Dive into a comprehensive 5-hour tutorial series on Python Pandas, covering essential data analysis techniques. Begin with installation and data loading, then progress through DataFrame and Series basics, indexing, filtering, data modification, and sorting. Learn to group and aggregate data for in-depth analysis, clean datasets by handling missing values and casting datatypes, work with time series data, and read/write data from various sources including Excel, JSON, and SQL. Master Pandas to efficiently manipulate, analyze, and explore complex datasets in Python.
Overview
Syllabus
Python Pandas Tutorial (Part 1): Getting Started with Data Analysis - Installation and Loading Data.
Python Pandas Tutorial (Part 2): DataFrame and Series Basics - Selecting Rows and Columns.
Python Pandas Tutorial (Part 3): Indexes - How to Set, Reset, and Use Indexes.
Python Pandas Tutorial (Part 4): Filtering - Using Conditionals to Filter Rows and Columns.
Python Pandas Tutorial (Part 5): Updating Rows and Columns - Modifying Data Within DataFrames.
Python Pandas Tutorial (Part 6): Add/Remove Rows and Columns From DataFrames.
Python Pandas Tutorial (Part 7): Sorting Data.
Python Pandas Tutorial (Part 8): Grouping and Aggregating - Analyzing and Exploring Your Data.
Python Pandas Tutorial (Part 9): Cleaning Data - Casting Datatypes and Handling Missing Values.
Python Pandas Tutorial (Part 10): Working with Dates and Time Series Data.
Python Pandas Tutorial (Part 11): Reading/Writing Data to Different Sources - Excel, JSON, SQL, Etc.
Taught by
Corey Schafer
