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Pandas Cookbook. Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python Theodore Petrou, Kuntal Ganguly

(ebook) (audiobook) (audiobook) Język publikacji: angielski
Pandas Cookbook. Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python Theodore Petrou, Kuntal Ganguly - okladka książki

Pandas Cookbook. Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python Theodore Petrou, Kuntal Ganguly - okladka książki

Pandas Cookbook. Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python Theodore Petrou, Kuntal Ganguly - audiobook MP3

Pandas Cookbook. Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python Theodore Petrou, Kuntal Ganguly - audiobook CD

Autorzy:
Theodore Petrou, Kuntal Ganguly
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
532
Dostępne formaty:
     PDF
     ePub
     Mobi
Ebook
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This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas 0.20. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way.

The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter.

Many advanced recipes combine several different features across the pandas 0.20 library to generate results.

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O autorach książki

Theodore Petrou is the founder of Dunder Data, a training company dedicated to helping teach the Python data science ecosystem effectively to individuals and corporations. Read his tutorials and attempt his data science challenges at the Dunder Data website.
Kuntal Ganguly is a big data analytics engineer focused on building large-scale, data-driven systems using big data frameworks and machine learning. He has around 7 years experience of building big data and machine learning applications. Kuntal provides solutions to cloud customers in building real-time analytics systems using managed cloud services and open source Hadoop ecosystem technologies such as Spark, Kafka, Storm, Solr, and so on, along with machine learning and deep learning frameworks. Kuntal enjoys hands-on software development and has single-handedly conceived, architected, developed, and deployed several large-scale distributed applications. He is a machine learning and deep learning practitioner and is very passionate about building intelligent applications.

Packt Publishing - inne książki

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