<?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>Chen, Daniel Y. on Wijnand Baretta</title><link>https://wijnandbaretta.com/authors/chen-daniel-y./</link><description>Recent content in Chen, Daniel Y. 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>Thu, 06 Apr 2017 00:00:00 +0000</lastBuildDate><atom:link href="https://wijnandbaretta.com/authors/chen-daniel-y./index.xml" rel="self" type="application/rss+xml"/><item><title>Pandas for Everyone: Python Data Analysis (Addison-Wesley Data &amp; Analytics Series)</title><link>https://wijnandbaretta.com/books/pandas-for-everyone-python-data-analysis-addison-wesley-data-analytics-series/</link><pubDate>Thu, 06 Apr 2017 00:00:00 +0000</pubDate><guid>https://wijnandbaretta.com/books/pandas-for-everyone-python-data-analysis-addison-wesley-data-analytics-series/</guid><description>&lt;h1 id="pandas-for-everyone-python-data-analysis"&gt;Pandas for Everyone: Python Data Analysis&lt;/h1&gt;
&lt;h2 id="summary"&gt;Summary&lt;/h2&gt;
&lt;p&gt;&amp;ldquo;Pandas for Everyone: Python Data Analysis&amp;rdquo; by Daniel Y. Chen is a comprehensive guide aimed at introducing and advancing one&amp;rsquo;s capabilities with the Pandas library in Python, an essential tool for data analysis tasks. The book focuses on providing a deep understanding of how to analyze and manipulate structured data with Pandas. It covers essential concepts such as dataset structures, advanced data cleaning, indexing, reshaping, aggregation, time series analysis, and merging datasets. Additionally, the book touches on more advanced topics like visualization and optimizing performance for large datasets. The content is structured to benefit everyone from beginners with a basic understanding of Python to more advanced users looking to refine their Pandas proficiency.&lt;/p&gt;</description></item></channel></rss>