Data-Analysis-Using-Python

This repository consists of all the files, resources, and recorded session links which are discussed during Data Analysis using Python Online Training during 14-Sept-2020 to 26-Sept-2020 Timings 1 PM to 4 PM

Few resources avaliable @ [resources.md] file don't forget to use them

Everyone should compulsory follow the below instruction in order to get the attendance --> Certificate

1. Login format rollnumber-name
2. Don't give spaces in roll number or shorcut of your roll number
3. Don't give spaces between rollnumber and name (only - single minus or hyphen character)
4. Make sure roll number should match with the registered roll number
5. Minimum 110 minutes should attend in 150 minutes` session with same login format

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Day01 Introduction to Data and Data Analysis Using Python (14-Sept-2020)

Discussed Concepts:

• Introduction to Data
• Types of Data in Statistics (Numerical & Categorical)
• Types of data in real world
• Introduction to Python
• Features and Applications of Python
• Ananconda Software installation for Jupyter Notebook

[Day1_Introduction to Data and Data Analysis Using Python_Slides]

[Day1_Recorded_Video]

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Day02 Introduction to Python & Conditional Statements (15-Sept-2020)

Discussed Concepts:

• Literate Programming
• Jupyter Notebook Environment
• Markdown format for documentation
• Python basics
• Operators in Python
• Conditional Statements in python

Day02 Jupyter Notebook [.ipynb format], [.pdf format]

[Day02 Recorded Video Link]

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Day - 3(16-09-2020)

Topics Discussed:

• Iterations
• Strings
• String Functions,String Slicing
• Python Data Structures
• Lists
• List Methods
• Tuples
• Tuple Methods
• Examples on Each topics

Materials

Recorded Video Link -->Click Here
Jupyer Notebook --> .ipynp File-->pdf Format .pdf File

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Day - 4(17-09-2020)

Topics Discussed:

• Dictionaries
• Dictionary Methods
• File Handling
• Packages and Modules
• List & Dictionary Comprehension
• set

Materials

Recorded Video Link -->Click Here
Jupyer Notebook --> .ipynp File

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Day - 5(18-09-2020)

Topics Discussed:

• Data Manipulation with NumPy
  • Introduction to Numpy
  • NumPy Arrays
  • NumPy Basics
  • Indexing
  • Math

Materials

Recorded Video Link -->Click Here
Jupyer Notebook --> .ipynp File

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Day - 6(19-09-2020)

Topics Discussed:

-Data Manipulation with NumPy

• Different ways to create arrays
• Random module
• Filtering
• Statistics & Aggregation Function in numpy
• Saving and Loading Data

Materials

Recorded Video Link -->Click Here
Jupyer Notebook --> .ipynp File

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Day - 7(21-09-2020)

Topics Discussed:

• Data Analysis with pandas
  • Introduction Series
  • Indexing
  • File I/O
  • Grouping Features
  • Filtering
  • Sorting
  • statistics
  • Plotting

Materials

Recorded Video Link -->Click Here
Jupyer Notebook --> .ipynp File

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Day - 8(22-09-2020)

Topics Discussed:

• Cleaning Data in Python
  • DataFrame Combining
  • Working with Duplicates and Missing Values
  • Filling missing data
  • Dropping duplicate data
  • Which values should be replace with missing values based on data

Materials

Recorded Video Link -->Click Here
Jupyer Notebook --> .ipynp File

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Day09 Data Preprocessing using Sklearn (23-Sept-2020)

Discussed Concepts:

• Identifying and Eliminating Outliers
• Filling missing data
• Applying on raw dataset and introduction to Kaggle and other data sources
• Introduction
• Standardizing Data
• Data Range
• Robust Scaling

Day09 Jupyter Notebook [.ipynb format], [.pdf format]

[Day09_Recorded_Video]

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Day10 Introduction to Visualization and Python packages (24-Sept-2020)

Discussed Concepts:

• Normalizing Data
• Data Imputation
• Introduction to Plotting
• Matplotlib history
• Line Plot
• Scatter Plot
• Bar Graph

Day10 Jupyter Notebook [.ipynb format], [.pdf format]

[Day10_Recorded_Video]

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Day11 Data Visualization using Seaborn (25-Sept-2020)

Discussed Concepts:

• Bar Graph
• Histogram
• Pie Chart
• Box Plot
• Color Palettes

Day11 Jupyter Notebook [.ipynb format], [.pdf format]

[Day11_Recorded_Video]

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Day12 Data Visualization using Seaborn Using Seaborn Styles (26-Sept-2020)

Discussed Concepts:

• Setting the default style
• stripplot() and swarmplot()
• boxplot, violinplot
• Regression Plot
• barplot, pointplot and countplot
• Creating heatmap
• Creating pairplot

Day12 Jupyter Notebook [.ipynb format], [.pdf format]

[Day12_Recorded_Video]

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