<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Numpy on Wijnand Baretta</title><link>https://wijnandbaretta.com/tags/numpy/</link><description>Recent content in Numpy on Wijnand Baretta</description><image><title>Wijnand Baretta</title><url>https://wijnandbaretta.com/images/og-default.png</url><link>https://wijnandbaretta.com/images/og-default.png</link></image><generator>Hugo -- 0.152.2</generator><language>en</language><lastBuildDate>Tue, 11 Jul 2017 00:00:00 +0000</lastBuildDate><atom:link href="https://wijnandbaretta.com/tags/numpy/index.xml" rel="self" type="application/rss+xml"/><item><title>Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython</title><link>https://wijnandbaretta.com/books/python-for-data-analysis-data-wrangling-with-pandas-numpy-and-ipython/</link><pubDate>Tue, 11 Jul 2017 00:00:00 +0000</pubDate><guid>https://wijnandbaretta.com/books/python-for-data-analysis-data-wrangling-with-pandas-numpy-and-ipython/</guid><description>&lt;h1 id="overview-of-python-for-data-analysis-data-wrangling-with-pandas-numpy-and-ipython-by-wes-mckinney"&gt;Overview of &lt;em&gt;Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython&lt;/em&gt; by Wes McKinney&lt;/h1&gt;
&lt;h2 id="summary"&gt;Summary&lt;/h2&gt;
&lt;p&gt;&lt;em&gt;Python for Data Analysis&lt;/em&gt; by Wes McKinney is a comprehensive guide aimed at providing readers with the necessary skills to perform data analysis using Python. The book primarily focuses on the libraries Pandas, NumPy, and IPython, which are powerful tools for data manipulation and analysis. It covers a range of topics from data cleaning, preparation, and transformation to data visualization. McKinney, who is also the creator of the Pandas library, introduces readers to efficient techniques for handling data, offering a hands-on approach with practical examples.&lt;/p&gt;</description></item></channel></rss>