Instructor Note: Do not make changes to this repo. See comments of this readme (view raw) for details.
Topic | Description | Link |
---|---|---|
Lessons | Pandas for Exploratory Data Analysis I | Here |
Pandas for Exploratory Data Analysis II | Here | |
Pandas Joining Operations | Here | |
Solution | Pandas for Exploratory Data Analysis I | Here |
Pandas for Exploratory Data Analysis II | Here | |
Pandas Joining Operations | Here | |
Datasets | AdventureWorks Production.Product | Here |
AdventureWorks Production.ProductSubCategory | Here | |
AdventureWorks Sales.SalesOrderDetail | Here | |
AdventureWorks Sales.SalesOrderHeader | Here |
- 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: