n0.00\nNA\nNA\n0.03\nNA\nNA\nNA\n-0.98\n0.00\nNA\nNA\n0.21\n0.00\nNA\nNA\n-1.25\n0.00\nNA\nNA\n-0.23\n-0.03\n0.10\n-0.09\n-0.25\nNA\n0.00\nNA\n1.04\nNA\nNA\nNA\n-1.22\n-0.03\nNA\nNA\nNA\n82.40\n0.35\n-0.11\n-0.24\n-7.74\n7.42\n0.00\n-0.31\n15.48\n-19.52\n-3.06\n-22.17\n\n\n(Operating Activities) Stock-based Compensation\n2.58\n2.06\n1.99\n1.86\n2.09\n1.65\n1.15\n1.16\n0.87\n0.71\n0.46\n0.38\n0.38\n0.80\n0.50\n0.71\n0.25\n1.00\n0.86\n0.40\n0.62\n0.69\n0.76\n0.31\n0.67\n0.86\n0.79\n0.71\n0.75\n0.37\n0.17\n0.46\n0.62\n0.11\n0.51\n0.44\n0.50\n0.48\n0.36\n0.36\nNA\n0.28\n0.52\n0.17\n0.18\n0.21\n-0.07\n0.38\n0.47\n0.34\n0.05\n0.43\n0.27\n0.85\n0.78\n1.53\n1.04\n1.09\n\n\n(Operating Activities) Cash Flow from Operating Activities\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-11.39\n17.60\n-19.44\n3.31\n9.93\n37.38\n-39.37\n-14.67\n33.38\n56.93\n-41.38\n11.46\n38.79\n26.16\n-72.55\n-21.58\nNA\n-11.05\n-5.61\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Property, Plant and Equipment\n2.23\n3.19\n0.80\n1.43\n3.49\n2.30\n2.81\n3.46\n1.82\n1.85\n2.65\n2.25\n1.47\n2.10\n1.84\n2.75\n1.58\n1.79\n2.42\n2.75\n2.46\n2.22\n3.04\n3.94\n2.57\n4.46\n2.85\n3.24\n4.37\n3.53\n5.13\n2.29\n3.82\n3.49\n3.17\n8.10\n3.08\n1.81\n1.82\n5.70\nNA\n1.20\n2.16\n2.06\n3.93\n1.98\n1.25\n4.23\n4.36\n3.22\n0.83\n2.99\n5.41\n3.22\n1.99\n3.04\n3.29\n4.08\n\n\n(Investing Activities) Proceeds from Asset Sales\n0.00\n0.04\n0.00\n-0.02\n0.02\n0.00\n0.00\n0.05\n0.00\n0.00\n0.00\n0.01\n0.06\n-0.17\n-0.01\n0.12\n0.00\n-0.01\n0.01\n0.00\n0.06\n-0.01\n0.08\n0.03\n0.00\n0.05\n0.00\n0.02\n0.00\n-0.01\nNA\nNA\n0.00\n-0.07\n0.00\n0.01\nNA\n0.00\n0.00\n-0.03\nNA\n0.01\n-0.86\n0.00\n-1.10\nNA\n-0.04\n0.00\n0.00\n-0.02\n-0.45\n0.00\n-0.04\n0.03\n-0.11\n0.00\n0.02\n-0.83\n\n\n(Investing Activities) Purchase of Businesses\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Marketable Securities and Investment\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n0.00\n0.00\nNA\n0.00\n0.00\n0.00\nNA\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n\n\n(Investing Activities) Proceeds from sale or maturity of Marketable Securities and Investment\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n0.07\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from maturities of Marketable Securities and Investment\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Cash Flow from Investing Activities\n-3.63\n-3.23\n-0.78\n-1.42\n-3.47\n-2.30\n-2.81\n-3.46\n-1.82\n-1.85\n-2.65\n-2.24\n-1.45\n-2.07\n-1.85\n-2.68\n-1.58\n-1.79\n-2.41\n-2.75\n-2.46\n-2.20\n-2.93\n-3.94\n-2.57\n-4.34\n-2.85\n-3.79\nNA\n-3.77\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-5.58\nNA\nNA\nNA\n-0.86\n-2.35\n-3.19\n-1.28\n-3.94\n-9.97\n-51.57\n-4.96\n-6.24\n-19.64\n-2.81\n-5.35\n-8.50\n-3.78\n0.31\n-4.86\n-7.62\n\n\n(Financing Activities) Proceeds from Issuance of Stock\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\n0.00\n9.66\nNA\n0.00\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment for Repurchase of Stock\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\n1.56\n2.10\n9.84\n6.20\n2.33\nNA\nNA\n0.00\n8.00\n24.00\n24\nNA\nNA\nNA\nNA\nNA\n0.00\n26.67\nNA\nNA\n0.00\n19.31\n0.00\n5.05\n5.64\n1.52\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Debt\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment of Debt\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash for Dividends\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n0.00\n1.54\n1.55\n2.16\n2.19\n2.60\n2.59\n2.59\n0.86\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash Flow from Financing Activities\n-20.00\n-0.58\n-1.28\n-30.50\n-39.93\n-0.76\n-18.76\n-10.62\n-0.89\n-0.25\n-0.09\n-32.29\n-0.16\n-15.07\n0.00\n4.30\n-0.17\n-5.00\n7.17\n-0.19\n-7.75\n7.69\n-13.18\n18.55\n-10.17\n5.87\n4.00\n-15.41\n-24.06\n2.03\n-1.56\n-2.79\n-12.62\n-31.21\n18.01\n-0.17\n-0.01\n-23.90\n-0.01\n76.16\nNA\n16.82\n-0.07\n69.64\n-96.34\n-14.35\n15.07\n-29.26\n-2.59\n-2.60\n-2.17\n-22.04\n0.13\n-4.98\n-5.78\n-4.61\n-10.19\n4.26\n\n\nEffect of Exchange Rate on Cash & Cash Equivalent\n-0.56\n1.18\n-0.79\n1.13\n0.33\n1.11\n-2.83\n-2.15\n-0.66\n-0.34\n-0.48\n0.38\n-0.06\n2.40\n1.13\n0.08\n-1.63\n1.47\n-0.90\n0.43\nNA\n-0.62\nNA\nNA\nNA\n0.92\nNA\nNA\nNA\n-1.54\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nChange in Cash, Cash Equivalents\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-6.02\nNA\nNA\nNA\n-11.01\nNA\nNA\nNA\nNA\n-19.04\n6.11\nNA\nNA\n-18.50\n46.76\n-41.22\n-32.22\n16.39\n21.02\n-29.06\n5.17\n33.57\n-17.48\n-74.10\n49.36\nNA\n-3.72\n65.62\n-18.20\n-95.64\n-23.96\n48.57\n-80.89\n-32.91\n-2.70\n25.01\n-14.60\n-27.62\n-3.88\n59.75\n-30.16\n-3.04\n21.33",
    "crumbs": [
      "**Financial Analysis**",
      "Data Analysis"
    ]
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    "objectID": "03_data_analysis.html#trailing-month-tm-format",
    "href": "03_data_analysis.html#trailing-month-tm-format",
    "title": "Data Analysis",
    "section": "",
    "text": "Finally, we will calculate the multiple trailing month value of the Income Statement and Cash Flow. These are easily comparable with the filing on SEC website.\n\n\nIncome Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_IS_12TM &lt;- calculate_trailing_months(df_std_IS,12)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_IS_12TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_IS_12TM_t &lt;- transpose_df(df_std_IS_12TM, order_df)\n\n# Format numeric columns to 2 decimal places\ndf_std_IS_12TM_t &lt;- df_std_IS_12TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_IS_12TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-09-03\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\nRevenue_12m\n694.15\n711.55\n716.04\n729.30\n782.79\n796.19\n852.26\n766.22\n658.15\n621.11\n562.12\n567.45\n533.86\n516.58\n537.27\n575.11\n591.53\n595.80\n588.09\n544.66\n555.26\n577.43\n572.11\n597.82\n611.60\n613.10\n643.50\n588.95\n631.20\n677.68\n606.46\n585.04\n760.26\n750.39\n768.78\n784.85\n797.18\n790.24\n758.55\n636.48\n598.01\n580.07\n575.63\n575.38\n578.98\n618.11\n613.44\n629.20\n647.13\n633.70\n632.62\n734.66\n750.92\n719.29\n847.90\nNA\nNA\nNA\n\n\nCost