Python for Data Analysis PDF Download Ebook. Wes McKinney provides the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, trendy introduction to scientific computing in Python, tailor-made for data-intensive applications.
It is a book about the components of the Python language and libraries you’ll successfully treat a broad set of knowledge evaluation problems. This book shouldn't be an exposition on analytical methods utilizing Python because the implementation language. Written by Wes McKinney, the principle author of the pandas library, this fingers-on book is filled with sensible cases studies.
It’s ideal for analysts new to Python and for Python programmers new to scientific computing. You can use the IPython interactive shell as your main growth environment, learn basic and advanced NumPy (Numerical Python) options, get started with data analysis tools in the pandas library, use excessive-efficiency instruments to load, clean, transform, merge, and reshape knowledge and create scatter plots and static or interactive visualizations with matplotlib.
This book shows tips to use the pandas group by facility to slice, cube, and summarize datasets, measure knowledge by cut-off dates, whether or not specific cases, mounted durations, or intervals and learn to remedy issues in web analytics, social sciences, finance, and economics, via detailed examples.
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