Instructor Note: Do not make changes to this repo. See comments of this readme (view raw) for details.

• Explain the definition and purpose of Pandas in a data science context
• Manipulate Pandas DataFrames and Series
• Filter and sort Pandas data
• Manipulate DataFrame columns
• Define how to handle null and missing values
• Join multiple data sources (tables) together

Before this lesson(s), students should already be able to:

• Recall and define basic syntax for Python code

TOTAL: 155 mins

• Pandas I
  • What is Pandas (5 mins)
  • Reading Files, Selecting Columns, and Summarizing (7 mins)
  • Renaming, Adding, and Removing Columns (13 mins)
  • Filtering and Sorting (10 mins)
  • Group Exercises (20 mins)
• Pandas II
  • Handling Missing Values (25 mins)
  • Groupby / Apply (25 mins)
• Pandas Joining
  • Concatenate and Append (15 mins)
  • Join and Merge (15 mins)
  • Group Exercises (20 mins)

For more information on this topic, check out the following resources:

• List of Resources from Data School
• Another EDA Tutorial
• A discussion forum on the topic