of Revenue_12m\n481.18\n488.21\n497.87\n526.20\n569.99\n584.90\n619.50\n550.44\n471.37\n438.16\n386.48\n392.12\n373.65\n366.11\n385.98\n417.58\n433.03\n439.31\n425.04\n398.14\n398.54\n412.09\n434.61\n462.87\n470.88\n465.32\n465.88\n473.11\n498.94\n530.64\n480.35\n386.32\n507.34\n502.98\n517.17\n577.66\n599.58\n594.11\n574.24\n498.88\n463.76\n481.40\n477.14\n480.92\n479.20\n473.68\n468.83\n488.21\n497.18\n485.55\n483.76\n494.10\n505.07\n484.30\n586.44\nNA\nNA\nNA\n\n\nGross Profit_12m\n212.96\n223.35\n218.19\n203.12\n212.81\n211.29\n232.76\n215.77\n186.78\n182.95\n170.35\n170.05\n154.92\n145.18\n147.58\n153.82\n154.80\n152.79\n151.88\n135.35\n145.54\n154.16\n154.15\n151.60\n157.38\n164.44\n177.62\nNA\nNA\nNA\nNA\n183.25\n237.45\n231.94\n236.14\n237.95\n228.36\n226.89\n215.07\n195.06\n191.71\n156.13\n155.95\n166.49\n171.81\n216.46\n216.65\n215.67\n224.63\n222.83\n223.53\n240.56\n245.85\n234.99\n261.45\nNA\nNA\nNA\n\n\nResearch and development_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nSales general and administrative costs_12m\n170.79\n164.25\n159.44\n153.02\n155.20\n150.01\n152.87\n152.88\n146.03\n144.20\n137.98\n136.76\n131.34\n134.86\n79.82\n87.45\n96.66\n99.59\n156.32\n155.91\n161.79\n185.14\n198.21\n210.02\n218.10\n205.22\n204.06\n208.59\nNA\nNA\nNA\nNA\n207.07\n203.47\n198.05\n214.02\n205.24\n205.58\n204.48\n186.86\n187.68\n191.57\n200.31\n207.47\n215.15\n215.41\n211.17\n204.14\n200.32\n196.62\n192.70\n192.31\n196.09\n193.41\n211.11\nNA\nNA\nNA\n\n\nOther Non Operating Income (Loss) Net_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-9.19\n-9.19\n-9.19\n-9.19\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOperating Income_12m\n42.19\n59.11\n58.75\n50.09\n57.30\n60.97\n79.60\n62.60\n40.76\n38.77\n39.07\n39.84\n28.27\n15.00\n7.32\n5.47\n-3.43\n-11.48\n-15.07\n-30.69\n-24.18\n-35.80\n-43.80\n-71.59\n-73.56\n-53.62\n-39.97\nNA\nNA\nNA\nNA\n28.22\n37.34\n35.43\n45.05\n45.25\n44.43\n42.62\n31.90\n12.94\n8.78\n-30.69\n-39.61\n-31.79\n-34.14\n10.26\n14.69\n18.32\n31.09\n32.98\n37.60\n48.25\n49.76\n41.58\n-56.74\nNA\nNA\nNA\n\n\nInterest Income_12m\n1.61\n1.35\n0.65\n0.33\n0.25\n0.13\n0.07\n0.01\n0.00\n0.00\n0.00\n0.00\n0.00\n0.01\n0.03\n0.05\n0.07\n0.09\n0.09\n0.09\n0.08\n0.06\n0.05\n0.04\n0.04\n0.03\n0.02\n0.02\nNA\nNA\nNA\nNA\n0.07\n0.07\n0.07\n0.08\n0.09\n0.10\n0.11\n0.12\n0.18\n0.28\n0.32\n0.35\n0.36\n0.54\n0.67\n0.69\n0.69\n0.50\n0.40\n0.40\n0.40\n0.36\n0.34\nNA\nNA\nNA\n\n\nInterest Expense_12m\n3.59\n6.45\n8.03\n10.94\n11.98\n11.18\n11.09\n9.40\n11.43\n14.11\n16.82\n19.73\n20.90\n21.57\n22.04\n21.09\n18.47\n15.94\n13.57\n12.05\n11.33\n10.25\n9.57\n8.50\n8.84\n9.83\n11.01\n12.00\nNA\nNA\nNA\nNA\n12.77\n12.66\n12.40\n12.49\n13.35\n13.22\n12.46\n11.90\n10.23\n9.31\n9.95\n10.35\n10.07\n10.05\n9.24\n8.17\n8.21\n8.19\n8.19\n7.10\n6.59\n6.67\n6.61\nNA\nNA\nNA\n\n\nOther income (expense) Net_12m\n6.30\n6.37\n4.83\n11.84\n-1.78\n-0.41\n5.36\n-4.32\n14.51\n30.32\n28.05\n30.42\n25.51\n-0.67\n1.18\n15.00\n7.61\n19.72\n14.99\n0.67\n2.51\n1.14\n4.32\n11.91\n9.48\n8.53\n6.50\n-35.01\n0.78\n-0.09\n-0.14\n32.26\n38.26\n33.03\n25.95\n32.70\n31.00\n29.30\n19.33\n0.92\n-1.63\n-40.28\n-49.89\n-42.50\n-44.58\n-0.34\n4.79\n9.47\n22.19\n24.28\n28.99\n40.73\n42.76\n34.55\n-63.69\nNA\nNA\nNA\n\n\nIncome Before Income Tax_12m\n30.69\n44.94\n45.24\n26.99\n46.87\n50.08\n63.09\n57.51\n14.81\n-5.66\n-5.80\n-10.31\n-18.15\n-5.91\n-15.93\n-30.66\n-29.56\n-47.21\n-43.71\n-43.49\n-38.09\n-47.25\n-57.74\n-92.04\n-91.91\n-72.01\n-57.49\n-9.23\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nProvision for (benefit) Income Tax_12m\n1.49\n6.84\n-41.85\n-42.66\n-42.81\n-41.01\n13.26\n1.99\n0.56\n0.23\n0.74\n0.17\n0.54\n0.73\n0.83\n2.12\n2.44\n1.92\n2.61\n3.54\n5.04\n2.94\n2.42\n1.39\n-1.03\n1.61\n2.80\n2.96\nNA\nNA\nNA\nNA\n2.82\n3.43\n3.43\n4.30\n4.66\n4.63\n3.72\n4.72\n3.26\n1.84\n2.62\n85.73\n91.43\n91.64\n86.15\n-17.11\n-9.83\n-8.05\n-9.00\n10.12\n6.63\n0.67\n-15.86\nNA\nNA\nNA\n\n\nNet Income (loss) (continous operations)_12m\n29.21\n38.11\n87.09\n69.65\n89.68\n91.09\n49.83\n55.53\n14.26\n-5.88\n-6.27\n-10.22\n-18.43\n-6.38\n-16.68\n-32.70\n-31.91\n-49.04\n-45.81\n-46.52\n-42.63\n-49.69\n-69.57\n-102.84\n-100.94\n-83.03\n-60.29\n-12.19\nNA\nNA\nNA\nNA\n14.95\n13.36\n23.16\n35.35\n33.56\n26.61\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n\n\n\n\n\nCash Flow Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_CF_12TM &lt;- calculate_trailing_months(df_std_CF,12)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_CF_12TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_CF_12TM_t &lt;- transpose_df(df_std_CF_12TM, order_df)\n\n# Format numeric columns to 2 decimal places\ndf_std_CF_12TM_t &lt;- df_std_CF_12TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_CF_12TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-06-09\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\n(Operating Activities) Cash Flow Depreciation, Depletion, Ammortization_12m\n9.26\n8.95\n8.82\n10.72\n11.36\n12.48\n12.16\n12.43\n12.68\n12.67\n10.30\n9.93\n11.71\n13.07\n8.67\n18.14\n21.46\n24.17\n35.13\n34.26\n34.44\n34.16\n33.16\n36.63\n39.44\n42.01\n48.92\n48.73\n46.57\n45.88\n43.07\n41.42\n39.72\n37.73\n34.12\n36.62\n37.66\nNA\nNA\nNA\nNA\n45.98\n46.02\n39.09\n45.67\n47.07\n46.15\n51.80\n37.39\n33.13\n31.54\n32.76\n33.98\n33.45\n38.56\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Receivable_12m\n-3.82\n21.76\n2.76\n-31.32\n-17.90\n-44.38\n-4.48\n56.43\n23.42\n43.75\n41.35\n38.61\n15.97\n-14.07\n-31.94\n-14.58\n-2.30\n-3.47\n-5.97\n-18.30\n-30.44\n-10.60\n-6.38\n11.18\n21.03\n-19.34\n-37.14\n-19.53\n13.01\n10.20\n-20.61\n15.74\n-18.85\n-71.13\n-11.48\n7.81\n38.96\nNA\nNA\nNA\nNA\n0.38\n-4.23\n15.33\n-29.75\n3.51\n-1.25\n-9.09\n3.29\n-8.00\n-27.81\n-47.68\n6.48\n-58.96\n1.67\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Inventory_12m\n-17.65\n-27.97\n-40.34\n-58.60\n-21.31\n-3.33\n19.38\n63.09\n48.66\n45.32\n35.22\n2.90\n-11.58\n-15.62\n-10.72\n4.16\n3.55\n0.38\n0.85\n-8.64\n-9.32\n-4.55\n-15.69\n-19.06\n-13.47\n-17.01\n5.07\n9.75\n14.00\n14.90\n-6.33\n-20.41\n-26.00\n-18.28\n-7.37\n26.74\n37.27\nNA\nNA\nNA\nNA\n-9.86\n-12.92\n-14.12\n-6.13\n5.05\n10.67\n14.62\n4.77\n-0.93\n3.02\n-4.62\n7.87\n4.23\n-10.41\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Prepaid expenses and other assets_12m\n4.69\n0.01\n-4.38\n-3.37\n-4.77\n-4.75\n-1.49\n-18.11\n-5.98\n-7.32\n-14.31\n-3.53\n-10.56\n-20.00\n-8.05\n-8.03\n-9.64\n6.19\n-8.04\n3.24\n6.66\n11.00\n24.49\n10.33\n3.16\n2.83\n-33.49\n-21.68\n-23.29\n-38.02\n-3.20\n-7.42\n3.35\n7.51\n1.74\n1.40\n-2.41\nNA\nNA\nNA\nNA\n-0.33\n6.36\n-5.87\n-7.81\n-3.91\n-11.80\n-4.59\n-12.84\n-5.44\n-2.93\n2.84\n8.00\n2.87\n-3.22\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Payable_12m\n4.16\n11.51\n17.73\n-52.86\n-15.53\n-23.47\n-1.44\n47.74\n7.47\n13.46\n3.98\n21.34\n14.95\n-14.77\n-40.99\n-11.15\n-5.14\n4.87\n-5.13\n-2.20\n-8.99\n9.52\n46.11\n2.80\n8.95\n-0.38\n-3.75\n-6.45\n0.06\n10.56\n2.32\n8.18\n2.08\n-21.04\n-21.49\n-1.78\n2.44\nNA\nNA\nNA\nNA\n-9.07\n-12.52\n-15.75\n-9.17\n9.48\n12.17\n10.58\n3.68\n-11.09\n-16.70\n-34.44\n-2.34\n-23.71\n-18.35\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Taxes Payable_12m\n-5.88\n-4.06\n6.27\n6.23\n7.76\n9.87\n13.30\n1.63\n0.30\n-0.21\n-1.72\n-1.07\n-0.70\n-2.63\n1.10\n0.51\n0.35\n2.59\n0.46\n0.47\n0.13\n0.20\n-0.19\n-0.20\n-0.39\nNA\nNA\nNA\nNA\n-21.03\n-1.89\n-3.26\n-2.55\n-3.02\n-1.17\n1.61\n2.48\nNA\nNA\nNA\nNA\n1.14\n5.76\n1.33\n10.03\n10.32\n10.20\n-7.05\n-1.74\n-0.15\n-4.27\n5.07\n-3.41\n-4.87\n-4.66\nNA\nNA\nNA\n\n\n(Operating Activities) Change in Reserve for Sales Return and allowances_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Operating Activities) Deferred Income Tax_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-0.25\n-0.27\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n82.40\n-7.74\n-0.67\n-0.56\n-0.63\n22.59\n-4.35\n-7.41\n-29.27\nNA\nNA\nNA\n\n\n(Operating Activities) Stock-based Compensation_12m\n8.49\n8.00\n7.59\n6.75\n6.05\n4.83\n3.89\n3.20\n2.42\n1.93\n2.02\n2.06\n2.39\n2.26\n2.46\n2.82\n2.51\n2.88\n2.57\n2.47\n2.38\n2.43\n2.60\n2.63\n3.03\n3.11\n2.62\n2.00\n1.75\n1.62\n1.36\n1.70\n1.68\n1.56\n1.93\n1.78\n1.70\nNA\nNA\nNA\nNA\n1.15\n1.08\n0.49\n0.70\n0.99\n1.12\n1.24\n1.29\n1.09\n1.60\n2.33\n3.43\n4.20\n4.44\nNA\nNA\nNA\n\n\n(Operating Activities) Cash Flow from Operating Activities_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-9.92\n11.40\n31.18\n11.25\n-6.73\n16.72\n36.27\n34.26\n60.39\n65.80\n35.03\n3.86\n-29.18\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Property, Plant and Equipment_12m\n7.65\n8.91\n8.02\n10.03\n12.06\n10.39\n9.94\n9.78\n8.57\n8.22\n8.47\n7.66\n8.16\n8.27\n7.96\n8.54\n8.54\n9.42\n9.85\n10.47\n11.66\n11.77\n14.01\n13.82\n13.12\n14.92\n13.99\n16.27\n15.32\n14.77\n14.73\n12.77\n18.58\n17.84\n16.16\n14.81\n12.41\nNA\nNA\nNA\nNA\n9.35\n10.13\n9.22\n11.39\n11.82\n13.06\n12.64\n11.40\n12.45\n12.45\n13.61\n13.66\n11.54\n12.40\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from Asset Sales_12m\n0.02\n0.04\n0.00\n0.00\n0.07\n0.05\n0.05\n0.05\n0.01\n0.07\n-0.10\n-0.11\n0.00\n-0.06\n0.10\n0.12\n0.00\n0.06\n0.06\n0.13\n0.16\n0.10\n0.16\n0.08\n0.07\n0.07\n0.01\nNA\nNA\nNA\nNA\nNA\n-0.06\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-1.95\nNA\nNA\nNA\nNA\n-0.06\n-0.47\n-0.47\n-0.51\n-0.46\n-0.12\n-0.12\n-0.06\n-0.92\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Businesses_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Marketable Securities and Investment_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n0.00\n0.00\n0.00\n0.00\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from sale or maturity of Marketable Securities and Investment_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from maturities of Marketable Securities and Investment_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Cash Flow from Investing Activities_12m\n-9.06\n-8.90\n-7.97\n-10.00\n-12.04\n-10.39\n-9.94\n-9.78\n-8.56\n-8.19\n-8.41\n-7.61\n-8.05\n-8.18\n-7.90\n-8.46\n-8.53\n-9.41\n-9.82\n-10.34\n-11.53\n-11.64\n-13.78\n-13.70\n-13.55\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-7.68\n-10.76\n-18.38\n-66.76\n-70.44\n-72.74\n-82.41\n-33.65\n-34.04\n-36.30\n-20.44\n-17.32\n-16.83\n-15.95\nNA\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Stock_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment for Repurchase of Stock_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n13.50\n19.70\n20.47\nNA\nNA\nNA\nNA\nNA\n56\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n24.36\n30.00\n12.21\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Debt_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment of Debt_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash for Dividends_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n3.09\n5.25\n7.44\n8.50\n9.54\n9.97\n8.64\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash Flow from Financing Activities_12m\n-52.36\n-72.29\n-72.47\n-89.95\n-70.07\n-31.03\n-30.52\n-11.85\n-33.52\n-32.79\n-47.61\n-47.52\n-10.93\n-10.94\n-0.87\n6.30\n1.81\n-5.77\n6.92\n-13.43\n5.31\n2.89\n1.07\n18.25\n-15.71\n-29.60\n-33.44\n-39.00\n-26.38\n-14.94\n-48.18\n-28.61\n-25.99\n-13.38\n-6.07\n-24.09\n52.24\nNA\nNA\nNA\nNA\n-9.95\n-41.12\n-25.98\n-124.88\n-31.13\n-19.38\n-36.62\n-29.40\n-26.68\n-29.06\n-32.67\n-15.24\n-25.56\n-16.32\nNA\nNA\nNA\n\n\nEffect of Exchange Rate on Cash & Cash Equivalent_12m\n0.96\n1.85\n1.78\n-0.26\n-3.54\n-4.53\n-5.98\n-3.63\n-1.10\n-0.50\n2.24\n3.85\n3.55\n1.98\n1.05\n-0.98\n-0.63\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nChange in Cash, Cash Equivalents_12m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-45.18\n-10.29\n-36.03\n-23.87\n13.52\n30.70\n-7.80\n-52.84\n-8.65\nNA\nNA\nNA\nNA\n-51.94\n-72.18\n-89.23\n-151.92\n-89.19\n-67.93\n-91.49\n-25.20\n-19.91\n-21.09\n13.65\n-1.91\n22.67\n47.88\nNA\nNA\nNA\n\n\n\n\n\n\n\n\n\n\nIncome Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_IS_9TM &lt;- calculate_trailing_months(df_std_IS,9)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_IS_9TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_IS_9TM_t &lt;- transpose_df(df_std_IS_9TM, order_df)\n\n# Format numeric columns to 2 decimal places\ndf_std_IS_9TM_t &lt;- df_std_IS_9TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_IS_9TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-09-03\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\nRevenue_9m\n527.22\n604.07\n584.15\n406.30\n562.37\n675.31\n664.30\n529.26\n545.80\n537.27\n433.15\n325.16\n455.10\n450.02\n387.61\n294.98\n496.35\n524.97\n446.14\n307.96\n449.48\n484.43\n435.48\n335.41\n492.04\n518.60\n476.47\n381.09\n469.39\n536.70\n510.65\n398.60\n423.23\n619.28\n654.58\n582.34\n447.82\n666.07\n676.04\n556.04\n287.12\n473.84\n497.56\n495.19\n264.49\n472.75\n540.04\n533.25\n314.71\n501.77\n560.30\n536.67\n402.24\n618.99\n646.97\n649.91\nNA\nNA\n\n\nCost of Revenue_9m\n365.44\n412.16\n394.55\n295.11\n410.46\n493.94\n481.58\n388.41\n390.91\n380.41\n300.24\n224.45\n311.66\n315.90\n279.87\n218.31\n355.59\n382.82\n333.20\n225.77\n320.70\n342.05\n320.25\n262.24\n385.03\n400.84\n350.96\n265.25\n387.26\n434.46\n415.72\n272.49\n274.64\n411.16\n438.35\n403.34\n344.96\n507.76\n515.29\n399.92\n244.26\n377.41\n422.45\n378.18\n261.42\n375.21\n418.99\n366.09\n270.43\n398.71\n435.71\n361.64\n267.35\n418.23\n436.25\n453.98\nNA\nNA\n\n\nGross Profit_9m\n161.76\n191.91\n189.62\n111.21\n151.92\n181.37\n182.72\n140.85\n154.88\n156.86\n132.91\n95.43\n138.15\n128.83\n107.74\n72.96\n137.05\n138.45\n112.95\n71.02\n117.60\n131.20\n115.23\n89.82\n123.66\n134.42\n125.52\n115.84\nNA\nNA\nNA\n126.11\n133.12\n192.65\n200.76\n179.00\n133.62\n189.07\n191.51\n156.12\n100.32\n153.89\n132.57\n117.01\n75.10\n169.57\n193.08\n167.17\n118.96\n177.74\n199.26\n175.03\n134.89\n200.76\n210.72\n195.92\nNA\nNA\n\n\nResearch and development_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nSales general and administrative costs_9m\n136.04\n128.41\n115.18\n114.85\n118.27\n119.36\n105.75\n114.70\n115.95\n115.38\n97.08\n99.80\n106.68\n102.52\n93.96\n42.86\n62.79\n64.32\n113.73\n111.73\n122.04\n126.52\n142.55\n154.03\n170.27\n159.48\n149.56\n148.07\n160.76\nNA\nNA\nNA\n147.37\n161.17\n158.47\n141.58\n154.32\n162.94\n166.00\n132.04\n135.94\n145.04\n153.09\n145.49\n155.73\n168.62\n168.19\n149.19\n144.72\n153.53\n153.64\n137.75\n136.71\n153.00\n154.35\n156.55\nNA\nNA\n\n\nOther Non Operating Income (Loss) Net_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-21.32\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n-9.19\n-9.19\n-9.19\n0.00\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nOperating Income_9m\n25.74\n63.51\n74.45\n-3.65\n33.64\n61.70\n76.67\n25.86\n38.94\n41.49\n35.84\n2.33\n38.02\n30.99\n11.77\n-30.19\n15.22\n12.56\n-7.03\n-50.73\n-12.04\n-0.14\n-27.76\n-63.84\n-59.45\n-37.90\n-37.58\n-32.22\nNA\nNA\nNA\n20.59\n-7.29\n38.44\n49.25\n37.42\n0.62\n47.44\n46.82\n24.07\n-30.87\n13.60\n-15.77\n-28.48\n-71.44\n10.15\n34.10\n18.00\n-18.98\n30.98\n52.39\n37.28\n-1.82\n47.76\n56.37\n-67.71\nNA\nNA\n\n\nInterest Income_9m\n1.52\n1.23\n0.59\n0.27\n0.24\n0.13\n0.07\n0.01\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.01\n0.03\n0.05\n0.06\n0.07\n0.07\n0.07\n0.05\n0.04\n0.03\n0.03\n0.03\n0.02\n0.01\n0.01\nNA\nNA\nNA\n0.05\n0.05\n0.05\n0.06\n0.06\n0.07\n0.08\n0.09\n0.09\n0.15\n0.25\n0.29\n0.26\n0.23\n0.47\n0.61\n0.59\n0.38\n0.30\n0.32\n0.30\n0.28\n0.26\n0.26\nNA\nNA\n\n\nInterest Expense_9m\n2.29\n3.45\n5.74\n6.59\n9.64\n8.98\n8.89\n6.74\n7.06\n9.23\n11.91\n14.16\n15.36\n16.02\n16.66\n16.47\n15.55\n12.92\n10.56\n8.95\n9.13\n8.31\n7.24\n6.47\n6.30\n6.90\n7.50\n8.98\n9.46\nNA\nNA\nNA\n9.66\n9.55\n9.43\n9.19\n9.38\n10.24\n10.25\n9.16\n7.93\n7.25\n7.10\n7.21\n8.05\n8.01\n7.20\n6.10\n6.15\n6.17\n6.15\n6.12\n5.04\n4.57\n4.63\n5.63\nNA\nNA\n\n\nOther income (expense) Net_9m\n-1.10\n7.19\n6.66\n4.75\n4.44\n-0.96\n1.42\n-1.73\n1.90\n13.96\n26.38\n30.64\n17.81\n9.15\n-2.34\n1.40\n7.30\n17.43\n16.20\n1.39\n0.36\n0.22\n2.35\n5.04\n9.76\n8.56\n6.56\n-0.37\n-34.73\n0.81\n-0.03\n34.50\n-3.25\n39.16\n33.14\n28.19\n-8.81\n37.13\n36.49\n14.82\n-38.89\n6.20\n-23.12\n-35.99\n-79.76\n1.90\n26.43\n11.30\n-25.71\n24.43\n45.92\n30.82\n-7.17\n42.91\n51.48\n-73.60\nNA\nNA\n\n\nIncome Before Income Tax_9m\n23.03\n51.64\n61.46\n-15.26\n19.33\n53.57\n66.30\n20.84\n29.97\n18.30\n-2.45\n-42.47\n4.85\n5.81\n-2.56\n-48.09\n-7.66\n-17.84\n-33.84\n-61.14\n-21.59\n-8.72\n-37.38\n-75.39\n-75.54\n-53.38\n-51.65\n-40.84\n7.14\nNA\nNA\nNA\n-13.74\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nProvision for (benefit) Income Tax_9m\n0.01\n8.22\n12.48\n-54.23\n-44.14\n-41.43\n13.32\n1.69\n0.66\n0.14\n0.29\n0.44\n0.27\n0.45\n0.28\n1.10\n1.85\n2.16\n1.37\n1.59\n2.95\n5.28\n1.70\n0.47\n-0.70\n1.31\n0.89\n1.88\n3.29\nNA\nNA\nNA\n1.44\n2.12\n3.00\n3.12\n2.92\n3.35\n4.20\n2.54\n2.98\n1.98\n2.32\n0.44\n85.45\n91.57\n91.34\n0.86\n-23.09\n-9.90\n-2.86\n8.97\n-3.14\n4.78\n6.81\n-17.01\nNA\nNA\n\n\nNet Income (loss) (continous operations)_9m\n23.03\n43.43\n48.98\n38.97\n63.47\n95.00\n52.98\n19.15\n29.32\n18.17\n-2.73\n-42.65\n4.84\n5.62\n-2.84\n-49.11\n-9.43\n-19.91\n-35.20\n-62.22\n-24.04\n-13.50\n-39.08\n-85.27\n-84.25\n-64.75\n-52.54\n-42.72\n4.50\nNA\nNA\nNA\n-30.91\n19.09\n30.74\n32.55\n-10.51\n39.29\n34.19\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n\n\n\n\n\nCash Flow Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_CF_9TM &lt;- calculate_trailing_months(df_std_CF,9)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_CF_9TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_CF_9TM_t &lt;- transpose_df(df_std_CF_9TM, order_df)\n\n\n# Format numeric columns to 2 decimal places\ndf_std_CF_9TM_t &lt;- df_std_CF_9TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_CF_9TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-06-09\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\n(Operating Activities) Cash Flow Depreciation, Depletion, Ammortization_9m\n6.77\n7.66\n6.51\n6.09\n8.23\n10.07\n10.17\n7.53\n9.30\n10.27\n10.68\n5.40\n6.55\n9.31\n13.45\n4.14\n12.98\n17.70\n28.95\n21.13\n25.78\n27.97\n27.98\n20.03\n27.97\n33.25\n36.83\n32.32\n37.26\n37.81\n33.79\n26.66\n32.11\n31.65\n28.45\n19.36\n29.01\n31.58\nNA\nNA\nNA\n37.19\n39.63\n33.81\n20.46\n36.88\n40.68\n40.87\n26.59\n27.20\n27.66\n20.61\n21.96\n28.05\n29.57\n26.41\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Receivable_9m\n-50.94\n38.98\n104.97\n-72.31\n-78.44\n-0.68\n57.83\n-45.47\n-4.11\n67.12\n106.06\n-60.55\n11.08\n39.34\n50.64\n-131.10\n-19.47\n51.11\n79.11\n-122.49\n-35.47\n24.14\n74.48\n-110.57\n6.15\n55.77\n61.52\n-158.89\n-34.41\n88.12\n108.86\n-159.97\n-31.68\n59.07\n58.34\n-187.19\n-5.02\n169.16\nNA\nNA\nNA\n-29.55\n36.24\n152.51\n-147.72\n-59.68\n43.98\n135.93\n-127.06\n-59.90\n37.23\n117.21\n-178.03\n-45.42\n6.08\n166.56\nNA\nNA\n\n\n(Operating