Python for Data Analysis isconcerned with the nuts and bolts of manipulating, processing, cleaning, andcrunching data in Python. It is also a practical, modern introduction toscientific computing in Python, tailored for data-intensive applications. Thisis a book about the parts of the Python language and libraries you’ll need toeffectively solve a broad set of data analysis problems. This book is not anexposition on analytical methods using Python as the implementation language.
Writtenby Wes McKinney, the main author of the pandas library, this hands-on book ispacked with practical cases studies. It’s ideal for analysts new to Python andfor 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 high-performance 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