Complete Python Pandas Data Science Tutorial - Reading CSV-Excel Files, Sorting, Filtering, Groupby

This beginner course introduces Python Pandas for loading data from CSV, Excel, and text files, reading and modifying DataFrames, filtering, sorting, conditional changes, groupby statistics, and processing large datasets in chunks. Python 3 familiarity is expected.

Syllabus

- Why Pandas?
- Installing Pandas
- Getting the data used in this video
- Loading the data into Pandas CSVs, Excel, TXTs, etc.
- Reading Data Getting Rows, Columns, Cells, Headers, etc.
- Iterate through each Row
- Getting rows based on a specific condition
- High Level description of your data min, max, mean, std dev, etc.
- Sorting Values Alphabetically, Numerically
- Making Changes to the DataFrame
- Adding a column
- Deleting a column
- Summing Multiple Columns to Create new Column.
- Rearranging columns
- Saving our Data CSV, Excel, TXT, etc.
- Filtering Data based on multiple conditions
- Reset Index
- Regex Filtering filter based on textual patterns
- Conditional Changes
- Aggregate Statistics using Groupby Sum, Mean, Counting
- Working with large amounts of data setting chunksize