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Learn Pandas

Turn messy CSVs, JSON, and event logs into clean, analysis-ready data with Pandas and Polars.

What will you learn?

Learn how to manipulate data in Python with Pandas, the industry-standard data analysis library. You'll load messy JSON, CSV, and Parquet files, then clean, filter, merge, and aggregate them into analysis-ready datasets. You'll even learn about Polars, a faster, modern alternative to Pandas.

Chapter List

1
Data Manipulation
Learn the core workflow, data types, date handling, and Python comprehension tools used in data manipulation.
2
Data Formats
Learn how to work with common data formats like JSON and CSV in Python workflows.
3
Pandas
Learn Pandas fundamentals like Series, DataFrames, indexes, loading data and inspection.
4
Filtering and Sorting
Learn how to filter, sort, derive, bin, and inspect tabular data with Pandas.
5
Data Cleaning
Learn how to clean messy datasets by handling missing values, duplicates, and invalid records.
6
Merging
Combine datasets with joins, validation, unmatched records, concatenation, and integration pipelines.
7
Aggregation and Modeling
Learn how to aggregate data, use pivots, and build analytical fact and dimension tables.
8
Events and Cohorts
Wrangle event data and analyze funnels, cohorts, retention, and growth metrics.
9
Polars
Learn Polars fundamentals and how it compares to Pandas for data work in Python.

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Frequently asked Questions

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Yes! It's free to create an account and start learning. You'll get all the immersive and interactive features for free for a few chapters. After that, if you still haven't paid for a membership, you'll be in read-only (content only) mode.