Introduction
- Introduction to Pandas with Python
Data Set
- Understanding Jupiter Environment
- Reading the Data Set
- Series and Data Frame
- Operations in Data Set
- More on Panda Functions
- Column Names and Operation
- Removing Columns and Rows
- Sorting Data Frame
- Filtering Data
Data Analysis
- Filter Multiple Criteria
- Selective Columns and Rows
- Data Frame and Series
- Axis Parameter
- String Methods in Pandas
- Changing the Data Types
- Example of Data Type Change
- Group by Functions
- Functions on Series
- Plotting series in Pandas
- Dealing with Null Values
- Uses of Index
- Column in Index
- Output of Data
- Functions of iX Method
- InPlace Parameter
- Inspecting the Space
- Reducing the Space
- Using in Country Series
- Creating Manual Data Frame
- Random Sampling with Pandas
- Concept of Dummy Coding
- Creating Dummified Values
- Duplicates in Data Frame
- Functions for Date and Time
- Setting with Copy Warning
- Example on Copy Warning
- Changing the Display Option
- Formatting the Data
- Tricks for Display Options
- Data with Rows and Columns
- Converting Data Frame
Azure Data Lake
- Introduction to Azure Data Lake
- Merging Data Frames
- Shaping a Data Frame
- Filling NA Values
- Importing Time Series Data
- Working with Interpolate Method
- Stacking and Unstacking
- Stacking and Unstacking for 3 Levels
- Concept of Crosstab
- More on Crosstab
- More Options with Crosstab
- Functions of Pivot
- Pivot Table Method
- Example on Pivot Table
- Data Frame to CSV File
- Using Excel Functions
Summary
- Summary on Pandas
