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 introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.
Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Wes McKinney is the main author of pandas, the popular open source Python library for data analysis. Wes is an active speaker and participant in the Python and open source communities. He worked as a quantitative analyst at AQR Capital Management before founding an enterprise data analysis company, Lambda Foundry, in 2012. He graduated from MIT with an S.B. in Mathematics.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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