This course delves deeper into advanced data preprocessing and collection techniques with an extensive focus on merging DataFrames, grouping, and sorting values. It aims to provide an in-depth comprehension of these techniques, preparing the learners to effectively manage, transform, and prepare complex datasets for analysis.
Overview
Syllabus
- Lesson 1: Mastering DataFrame Merging in Python with Pandas
- Exploring Right Join in DataFrame Merges
- Navigating Library Data: Changing Merge Type in Pandas DataFrames
- Fix the DataFrame Merging
- Merging Catalog DataFrames
- Merging Bookstore DataFrames from Scratch
- Lesson 2: Mastering DataFrame Grouping in Pandas
- Calculating Average City Income using Grouping in Pandas DataFrame
- Calculate the Max Age in Each City
- Grouping and Calculating Mean in Pandas DataFrame
- Population Analysis of Cities
- Grouping and Calculating Population by City
- Lesson 3: Mastering Filtering Techniques on Grouped DataFrames in Python
- Filtering Grouped Data in Supermarket Sales Analysis
- Modify Lambda Function in DataFrame Filtering
- Filtering Product Sales in a Grocery Store
- Supermarket Inventory Analysis
- Lesson 4: Mastering Sorting Values within Pandas DataFrame
- Sorting Stock Data Using DataFrame in Pandas
- Sort Stock Prices and Volumes in Ascending Order
- Sorting Stock Data By Price and Volume
- Analyze and Sort Stock Market Data using Python and Pandas