Activities) Change in Inventory_9m\n-18.72\n-11.34\n-11.79\n-44.11\n-59.67\n-4.68\n25.22\n33.87\n24.73\n47.31\n51.16\n6.00\n-21.03\n-9.59\n0.32\n-7.62\n-5.29\n9.58\n11.42\n-10.93\n-17.48\n-0.12\n6.02\n-17.98\n-27.22\n-9.04\n4.70\n6.15\n-4.00\n21.97\n14.53\n-9.93\n-38.41\n-18.93\n2.58\n3.11\n14.33\n36.62\nNA\nNA\nNA\n-14.48\n-5.28\n-0.58\n-16.56\n-10.75\n12.69\n24.21\n4.19\n-11.03\n1.09\n12.61\n-5.20\n-2.23\n2.30\n6.82\nNA\nNA\n\n\n(Operating Activities) Change in Prepaid expenses and other assets_9m\n6.29\n-6.51\n0.38\n0.16\n-1.77\n-11.29\n0.01\n2.04\n-15.11\n-12.52\n-5.82\n5.84\n-12.66\n-15.76\n-11.51\n1.32\n-10.13\n-5.40\n2.73\n1.31\n2.75\n-4.93\n21.77\n22.56\n6.42\n-12.77\n0.11\n-21.26\n-18.42\n-38.89\n-4.42\n-2.78\n-2.55\n2.48\n6.29\n6.38\n-4.50\n-7.44\nNA\nNA\nNA\n5.02\n-5.25\n2.34\n-1.95\n-2.46\n-15.52\n-3.59\n1.27\n-11.39\n-9.16\n-1.93\n16.95\n2.05\n-3.36\n-7.99\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Payable_9m\n-34.38\n18.29\n78.55\n-29.06\n-91.40\n-8.75\n37.35\n22.36\n-28.13\n22.19\n52.25\n-21.40\n-14.26\n23.68\n33.50\n-83.73\n-40.36\n33.31\n79.36\n-77.71\n-37.42\n19.45\n94.01\n-29.40\n-25.63\n18.88\n47.52\n-35.95\n-41.03\n19.32\n61.83\n-27.18\n-32.91\n10.84\n38.47\n-56.85\n-36.77\n34.32\nNA\nNA\nNA\n-34.70\n-5.13\n52.37\n-49.88\n-34.80\n16.87\n80.29\n-30.13\n-40.60\n-6.39\n53.01\n-68.25\n-31.85\n-13.40\n69.10\nNA\nNA\n\n\n(Operating Activities) Change in Accounts Taxes Payable_9m\n-5.48\n-2.15\n9.33\n-5.37\n6.63\n9.67\n12.93\n1.70\n0.50\n0.10\n-0.58\n-1.65\n-0.87\n-0.39\n-1.49\n0.52\n0.34\n2.59\n0.00\n0.47\n0.46\n0.13\n-0.26\n-0.19\n0.13\n-0.46\nNA\nNA\nNA\n-21.70\n1.84\n-2.75\n-3.57\n-3.22\n0.71\n-0.66\n0.59\n2.28\nNA\nNA\nNA\n1.31\n0.50\n3.63\n2.79\n10.20\n5.06\n12.50\n-14.29\n-1.86\n-5.29\n15.28\n-7.48\n-5.12\n-5.89\n5.55\nNA\nNA\n\n\n(Operating Activities) Change in Reserve for Sales Return and allowances_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Operating Activities) Deferred Income Tax_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-0.16\n-0.02\n-0.24\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n82.64\n0.00\n-8.09\n-0.56\n-0.32\n7.11\n15.17\n-4.35\n-7.10\n-44.75\nNA\nNA\n\n\n(Operating Activities) Stock-based Compensation_9m\n6.63\n5.91\n5.94\n5.60\n4.89\n3.96\n3.18\n2.74\n2.04\n1.55\n1.22\n1.56\n1.68\n2.01\n1.46\n1.96\n2.11\n2.26\n1.88\n1.71\n2.07\n1.76\n1.74\n1.84\n2.32\n2.36\n2.25\n1.83\n1.29\n1.00\n1.25\n1.19\n1.24\n1.06\n1.45\n1.42\n1.34\n1.20\nNA\nNA\nNA\n0.97\n0.87\n0.56\n0.32\n0.52\n0.78\n1.19\n0.86\n0.82\n0.75\n1.55\n1.90\n3.16\n3.35\n3.66\nNA\nNA\n\n\n(Operating Activities) Cash Flow from Operating Activities_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-13.23\n1.47\n-6.20\n50.62\n7.94\n-16.66\n-20.66\n75.64\n48.93\n27.01\n8.87\n76.41\n-7.60\n-67.97\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Property, Plant and Equipment_9m\n6.22\n5.42\n5.72\n7.22\n8.60\n8.57\n8.09\n7.13\n6.32\n6.75\n6.37\n5.82\n5.41\n6.69\n6.17\n6.12\n5.79\n6.96\n7.63\n7.43\n7.72\n9.20\n9.55\n10.97\n9.88\n10.55\n10.46\n11.14\n13.03\n10.95\n11.24\n9.60\n10.48\n14.76\n14.35\n12.99\n6.71\n9.33\nNA\nNA\nNA\n5.42\n8.15\n7.97\n7.16\n7.46\n9.84\n11.81\n8.41\n7.04\n9.23\n11.62\n10.62\n8.25\n8.32\n10.41\nNA\nNA\n\n\n(Investing Activities) Proceeds from Asset Sales_9m\n0.04\n0.02\n0.00\n0.00\n0.02\n0.05\n0.05\n0.05\n0.00\n0.01\n0.07\n-0.10\n-0.12\n-0.06\n0.11\n0.11\n0.00\n0.00\n0.07\n0.05\n0.13\n0.10\n0.11\n0.08\n0.05\n0.07\n0.02\n0.01\nNA\nNA\nNA\nNA\n-0.07\n-0.06\nNA\nNA\nNA\n-0.03\nNA\nNA\nNA\n-0.85\n-1.96\nNA\nNA\nNA\n-0.04\n-0.02\n-0.47\n-0.47\n-0.49\n-0.01\n-0.12\n-0.08\n-0.09\n-0.81\nNA\nNA\n\n\n(Investing Activities) Purchase of Businesses_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Marketable Securities and Investment_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\nNA\nNA\nNA\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\nNA\nNA\n\n\n(Investing Activities) Proceeds from sale or maturity of Marketable Securities and Investment_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from maturities of Marketable Securities and Investment_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Cash Flow from Investing Activities_9m\n-7.64\n-5.43\n-5.67\n-7.19\n-8.58\n-8.57\n-8.09\n-7.13\n-6.32\n-6.74\n-6.34\n-5.76\n-5.37\n-6.60\n-6.11\n-6.05\n-5.78\n-6.95\n-7.62\n-7.41\n-7.59\n-9.07\n-9.44\n-10.85\n-9.76\n-10.98\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-6.40\n-6.82\n-8.41\n-15.19\n-65.48\n-66.50\n-62.77\n-30.84\n-28.69\n-27.80\n-16.66\n-17.63\n-11.97\n-8.33\n-12.17\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Stock_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n9.66\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment for Repurchase of Stock_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n3.66\n13.50\n18.14\n18.37\nNA\nNA\nNA\nNA\n32.00\n56\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n19.31\n24.36\n10.69\n12.21\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Debt_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Payment of Debt_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash for Dividends_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n1.54\n3.09\n5.25\n5.90\n6.95\n7.38\n7.78\n6.04\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing Activities) Cash Flow from Financing Activities_9m\n-21.86\n-32.36\n-71.71\n-71.19\n-59.45\n-30.14\n-30.27\n-11.76\n-1.23\n-32.63\n-32.54\n-47.52\n-15.23\n-10.77\n4.13\n-0.87\n2.00\n1.98\n-0.77\n-0.25\n-13.24\n13.06\n-4.80\n14.25\n-0.30\n-5.54\n-35.47\n-37.44\n-23.59\n-2.32\n-16.97\n-46.62\n-25.82\n-13.37\n17.83\n-24.08\n-23.92\n52.25\nNA\nNA\nNA\n86.39\n-26.77\n-41.05\n-95.62\n-28.54\n-16.78\n-34.45\n-7.36\n-26.81\n-24.08\n-26.89\n-10.63\n-15.37\n-20.58\n-10.54\nNA\nNA\n\n\nEffect