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Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern Python for Data Analysis, 2e: Amazon.in: Wes Mckinney: Books. Don't have a Kindle? Get your Kindle here, or download a FREE Kindle Reading App. Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on PDF | —In this paper we will discuss pandas, a Python library of rich data structures and tools for pandas: a Foundational Python Library for Data Analysis and Statistics Content uploaded by Wes Mckinney Download full-text PDF. 1. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython: Wes McKinney: Get your Kindle here, or download a FREE Kindle Reading App. Wes McKinney is a New York?based software developer and entrepreneur. 11 Mar 2013 itself was not specifically designed with data analysis or scientific computing in mind. Though there are various ways to install Python, the one I would suggest for use in data science is Wes McKinney's book includes a chapter that covers using IPython as a data sci‐ 'pdf': 'Portable Document Format',.

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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. 541 Pages · 2017 · 12.52 MB · 20,003 Downloads ·English. by Wes McKinney.

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I think Automating the boring stuff with Python by Al Sweigart to be the best book to begin with python. It introduces the basics and moves in a pace that is comfortable to grasp and does not drown in too much of details.

Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python.

Python bindings of the widely used computer vision library OpenCV utilize NumPy arrays to store and operate on data. Since images with multiple channels are simply represented as three-dimensional arrays, indexing, slicing or masking with…