Beschreibung
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. * Use the IPython interactive shell as your primary development environment * Learn basic and advanced NumPy (Numerical Python) features * Get started with data analysis tools in the pandas library * Use highperformance tools to load, clean, transform, merge, and reshape data * Create scatter plots and static or interactive visualizations with matplotlib * Apply the pandas groupby facility to slice, dice, and summarize datasets * Measure data by points in time, whether it’s specific instances, fixed periods, or intervals * Learn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples
Produktsicherheitsverordnung
Hersteller:
dpunkt.verlag GmbH
Vanessa Niethammer
hallo@dpunkt.de
Wieblinger Weg 17
DE 69123 Heidelberg
www.dpunkt.de
Autorenportrait
Wes McKinney is the main author of pandas, the popular open sourcePython library for data analysis. Wes is an active speaker andparticipant in the Python and open source communities. He worked as aquantitative analyst at AQR Capital Management and Python consultantbefore founding DataPad, a data analytics company, in 2013. Hegraduated from MIT with an S.B. in Mathematics.
