A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistic...

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A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

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A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

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Mô tả

A Python Data Analyst’s Toolkit Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics

A Python Data Analyst’s Toolkit (sách bìa mềm keo gáy)

Categories:Mathematics

Year:2021

Edition:1st Edition

Publisher:Apress

Language:english

Pages:409

Explore the fundamentals of data analysis, and statistics with case

studies using Python. This book will show you how to confidently write

code in Python, and use various Python libraries and functions for

analyzing any dataset. The code is presented in Jupyter notebooks that

can further be adapted and extended.

This book is divided into three

parts – programming with Python, data analysis and visualization, and

statistics. You'll start with an introduction to Python – the syntax,

functions, conditional statements, data types, and different types of

containers. You'll then review more advanced concepts like regular

expressions, handling of files, and solving mathematical problems with

Python.

The second part of the book, will cover Python libraries used

for data analysis. There will be an introductory chapter covering basic

concepts and terminology, and one chapter each on NumPy(the

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