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Pandas Cookbook: Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python by [Petrou, Theodore]

Pandas Cookbook: Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python 1st Edition, Kindle Edition

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Product description

About the Author

Theodore Petrou is a data scientist and the founder of Dunder Data, a professional educational company focusing on exploratory data analysis. He is also the head of Houston Data Science, a meetup group with more than 2,000 members that has the primary goal of getting local data enthusiasts together in the same room to practice data science. Before founding Dunder Data, Ted was a data scientist at Schlumberger, a large oil services company, where he spent the vast majority of his time exploring data.

Some of his projects included using targeted sentiment analysis to discover the root cause of part failure from engineer text, developing customized client/server dashboarding applications, and real-time web services to avoid the mispricing of sales items. Ted received his masters degree in statistics from Rice University, and used his analytical skills to play poker professionally and teach math before becoming a data scientist. Ted is a strong supporter of learning through practice and can often be found answering questions about pandas on Stack Overflow.

Product details

  • Format: Kindle Edition
  • File Size: 51298 KB
  • Print Length: 538 pages
  • Publisher: Packt Publishing; 1 edition (23 Oct. 2017)
  • Sold by: Amazon Media EU S.à r.l.
  • Language: English
  • Text-to-Speech: Enabled
  • X-Ray:
  • Word Wise: Not Enabled
  • Screen Reader: Supported
  • Enhanced Typesetting: Enabled
  • Average Customer Review: Be the first to review this item
  • Amazon Bestsellers Rank: #342,181 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Most helpful customer reviews on 4.7 out of 5 stars 10 reviews
Dimitri Shvorob
5.0 out of 5 starsValue added
12 November 2017 - Published on
33 people found this helpful.
5.0 out of 5 starsFive Stars
12 April 2018 - Published on
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R Roberts
3.0 out of 5 starsThe useful content is crippled by lack of indexing
23 March 2018 - Published on
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3 people found this helpful.
Scott B.
5.0 out of 5 starsAn excellent book about how to and why it works for Pandas Data Analysis
26 October 2017 - Published on
8 people found this helpful.
Petter Dischington
5.0 out of 5 starsA great resource for beginning and experienced Python data analysts
24 December 2017 - Published on
3 people found this helpful.
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