Python for Data Analysis
Publication details: Mumbai Shroff Publishers & Distributors Pvt. Ltd. 2022 Edition: 3Description: 561ISBN: 978-9355421906Subject(s): Computer ScienceDDC classification: 001.6424502 MAR.RAV Summary: 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| Cover image | Item type | Home library | Call number | Materials specified | Status | Date due | Barcode |
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Parvatibai Chowgule College of Arts and Science, Margao Computer Science | 001.6424502 MAR.RAV (Browse shelf(Opens below)) | Checked out | 20.07.2024 | PCC-49016 |
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| 001.6424502 LUT/Pyt Python Pocket Reference | 001.6424502 MAR/Pyt Python in a nutshell | 001.6424502 MAR.RAV Python in a Nutshell | 001.6424502 MAR.RAV Python for Data Analysis | 001.6424502 MOT/Dat Data Analytics using Python | 001.6424502 MUE.MAS Python for Data Science For Dummies | 001.6424502 PRA.KUM Machine Learning using Python |
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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