Crookshanks' Academy
Data Analysis

Pandas

3 Seasons · 11 Episodes · 0/11 watched

A binge-worthy 3-season journey through Pandas. Learn to turn raw numbers into decisions — one episode at a time.

About this course

A binge-worthy 3-season journey through Pandas. Learn to turn raw numbers into decisions — one episode at a time.

Pandas is a free, self-paced data analysis course from Crookshanks' Academy. It contains 11 video lessons organised into 3 seasons, each with study notes and a practice task. Track your progress as you go and earn a certificate of completion when you finish every episode.

What you'll learn

Season 1

  • 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

Season 2

  • 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

Season 3

  • 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

Episodes

  1. 1
    Python Pandas Tutorial (Part 1): Getting Started with Data Analysis - Installation and Loading Data
  2. 2
    Python Pandas Tutorial (Part 2): DataFrame and Series Basics - Selecting Rows and Columns
  3. 3
    Python Pandas Tutorial (Part 3): Indexes - How to Set, Reset, and Use Indexes
  4. 4
    Python Pandas Tutorial (Part 4): Filtering - Using Conditionals to Filter Rows and Columns