Python for Data Analysis
Seiten
2012
O'Reilly Media (Verlag)
978-1-4493-1979-3 (ISBN)
O'Reilly Media (Verlag)
978-1-4493-1979-3 (ISBN)
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Despite the explosive growth of data in industry after industry, learning and accessing data analysis tools has remained a challenge. This pragmatic guide demonstrates the nuts and bolts of manipulating, processing, cleaning, and crunching data with Python.
Finding great data analysts is difficult. Despite the explosive growth of data in industries ranging from manufacturing and retail to high technology, finance, and healthcare, learning and accessing data analysis tools has remained a challenge. This pragmatic guide will help train you in one of the most important tools in the field - Python. Filled with practical case studies, Python for Data Analysis demonstrates the nuts and bolts of manipulating, processing, cleaning, and crunching data with Python. It also serves as a modern introduction to scientific computing in Python for data-intensive applications. Learn about the growing field of data analysis from an expert in the community. Learn everything you need to start doing real data analysis work with Python Get the most complete instruction on the basics of the "modern scientific Python platform" Learn from an insider who builds tools for the scientific stack Get an excellent introduction for novices and a wealth of advanced methods for experienced analysts
Finding great data analysts is difficult. Despite the explosive growth of data in industries ranging from manufacturing and retail to high technology, finance, and healthcare, learning and accessing data analysis tools has remained a challenge. This pragmatic guide will help train you in one of the most important tools in the field - Python. Filled with practical case studies, Python for Data Analysis demonstrates the nuts and bolts of manipulating, processing, cleaning, and crunching data with Python. It also serves as a modern introduction to scientific computing in Python for data-intensive applications. Learn about the growing field of data analysis from an expert in the community. Learn everything you need to start doing real data analysis work with Python Get the most complete instruction on the basics of the "modern scientific Python platform" Learn from an insider who builds tools for the scientific stack Get an excellent introduction for novices and a wealth of advanced methods for experienced analysts
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.
| Erscheint lt. Verlag | 27.11.2012 |
|---|---|
| Verlagsort | Sebastopol |
| Sprache | englisch |
| Einbandart | Paperback |
| Themenwelt | Informatik ► Programmiersprachen / -werkzeuge ► Python |
| Informatik ► Web / Internet ► Suchmaschinen / Web Analytics | |
| Mathematik / Informatik ► Mathematik ► Statistik | |
| ISBN-10 | 1-4493-1979-3 / 1449319793 |
| ISBN-13 | 978-1-4493-1979-3 / 9781449319793 |
| Zustand | Neuware |
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