Introduction to Pandas
DataFrame operations
Grouping and Aggregation
Joining and Merging
Different Data Types
Advanced Transformations
Writing Data
Alternatives to Pandas
Practice
Assignment
Gotchas & Pitfalls
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5. Different Data Types
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Suggested Topics
- String methods: .str accessor for vectorized string operations
- Common string operations: split, replace, strip, upper/lower
- Pattern matching: contains, startswith, endswith
- Extracting substrings: slicing and regex extraction
- Parsing dates: pd.to_datetime() and format strings
- Date components: extracting year, month, day, weekday
- Date arithmetic: calculating differences, adding time deltas
- Time zones: handling timezone-aware datetimes
- Resampling time series: aggregating by time periods
- Real example: cleaning messy text data and analyzing time-based patterns
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