of Exchange Rate on Cash & Cash Equivalent_9m\n-0.17\n1.52\n0.67\n2.57\n-1.39\n-3.87\n-5.64\n-3.15\n-1.48\n-0.44\n-0.16\n2.72\n3.47\n3.61\n-0.42\n-0.08\n-1.06\n1.00\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nChange in Cash, Cash Equivalents_9m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-12.96\n-26.68\n-57.05\n5.19\n8.35\n-2.87\n9.68\n21.26\n-58.01\n-42.22\nNA\nNA\nNA\n43.70\n-48.22\n-137.80\n-71.03\n-56.28\n-65.23\n-116.50\n-10.60\n7.71\n-17.21\n-46.10\n28.25\n25.71\n26.55\n-11.87\nNA\nNA\n\n\n\n\n\n\n\n\n\n\nIncome Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_IS_6TM &lt;- calculate_trailing_months(df_std_IS,6)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_IS_6TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_IS_6TM_t &lt;- transpose_df(df_std_IS_6TM, order_df)\n\n\n# Format numeric columns to 2 decimal places\ndf_std_IS_6TM_t &lt;- df_std_IS_6TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_IS_6TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-09-03\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\nRevenue_6m\n217.48\n437.14\n476.67\n274.41\n239.37\n454.89\n543.42\n341.30\n308.84\n424.92\n349.31\n196.19\n212.81\n371.26\n321.05\n145.32\n216.22\n429.79\n375.31\n166.01\n212.78\n378.65\n342.48\n198.78\n229.63\n399.04\n381.97\n214.06\n261.53\n374.89\n369.67\n302.79\n236.79\n282.25\n523.47\n468.14\n245.31\n316.71\n551.87\n473.53\n206.68\n162.95\n391.33\n417.12\n184.30\n158.26\n394.68\n459.85\n218.76\n169.35\n428.37\n464.35\n204.25\n270.31\n546.67\n448.98\n301.23\nNA\n\n\nCost of Revenue_6m\n162.68\n296.42\n318.50\n191.79\n179.37\n334.41\n390.62\n250.49\n228.88\n299.95\n242.49\n138.21\n143.99\n253.91\n229.66\n112.20\n156.32\n305.38\n276.71\n133.93\n148.33\n264.21\n250.21\n147.88\n184.40\n314.99\n286.48\n150.33\n179.40\n322.78\n319.54\n207.86\n160.81\n178.46\n346.53\n324.52\n170.64\n253.14\n428.94\n340.97\n145.30\n157.91\n318.46\n323.49\n158.68\n157.43\n320.52\n316.25\n148.31\n171.96\n348.87\n313.59\n134.89\n180.51\n370.18\n303.79\n216.26\nNA\n\n\nGross Profit_6m\n54.78\n140.71\n158.18\n82.64\n60.01\n120.48\n152.80\n90.81\n79.96\n124.96\n106.82\n57.99\n63.53\n112.06\n91.39\n33.12\n56.19\n120.70\n98.61\n32.09\n53.27\n103.26\n92.27\n50.90\n61.88\n100.70\n95.50\n63.74\n82.12\nNA\nNA\n94.93\n75.98\n88.32\n161.47\n143.62\n74.67\n94.33\n153.69\n132.56\n61.38\n62.50\n130.33\n93.63\n25.62\n72.86\n146.19\n143.60\n70.46\n72.07\n154.17\n150.76\n69.36\n89.80\n176.49\n145.19\n84.96\nNA\n\n\nResearch and development_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nSales general and administrative costs_6m\n91.45\n93.66\n79.34\n70.59\n80.10\n82.43\n75.10\n67.58\n77.77\n85.30\n68.26\n58.90\n69.72\n77.86\n61.62\n57.00\n18.20\n30.45\n78.46\n69.14\n77.86\n86.77\n83.93\n98.37\n114.28\n111.65\n103.82\n93.57\n100.24\n115.02\nNA\nNA\n90.90\n101.47\n116.17\n102.00\n81.88\n112.02\n123.36\n93.56\n81.12\n93.30\n106.56\n98.27\n93.75\n109.20\n121.40\n106.21\n89.77\n97.93\n110.55\n98.69\n82.15\n93.62\n113.94\n99.79\n97.17\nNA\n\n\nOther Non Operating Income (Loss) Net_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n-21.32\nNA\nNA\n0.00\nNA\nNA\n0.00\n0.00\n-9.19\n-9.19\n0.00\n0.00\nNA\nNA\n0.00\n0.00\nNA\nNA\n0.00\nNA\nNA\n\n\nOperating Income_6m\n-36.66\n47.06\n78.85\n12.05\n-20.10\n38.04\n77.40\n22.93\n2.20\n39.67\n38.56\n-0.90\n0.51\n40.74\n27.76\n-25.74\n-20.44\n31.21\n17.01\n-42.69\n-32.08\n12.00\n7.90\n-47.80\n-51.70\n-23.79\n-21.86\n-29.83\n-18.11\nNA\nNA\n34.41\n-14.92\n-6.19\n52.26\n41.62\n-7.21\n3.63\n51.64\n38.99\n-19.74\n-26.05\n28.52\n-4.64\n-68.13\n-27.15\n33.99\n37.41\n-19.30\n-19.09\n50.39\n52.07\n-12.79\n-3.82\n62.55\n45.40\n-119.29\nNA\n\n\nInterest Income_6m\n1.14\n1.14\n0.47\n0.21\n0.18\n0.12\n0.07\n0.01\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.01\n0.03\n0.04\n0.04\n0.05\n0.05\n0.04\n0.03\n0.02\n0.02\n0.02\n0.02\n0.01\n0.00\n0.01\nNA\nNA\n0.04\n0.03\n0.03\n0.04\n0.04\n0.04\n0.05\n0.06\n0.06\n0.06\n0.12\n0.22\n0.20\n0.13\n0.16\n0.41\n0.51\n0.28\n0.18\n0.22\n0.22\n0.18\n0.18\n0.18\n0.16\nNA\n\n\nInterest Expense_6m\n0.85\n2.15\n2.74\n4.30\n5.29\n6.64\n6.69\n4.54\n4.40\n4.86\n7.03\n9.25\n9.79\n10.48\n11.11\n11.09\n10.93\n10.00\n7.54\n5.94\n6.03\n6.11\n5.30\n4.14\n4.27\n4.36\n4.57\n5.47\n6.44\n6.53\nNA\nNA\n6.45\n6.44\n6.32\n6.22\n6.08\n6.27\n7.27\n6.95\n5.19\n4.95\n5.04\n4.36\n4.91\n5.99\n5.16\n4.06\n4.08\n4.11\n4.13\n4.08\n4.06\n3.02\n2.53\n3.65\n4.08\nNA\n\n\nOther income (expense) Net_6m\n-1.18\n-0.21\n7.48\n6.58\n-2.65\n5.26\n0.87\n-5.67\n4.49\n1.35\n10.02\n28.97\n18.03\n1.45\n7.48\n-2.12\n-6.30\n17.12\n13.91\n2.60\n1.08\n-1.93\n1.43\n3.07\n2.89\n8.84\n6.59\n-0.31\n-0.09\n-34.70\n0.87\n34.61\n-1.01\n-2.35\n39.27\n35.38\n-13.32\n-2.68\n44.32\n31.98\n-24.99\n-31.06\n23.36\n-9.22\n-73.25\n-33.28\n28.67\n32.94\n-23.88\n-23.47\n46.07\n47.75\n-17.08\n-7.02\n59.84\n41.57\n-123.53\nNA\n\n\nIncome Before Income Tax_6m\n-37.47\n43.98\n68.16\n0.96\n-22.92\n26.03\n69.79\n24.05\n-6.70\n33.46\n21.51\n-39.12\n-27.31\n28.81\n9.16\n-34.72\n-25.09\n4.06\n-4.47\n-51.27\n-39.24\n7.78\n1.15\n-55.03\n-58.89\n-37.01\n-33.02\n-35.00\n-24.47\n25.77\nNA\nNA\n-20.39\n-10.30\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\nProvision for (benefit) Income Tax_6m\n-12.37\n6.74\n13.86\n0.10\n-55.71\n-42.76\n12.90\n1.75\n0.36\n0.24\n0.20\n-0.01\n0.54\n0.18\n0.00\n0.55\n0.83\n1.57\n1.61\n0.35\n1.00\n3.19\n4.04\n-0.25\n-1.62\n1.64\n0.59\n-0.03\n2.21\n2.99\nNA\nNA\n1.13\n0.74\n1.69\n2.69\n1.74\n1.61\n2.92\n3.02\n0.80\n1.70\n2.46\n0.14\n0.16\n85.59\n91.27\n6.05\n-5.12\n-23.16\n-4.71\n15.11\n-4.29\n-4.99\n10.92\n5.66\n-26.78\nNA\n\n\nNet Income (loss) (continous operations)_6m\n-25.09\n37.25\n54.30\n0.86\n32.79\n68.79\n56.89\n22.30\n-7.06\n33.23\n21.32\n-39.11\n-27.59\n28.89\n9.16\n-35.27\n-25.84\n2.57\n-6.07\n-51.61\n-39.74\n5.09\n-2.89\n-54.78\n-66.68\n-48.06\n-34.26\n-34.97\n-26.03\n22.78\nNA\nNA\n-21.52\n-26.77\n36.47\n40.13\n-13.31\n-4.78\n46.87\n31.39\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n\n\n\n\n\nCash Flow Statement\n\n\nShow the code\n# Calculation Trailing month\ndf_std_CF_6TM &lt;- calculate_trailing_months(df_std_CF,6)\n\n# Define