Python for Data Analysis: Data Wrangling with Pandas, Numpy, and Jupyter
RM375.07 RM417.21
By McKinney Wes
Paperback – English
ISBN: 109810403X
EAN: 9781098104030
Publisher: OREILLY MEDIA
Publication Date: 20/09/2022
Pages: 579
Dimension: 17.53cm x 23.11cm x 3.05cm
Age Group: NA to NA
Grades: Not Applicable to Not Applicable
Lexile Level: 0
Award: –
About Author: McKinney, Wes
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 and Python consultant before founding DataPad, a data analytics company, in 2013. He graduated from MIT with an S.B. in Mathematics.
Categories:
Computers – Data Science – Data Analytics
Computers – Languages – Python
Computers – Data Science – Data Visualization
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Description
By McKinney Wes
Paperback – English
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, and Jupyter in the process.
Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.
– Use the Jupyter notebook and IPython shell for exploratory computing
– Learn basic and advanced features in NumPy
– Get started with data analysis tools in the pandas library
– Use flexible tools to load, clean, transform, merge, and reshape data
– Create informative visualizations with matplotlib
– Apply the pandas groupby facility to slice, dice, and summarize datasets
– Analyze and manipulate regular and irregular time series data
– Learn how to solve real-world data analysis problems with thorough, detailed examples
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