Python for Data Analysis
Data Wrangling with Pandas, Numpy, and Ipython
Ranked #4 in Data Science, Ranked #4 in Python — see more rankings.
Looking for complete instructions on manipulating, processing, cleaning, and crunching structured data in Python? The second edition of this hands-on guide--updated for Python 3.5 and Pandas 1.0--is packed with practical cases studies that show you how to effectively solve a broad set of data analysis problems, using Python libraries such as NumPy, pandas, matplotlib, and IPython.
Written by Wes McKinney, the main author of the pandas library, Python for Data Analysis also serves as a practical, modern introduction to scientific computing in Python for data-intensive... more
Written by Wes McKinney, the main author of the pandas library, Python for Data Analysis also serves as a practical, modern introduction to scientific computing in Python for data-intensive... more
Rankings by Category
Python for Data Analysis is ranked in the following categories:
- #24 in Big Data
- #17 in Data Mining
- #31 in Databases
- #41 in Machine Learning
- #83 in Programming
- #98 in Statistics
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