Faster pandas

Faster pandas

with Miki Tebeka
Electronic Video - 2020

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.

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書目詳細資料
企業作者: linkedin.com (Firm)
其他作者: Tebeka, Miki (Speaker)
格式: 電子 影片
語言:English
出版: Carpenteria, CA linkedin.com, 2020.
主題:
在線閱讀:View course details on linkedin.com/learning

MARC

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520 |a 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. 
511 1 |a Presenter: Miki Tebeka 
520 |a 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. 
538 |a 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. 
655 4 |a Instructional films.  |2 lcgft 
655 4 |a Educational films.  |2 lcgft 
710 2 |a linkedin.com (Firm) 
856 4 0 |u https://www.linkedin.com/learning/faster-pandas?u=95224889&auth=true  |z View course details on linkedin.com/learning 
092 |a ONLINE CLASS