Pandas for Data Science
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Course Page
Section 1: Introduction to Pandas
Introduction to Pandas
How to Get Queries Resolved
Download Resources
Need For DataFrame
Creating DataFrame
Mini Challenge
Series
Mini Challenge
Complete ML Mastery
Assignment
Assignment Solution
Section 2: Setup Environment
Python Setup Local Installation
Python Setup Google Colab
Section 3: Inspecting Dataframes and Must know operations
Course Review
Inspecting Dataframes
Renaming Columns
Pandas Summary
Essential Operations
Display Options
Assignment
Assignment Solution
Section 4: Conditional filtering and sorting
Extracting Specific Part of Data - Part 1
Extracting Specific Part of Data - Part 2
Mini Challenge
at and iat
Mini Challenge
Filtering Data That Satisfy Conditions
Membership Filtering
Query and Eval
Removing Duplicates
Sorting
Map and Applymap
Assignment
Assignment Solution
Section 5: Data preparation and transformation
Apply a function rowwise or columnwise
Scaling and Standardization
Make Index as a Dataframe Column
Discretization and Binning
Course Review
Assignment
Assignment Solution
Section 6: Useful tips and tricks
Random Sampling
Dummy Variables
Categorical Data Part-1
Categorical Data Part-2
Method Chaining
Efficiently Read Data From Multiple Files
Assignment
Assignment Solution
Section 7: Data grouping and aggregation
Group by Mechanism
Mini Challenge
Iterating Between Groups
Transform
Course Review
Assignment
Assignment Solution
Section 8: Reshaping and pivoting data
Cross Tabulation
Pivoting
Wide to long and back
Assignment
Assignment Solution
Section 9: Combining dataframes
Joining Dataframes
Types of Joins
Concatenating Dataframes
Course Review
Assignment
Assignment Solution
Section 10: Data cleaning and transformations
Representing Missing Values
Threshold Based Dropping
Approaches To Filling Missing Data
Interpolation
Assignment
Assignment Solution
Section 11: Practical tips and tricks
Compressed File Formats
Sparse Datatype
Combining Categories
Split Contents of a Column
Insert Column at Specific Location
Select using both Position and Lab
Styling Dataframes
Comprehensive Profile Report
Interactive Plots
Third Party Data
Interactive Data Analysis
Course Review
Section 12: Optimizing dataframes
Optimizing dataframes
Section 13: Handling Large Data
Sampling On Load
Efficient File Formats
HDF5
Chunking
Load to Database
Course Review
Section 14: Making Pandas Faster
Faster Pandas
Numba
Dask Part-1
Dask Part-2
Modin
Swifter
Vaex
Cython
Cythonize Pandas Code
Cythonize apply
Section 15: Data Visualization
Matplotlib Part 1 - Getting Started
Matplotlib Part 2 - Plot Components
Matplotlib Part 3 - Subplots
Matplotlib Part 4 - Annotations
Dual Axis Line Plots
Bar Charts
Histogram and Density Plots
Regression Plots
Pair Plots
Course Review
Assignment
Assignment Solution
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