In this course, you’ll learn how to work with medium-sized datasets by optimizing your pandas workflow, processing data in batches, and augmenting pandas with SQLite.
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“Getting a data science job would have been much harder without Dataquest. It’s a great product. I recommend it to anyone who asks me about how to get started.”
In this course, you’ll learn how to reduce the memory footprint of a pandas DataFrame while working with data from the Museum of Modern Art. You’ll learn how to work with DataFrame chunks, how to use them to increase processing speed in pandas, and how to optimize DataFrame types while exploring data from the Lending Club. You’ll also learn how to augment pandas with SQLite to combine the best of both tools. Finally, you’ll learn when to use disk space over in-memory space, as well as how to run SQL queries using pandas.
Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser. At the end of the course, you’ll complete a project that asks you to work on a real-life example — using the pandas SQLite workflow to analyze startup fundraising deals using data from CrunchBase.
Reducing the memory footprint of a pandas DataFrameProcessing large DataFrames in chunks using SQLiteLoading lessons...
Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our course, you'll master data skills and grow your career.
We believe so strongly in our courses that we offer a full satisfaction guarantee. If you complete a career course on Dataquest and aren't satisfied with your outcome, we'll give you a refund.
Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.
Build confidence with our in-depth projects, and show off your data skills.
Work with real data from day one with interactive lessons and hands-on exercises.
Impress employers by completing a capstone project and certifying it with an expert review.
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