Название: Python Crash Course for Data Analysis: A Complete Beginner Guide for Python Coding, NumPy, Pandas and Data Visualization 2nd EditionАвтор: AI Publishing
Издательство: AI Publishing
Год: 2020
Формат: epub/pdf(conv.)
Страниц: 182
Название: Python Crash Course for Data Analysis: A Complete Beginner Guide for Python Coding, NumPy, Pandas and Data Visualization 2nd Edition
Автор: AI Publishing
Издательство: AI Publishing
Год: 2020
Формат: epub/pdf(conv.)
Страниц: 182
Размер: 10.4 Mb
Язык: English
Python Coding and Python for Data Analysis for Beginners with Hands-On Projects
Are you looking for a hands-on approach to learn Python coding and Python for Data Analysis fast?
Do you need to start learning Python coding and Data Analysis from Scratch?
This book is for you.
Data analysis is the lifeblood of any business and Python is the perfect language for data analysis.
In simplest terms, data analysis is the inspection, cleansing, evaluation, and transformation of data. One of the widely used languages for data analysis today is Python. Gaining a quick understanding of Python will give you an entry to this evergreen field of study.
How Is This Book Different?
The main focus of this book is on hands-on learning. The best way you can learn Python is by practicing everything you learn in real-time, step by step. And you can certainly go beyond the basics without having to swallow the whole Python official documentation.
This book aims to shorten your learning curve by presenting you with ample hands-on tools. The primary goal is to present you with the concepts, the ideas, the intuitions, and the elementary tools needed to actually start coding and analyzing data in Python.
The main advantage of buying this book is you get easy access to all the materials provided with this book—Python codes, references, exercises, and extra PDF content—on the publisher’s website, at no extra cost. You get to experiment with the practical aspects of Python right from page 1.
This book is ideal if you are new to Python and data science. The topics covered include:
Introduction to Data Analysis
Python for Data Analysis—Basics and Advanced
IPython and Jupyter Notebooks
Numpy for Numerical Data Processing
Pandas for Data Manipulation
Data Visualization