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Himanshutiwari15/Data-Science-CookBook

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Data Science CookBook

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These are the topics covered

  1. Data Wrangling
  • Creating a Data Frame
  • Describing the Data
  • Navigating DataFrames
  • Selecting Rows Based on Conditionals
  • Replacing Values
  • Renaming Columns
  • Finding the Minimum, Maximum, Sum, Average, and Count
  • Finding Unique Values
  • Handling Missing Values
  • Deleting a Column
  • Deleting a Row
  • Dropping Duplicate Rows
  • Grouping Rows by Values
  • Grouping Rows by Time
  • Looping Over a Column
  • Applying a Function Over All Elements in a Column
  • Applying a Function to Groups
  • Concatenating DataFrames
  • Merging DataFrames
  1. Handling Numerical Data
  • Rescaling a Feature
  • Standardizing a Feature
  • Normalizing Observations
  • Generating Polynomial and Interaction Features
  • Transforming Features
  • Detecting Outliers
  • Handling Outliers
  • Discretizating Features
  • Grouping Observations Using Clustering
  • Deleting Observations with Missing Values
  • Imputing Missing Values
  1. Handling Categorial Data
  • Encoding Nominal Categorical Features
  • Encoding Ordinal Categorical Features
  • Encoding Dictionaries of Features
  • Imputing Missing Class Values
  • Handling Imbalanced Classes
  1. Handling Text
  • Cleaning Text
  • Parsing and Cleaning HTML
  • Removing Punctuation
  • Tokenizing Text
  • Removing Stop Words
  • Stemming Words
  • Tagging Parts of Speech
  • Encoding Text as a Bag of Words
  • Weighting Word Importance

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