Pandas Cookbook Second Edition
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Pandas Cookbook | 5,900 | 5 months ago | 32 | Jupyter Notebook | ||||||
| Recipes for using Python's pandas library | ||||||||||
| Pandas Cookbook | 596 | 2 months ago | 6 | mit | Jupyter Notebook | |||||
| Pandas Cookbook, published by Packt | ||||||||||
| Pandas Cookbook Second Edition | 234 | 2 months ago | 6 | mit | Jupyter Notebook | |||||
| Pandas Cookbook Second Edition, published by Packt | ||||||||||
| Matplotlib 3.0 Cookbook | 109 | 2 months ago | 1 | mit | Jupyter Notebook | |||||
| Matplotlib 3.0 Cookbook, published by Packt | ||||||||||
| Financial Analysis Using Python | 10 | 3 years ago | Jupyter Notebook | |||||||
| Cookbook of iPython Notebook Recipes | ||||||||||
| Data Engineering | 9 | a year ago | mit | |||||||
| Common data manipulations in different languages and frameworks. | ||||||||||
| Howtos | 5 | 2 years ago | Jupyter Notebook | |||||||
| How-To Recipes, 碎片化实用教程, 开发技巧 | ||||||||||
| Pydata Cookbook | 4 | 5 years ago | Jupyter Notebook | |||||||
| blaze, odo, pandas, numpy | ||||||||||
| Dand_vip_class | 3 | 3 years ago | ||||||||
| Udacity-DAND-VIP入门课程 每周导学及项目 | ||||||||||
| My Little Pandas Cookbook | 3 | 8 months ago | Jupyter Notebook | |||||||
Pandas 1.x Cookbook - 2nd Edition
This is the code repository for Pandas 1.x Cookbook - 2nd Edition, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.
About the Book
A new edition of the bestselling Pandas cookbook updated to pandas 1.x with new chapters on creating and testing, and exploratory data analysis. Recipes are written with modern pandas constructs. This book also covers EDA, tidying data, pivoting data, time-series calculations, visualizations, and more.
Instructions and Navigation
All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.
The code will look like the following:
def tweak_kag(df):
na_mask = df.Q9.isna()
hide_mask = df.Q9.str.startswith('I do not').fillna(False)
df = df[~na_mask & ~hide_mask]
Related Products
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Mastering Machine Learning Algorithms - Second Edition### Download a free PDF
If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.
