Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
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Summary
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
The second edition of Python for Data Analysis by Wes McKinney is a practical guide that equips you with the essential tools for manipulating, processing, cleaning, and analyzing datasets in Python. Whether you're new to Python or a seasoned programmer, this book provides a modern introduction to data science tools.
Key topics covered in the book include:
- Using the IPython shell and Jupyter notebook for exploratory computing.
- Learning basic and advanced features of NumPy (Numerical Python).
- Getting started with data analysis tools in the pandas library.
- Employing flexible tools to load, clean, transform, merge, and reshape data.
- Creating informative visualizations with matplotlib.
- Applying the pandas groupby facility to slice, dice, and summarize datasets.
- Analyzing and manipulating regular and irregular time series data.
- Solving real-world data analysis problems through thorough, detailed examples.
The book is updated for Python 3.6 and includes practical case studies to help you effectively tackle a wide range of data analysis challenges. If you're interested in diving into data science using Python, this book is an excellent resource!