the order of columns of the transposed dataframe\norder_df &lt;- colnames(df_std_CF_6TM) %&gt;% as.data.frame()\n\n# Transpose the Income Statement into standardized format\ndf_std_CF_6TM_t &lt;- transpose_df(df_std_CF_6TM, order_df)\n\n# Format numeric columns to 2 decimal places\ndf_std_CF_6TM_t &lt;- df_std_CF_6TM_t %&gt;%\n  mutate(across(where(is.numeric), ~ round(.x,2) ))\n\n# Print the standardized Income Statement in standardized format\ndf_std_CF_6TM_t %&gt;% \n  kable( \"html\") %&gt;%\n  kable_styling(full_width = FALSE) %&gt;%\n  column_spec(1, width = \"30em\", extra_css = \"white-space: nowrap;\")\n\n\n\n\n\nFinancial Item\n2024-03-31\n2023-12-31\n2023-09-30\n2023-06-30\n2023-03-31\n2022-12-31\n2022-09-30\n2022-06-30\n2022-03-31\n2021-12-31\n2021-09-30\n2021-06-30\n2021-03-31\n2020-12-31\n2020-09-30\n2020-06-30\n2020-03-31\n2019-12-31\n2019-09-30\n2019-06-30\n2019-03-31\n2018-12-31\n2018-09-30\n2018-06-30\n2018-03-31\n2017-12-31\n2017-09-30\n2017-06-30\n2017-03-31\n2016-12-31\n2016-09-30\n2016-06-30\n2016-03-31\n2015-12-31\n2015-09-30\n2015-06-30\n2015-03-31\n2014-12-31\n2014-09-30\n2014-06-30\n2014-06-09\n2014-03-31\n2013-12-31\n2013-09-30\n2013-06-30\n2013-03-31\n2012-12-31\n2012-09-30\n2012-06-30\n2012-03-31\n2011-12-31\n2011-09-30\n2011-06-30\n2011-03-31\n2010-12-31\n2010-09-30\n2010-06-30\n2009-12-31\n\n\n\n\n(Operating Activities) Cash Flow Depreciation, Depletion, Ammortization_6m\n4.04\n5.17\n5.22\n3.78\n3.60\n6.94\n7.76\n5.54\n4.40\n6.89\n8.28\n5.78\n2.02\n4.15\n9.69\n8.92\n-1.02\n9.22\n22.48\n14.95\n12.65\n19.31\n21.79\n14.85\n11.37\n21.78\n28.07\n20.23\n20.85\n28.50\n25.72\n17.38\n17.35\n24.04\n22.37\n13.69\n11.75\n22.93\n25.91\nNA\nNA\n18.56\n30.84\n27.42\n15.18\n11.67\n30.49\n35.40\n15.66\n16.40\n21.73\n16.73\n9.81\n16.03\n24.17\n17.42\n14.39\nNA\n\n\n(Operating Activities) Change in Accounts Receivable_6m\n-126.01\n-8.14\n122.19\n29.90\n-119.43\n-61.22\n101.53\n16.84\n-106.01\n39.59\n129.43\n4.16\n-88.08\n34.45\n104.05\n-48.52\n-135.99\n33.94\n133.69\n-37.41\n-139.66\n19.11\n109.22\n-29.71\n-115.60\n40.89\n136.63\n-60.23\n-173.77\n40.70\n186.78\n-30.50\n-207.39\n46.24\n188.54\n-117.37\n-200.02\n125.18\n238.98\nNA\nNA\n-192.60\n6.31\n192.98\n-10.54\n-177.65\n-19.21\n181.16\n17.96\n-190.25\n-14.67\n182.25\n-13.14\n-229.93\n19.62\n170.97\n-17.95\nNA\n\n\n(Operating Activities) Change in Inventory_6m\n-22.49\n-12.41\n4.84\n-15.56\n-45.18\n-43.04\n23.87\n39.71\n-4.49\n23.38\n53.15\n21.94\n-17.93\n-19.04\n6.35\n3.42\n-17.07\n0.74\n20.62\n-0.36\n-19.77\n-8.28\n10.45\n3.73\n-26.14\n-22.79\n12.67\n5.78\n-7.60\n3.97\n21.60\n10.93\n-27.93\n-31.34\n1.93\n13.06\n-9.30\n13.68\n46.57\nNA\nNA\n-16.92\n-9.90\n7.06\n-3.02\n-21.18\n-3.11\n26.23\n13.78\n-11.61\n-9.01\n10.68\n12.03\n-15.30\n-4.16\n19.53\n-6.25\nNA\n\n\n(Operating Activities) Change in Prepaid expenses and other assets_6m\n10.83\n-4.91\n-6.14\n4.92\n1.76\n-8.29\n-6.53\n3.54\n5.04\n-21.65\n-11.02\n14.33\n-3.29\n-17.86\n-7.27\n-2.14\n-0.78\n-5.89\n-8.86\n12.08\n0.82\n-8.84\n5.84\n19.84\n18.65\n-9.51\n-15.49\n12.34\n-18.00\n-34.02\n-5.29\n-4.00\n2.09\n-3.42\n1.26\n10.93\n0.48\n-9.53\n-2.89\nNA\nNA\n8.94\n0.10\n-9.27\n6.26\n3.40\n-14.07\n-7.31\n2.27\n2.72\n-15.11\n-8.16\n12.18\n11.00\n-4.18\n-8.13\n0.96\nNA\n\n\n(Operating Activities) Change in Accounts Payable_6m\n-81.17\n-20.25\n85.33\n31.76\n-67.60\n-84.62\n52.07\n61.15\n-53.51\n-13.41\n60.98\n26.87\n-57.00\n-5.53\n71.95\n-9.24\n-112.94\n-1.91\n107.80\n6.78\n-112.93\n-8.98\n103.94\n18.50\n-57.83\n-15.70\n66.78\n15.32\n-70.53\n-21.77\n70.59\n32.33\n-68.27\n-24.15\n70.35\n3.11\n-91.84\n-4.89\n94.28\nNA\nNA\n-68.83\n-30.76\n59.76\n18.24\n-75.51\n-27.41\n84.99\n39.58\n-74.41\n-35.90\n63.32\n19.20\n-97.76\n-21.54\n74.05\n3.19\nNA\n\n\n(Operating Activities) Change in Accounts Taxes Payable_6m\n-17.12\n-1.75\n11.24\n-2.31\n-4.97\n8.54\n12.73\n1.33\n0.57\n0.30\n-0.27\n-0.51\n-1.45\n-0.56\n0.75\n-2.07\n0.35\n2.58\n0.00\n0.01\n0.46\n0.46\n-0.33\n-0.26\n0.14\n0.06\n-0.53\nNA\nNA\n-22.01\n1.17\n0.98\n-3.06\n-4.24\n0.51\n1.22\n-1.68\n0.39\n4.16\nNA\nNA\n2.77\n0.67\n-1.63\n5.09\n2.96\n4.94\n7.36\n5.26\n-14.41\n-7.00\n14.26\n2.73\n-9.19\n-6.14\n4.32\n1.48\nNA\n\n\n(Operating Activities) Change in Reserve for Sales Return and allowances_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Operating Activities) Deferred Income Tax_6m\nNA\nNA\nNA\nNA\nNA\n-57.86\nNA\nNA\nNA\n-0.07\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-0.98\nNA\nNA\nNA\n0.21\nNA\nNA\nNA\n-1.25\nNA\nNA\nNA\n-0.26\n0.07\n0.01\n-0.34\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-1.25\nNA\nNA\nNA\nNA\n82.75\n0.24\n-0.35\n-7.98\n-0.32\n7.42\n-0.31\n15.17\n-4.04\n-22.58\n-25.23\nNA\n\n\n(Operating Activities) Stock-based 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Equipment_6m\n5.42\n3.99\n2.23\n4.92\n5.79\n5.11\n6.27\n5.28\n3.67\n4.50\n4.90\n3.72\n3.57\n3.94\n4.59\n4.33\n3.37\n4.21\n5.17\n5.21\n4.68\n5.26\n6.98\n6.51\n7.03\n7.31\n6.09\n7.61\n7.90\n8.66\n7.42\n6.11\n7.31\n6.66\n11.27\n11.18\n4.89\n3.63\n7.52\nNA\nNA\n3.36\n4.22\n5.99\n5.91\n3.23\n5.48\n8.59\n7.58\n4.05\n3.82\n8.40\n8.63\n5.21\n5.03\n6.33\n7.37\nNA\n\n\n(Investing Activities) Proceeds from Asset Sales_6m\n0.04\n0.04\n-0.02\n0.00\n0.02\n0.00\n0.05\n0.05\n0.00\n0.00\n0.01\n0.07\n-0.11\n-0.18\n0.11\n0.12\n-0.01\n0.00\n0.01\n0.06\n0.05\n0.07\n0.11\n0.03\n0.05\n0.05\n0.02\n0.02\n-0.01\nNA\nNA\nNA\n-0.07\n-0.07\n0.01\nNA\nNA\n0.00\n-0.03\nNA\nNA\n-0.85\n-0.86\n-1.10\nNA\nNA\n-0.04\n0.00\n-0.02\n-0.47\n-0.45\n-0.04\n-0.01\n-0.08\n-0.11\n0.02\n-0.81\nNA\n\n\n(Investing Activities) Purchase of Businesses_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Purchase of Marketable Securities and Investment_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n0.00\nNA\nNA\n0.00\n0.00\nNA\nNA\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\n0.00\nNA\n\n\n(Investing Activities) Proceeds from sale or maturity of Marketable Securities and Investment_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.07\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Proceeds from maturities of Marketable Securities and Investment_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Investing