Month 9: Data Analysis using Pandas Library
Week 1: Introduction to Pandas
- Day 1: Introduction to the Pandas Library
- Day 2: Series and DataFrames
- Day 3: Accessing Data in Pandas
- Day 4: Cleaning Data in Pandas
- Day 5: Data Wrangling with Pandas
Week 2: Intermediate Pandas
- Day 1: Working with Text Data
- Day 2: Working with Dates and Time Series Data
- Day 3: Handling Missing and Duplicate Data
- Day 4: Merging, Joining, and Concatenating DataFrames
- Day 5: Grouping and Aggregation in Pandas
Week 3: Advanced Pandas
- Day 1: Applying Functions to DataFrames
- Day 2: Sorting and Ranking in Pandas
- Day 3: Pivot Tables in Pandas
- Day 4: Working with Large Datasets in Pandas
- Day 5: Performance Tuning in Pandas
Week 4: Data Analysis Projects with Pandas
- Day 1: Project 1 – E-commerce Data Analysis
- Day 2: Project 2 – Stock Market Data Analysis
- Day 3: Project 3 – Real Estate Data Analysis
- Day 4: Project 4 – Sports Data Analysis
- Day 5: Project 5 – Social Media Data Analysis
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