Faster pandas. / with Miki Tebeka.

Format:

Video

Author/Creator:

Tebeka, Miki, speaker.

Contributor:

linkedin.com (Firm)

Language:

English

Genre:

Instructional films.

Educational films.

Video recordings.

Physical Description:

polychrome

Place of Publication:

Carpenteria, CA linkedin.com, 2020.

System Details:

Latest version of the following browsers: Chrome, Safari, Firefox, or Internet Explorer. Adobe Flash Player Plugin. JavaScript and cookies must be enabled. A broadband Internet connection.

Summary:

Learn how to make your pandas code quicker and more efficient. This course covers vectorization, common mistakes, pandas performance, saving memory, Numba, Cython, and more.

Data scientists often favor pandas, because it lets them work efficiently with larger amounts of data?a useful quality as data sets become bigger and bigger. In this course, instructor Miki Tebeka shows you how to improve your pandas? code?s speed and efficiency. First, Miki explains why performance matters and how you can measure it with Python profilers. Then, the course teaches you how to use vectorization to manipulate data. The course also walks through some common mistakes and how to address them. Python and pandas have many high-performance built-in functions, and Miki covers how to use them. Pandas can use a lot of memory, so Miki offers good tips on how to save memory. The course demonstrates how to serialize data with SQL and HDF5. Then Miki goes over how to speed up your code with Numba and Cython. Alternative DataFrames can also speed up your code, and Miki steps through some options. Plus, explore a few extra resources that you can check out.

Participant:

Presenter: Miki Tebeka

Notes:

11/18/202012:00:00AM