Complete Python Pandas Data Science Tutorial - 2024 Updated Edition

Dive into a comprehensive Python Pandas tutorial that covers essential data science techniques for analyzing and manipulating tabular data. Learn to set up your environment, work with DataFrames, load data from various file formats, access and manipulate data, handle missing values, and perform advanced operations. Explore new features in Pandas 2.0, integrate AI tools like GitHub Copilot and ChatGPT into your workflow, and discover best practices for data analysis. Perfect for beginners and experienced users alike, this tutorial provides hands-on examples and practical insights to enhance your data science skills using Python Pandas.

- Video Overview
- Getting Started with Python Pandas | Google Colab
- Getting Started with Python Pandas | Local Environment Setup Cloning code, using virtual environment, VS Code
- Intro to Dataframes | Creating DataFrames, Index/Columns, Basic Functionality
- Loading in DataFrames from Files CSV, Excel, Parquet, etc.
- Accessing Data | .head .tail .sample
- Accessing Data | .loc .iloc
- Setting DataFrame Values w/ loc & iloc
- Accessing Single Values | .at .iat
- Accessing Data | Grab Columns, Sort Values, Ascending/Descending
- Iterating over a DataFrame df with a For Loop | df.iterrows
- Filtering Data | Syntax Options, Numeric Values, Multiple Conditions
- Filtering Data | String Operations, Regular Expressions Regex
- Filtering Data | Query Functions
- Adding / Removing Columns | Basics, Conditional Values, Math Operations, Renaming Columns
- Adding / Removing Columns | String Operations, Datetime pd.to_datetime Operations
- Saving our Updated DataFrame df.to_csv, df.to_excel, df.to_parquet, etc
- Adding / Removing Columns | Using Lambda & Custom Functions w/ .apply
- Merging & Concatenating Data | pd.merge, pd.concat, types of joins
- Handling Null Values NaNs | .fillna .interpolate .dropna .isna .notna
- Aggregating Data | value_counts
- Aggregating Data | Using Groupby - groupby .sum .mean .agg
- Aggregating Data | Pivot Tables
- Groupby combined with Datetime Operations
- Advanced Functionality | .shift .rank .cumsum .rolling
- New Functionality | Pandas 1.0 vs Pandas 2.0 - pyarrow
- New Functionality | GitHub Copilot & OpenAI ChatGPT
- What Next?? | Continuing your Python Pandas Learning…