Activities) Cash Flow from Investing Activities_6m\n-6.86\n-4.01\n-2.20\n-4.89\n-5.77\n-5.11\n-6.27\n-5.28\n-3.67\n-4.50\n-4.89\n-3.69\n-3.52\n-3.92\n-4.53\n-4.26\n-3.37\n-4.20\n-5.16\n-5.21\n-4.66\n-5.13\n-6.87\n-6.51\n-6.91\n-7.19\n-6.64\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n-3.21\n-5.54\n-4.47\n-5.22\n-13.91\n-61.54\n-56.53\n-11.20\n-25.88\n-22.45\n-8.16\n-13.85\n-12.28\n-3.47\n-4.55\n-12.48\nNA\n\n\n(Financing Activities) Proceeds from Issuance of Stock_6m\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n0.00\n9.66\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\nNA\n\n\n(Financing 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    "text": "To kick things off, we need to import the essential libraries that will empower us to interact with the SEC’s data and perform insightful analysis. The magic happens when we source the necessary files via setup.qmd.\n\n\nTo start, we need to import the required libraries. These libraries provide functions and tools that enable us to interact with the SEC’s data and perform data analysis. The necessary libraries are listed in setup.qmd.\nThe data retrieval process is orchestrated using a set of functions located in separate R script files. We’ll be sourcing these files via setup.qmd to access the functions for retrieving, processing, and analyzing SEC data.\n\n\nShow the code\nsource(\"setup.qmd\")           # Sourcing necessary libraries\n\n\nThis sets the stage for retrieving and working with SEC data efficiently.\n\n\n\n\nIn this example, we will focus on one company, JAKKS Pacific Inc. (AAPL), as the target for our data retrieval.\n\n\nTo access the SEC API, we need to define user headers. These headers will be used for making HTTP requests to the SEC servers. We can set our user agent as an example:\n\n\nShow the code\n# Define user headers\nheaders &lt;- c('User-Agent' = 'email@address.com')\nkable(headers, \"html\", class = \"custom-table custom-narrow-table\")\n\n\n\n\n\n\nx\n\n\n\n\nUser-Agent\nemail@address.com\n\n\n\n\n\n\n\nIt’s essential to set user headers as a standard practice when accessing web APIs to identify the source of the requests.\n\n\n\n\nOur first step in data retrieval is to obtain the list of companies available on the SEC. This list contains essential information, including the Central Index Key (CIK), which uniquely identifies each company that files reports with the SEC. We’ll make an HTTP request to fetch this list:\n\n\nShow the code\n# Retrieve company list\ncompany_List &lt;- retrieve_Company_List(headers)\nkable(head(company_List), \"html\", class = \"custom-table custom-narrow-table\")\n\n\n\n\n\n\ncik_str\nticker\ntitle\n\n\n\n\n0\n0000789019\nMSFT\nMICROSOFT CORP\n\n\n1\n0000320193\nAAPL\nApple Inc.\n\n\n2\n0001045810\nNVDA\nNVIDIA CORP\n\n\n3\n0001652044\nGOOGL\nAlphabet Inc.\n\n\n4\n0001018724\nAMZN\nAMAZON COM INC\n\n\n5\n0001326801\nMETA\nMeta Platforms, Inc.\n\n\n\n\n\n\n\n\n\n\nFor our analysis, we’ll use JAKKS Pacific Inc. (JAKK) as the company of interest. The CIK for JAKKS Pacific Inc. is 0001009829.\nLet’s now select JAKKS Pacific Inc. by its CIK and retrieve its data from the SEC. The data we retrieve will be stored in the company_data object for further analysis:\n\n\nShow the code\n# Select JAKKS Pacific Inc. (AAPL) by CIK\ncik &lt;- \"0001009829\"  # CIK for JAKKS Pacific Inc.\ncompany_data &lt;- retrieve_Company_Data(headers, cik)\n\n# this the corresponding row of the company list\ncompany_List %&gt;% \n  filter(cik_str == cik) %&gt;% \n  kable(\"html\", class = \"custom-table custom-narrow-table\")\n\n\n\n\n\n\ncik_str\nticker\ntitle\n\n\n\n\n4090\n0001009829\nJAKK\nJAKKS PACIFIC INC\n\n\n\n\n\n\n\nBy following these steps, we’ve imported the necessary libraries, sourced relevant files, and initiated the retrieval of financial data from the SEC. In the subsequent chapters, we will delve deeper into exploring and analyzing the SEC data for JAKKS Pacific Inc.\nBefore we move to the next chapter we save the files.\n\n\nShow the code\n# Load company_data\nsaveRDS(company_data, file = \"company_data.RDS\") \nsaveRDS(cik, file = \"cik.RDS\")",
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    "text": "For our analysis, we’ll use JAKKS Pacific Inc. (JAKK) as the company of interest. The CIK for JAKKS Pacific Inc. is 0001009829.\nLet’s now select JAKKS Pacific Inc. by its CIK and retrieve its data from the SEC. The data we retrieve will be stored in the company_data object for further analysis:\n\n\nShow the code\n# Select JAKKS Pacific Inc. (AAPL) by CIK\ncik &lt;- \"0001009829\"  # CIK for JAKKS Pacific Inc.\ncompany_data &lt;- retrieve_Company_Data(headers, cik)\n\n# this the corresponding row of the company list\ncompany_List %&gt;% \n  filter(cik_str == cik) %&gt;% \n  kable(\"html\", class = \"custom-table custom-narrow-table\")\n\n\n\n\n\n\ncik_str\nticker\ntitle\n\n\n\n\n4090\n0001009829\nJAKK\nJAKKS PACIFIC INC\n\n\n\n\n\n\n\nBy following these steps, we’ve imported the necessary libraries, sourced relevant files, and initiated the retrieval of financial data from the SEC. In the subsequent chapters, we will delve deeper into exploring and analyzing the SEC data for JAKKS Pacific Inc.\nBefore we move to the next chapter we save the files.\n\n\nShow the code\n# Load company_data\nsaveRDS(company_data, file = \"company_data.RDS\") \nsaveRDS(cik, file = \"cik.RDS\")",
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      "**Basics**",
      "Data Retrieval"
    ]
  },
  {
    "objectID": "11_JAKK.html",
    "href": "11_JAKK.html",
    "title": "JAKKS Pacific, Inc. (JAKK)",
    "section": "",
    "text": "JAKKS Pacific, Inc. (JAKK)\nWork in progress [..]",
    "crumbs": [
      "**Real Case: AAPL**",
      "JAKKS Pacific, Inc. (JAKK)"
    ]
  },
  {
    "objectID": "A1_main_script.html",
    "href": "A1_main_script.html",
    "title": "Appendix A1: R Main script",
    "section": "",
    "text": "Appendix A1: R Main script\nWork in progress [..]",
    "crumbs": [
      "**Appendix A - R script and functions**",
      "Appendix A1: R Main script"
    ]
  }
]