:Search:

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

Torrent:
Similar Posts:
Name Uploaded Size Se Le Upl. by
computer internet Numerical Python Scientific Computing and Data Scie… 2024-09-28 24.5 MB 19 32 zakareya
Nayak R Data Structures for Engineers and Scientists Using Python 202… 2024-09-12 17.0 MB 14 9 indexFroggy
Henley Wolf Learn Data Analysis with Python 2018 epub 2024-09-11 612.3 KB 26 40 hardcover
Squire Mastering Data Mining with Python 2016 pdf 2024-09-11 13.0 MB 29 20 hardcover
Layton Learning Data Mining with Python 2015 pdf 2024-09-11 3.9 MB 49 33 hardcover
Kane Frank Kane s Taming Big Data with Apache Spark and Python 2024-09-11 14.4 MB 21 40 hardcover
Python Data Science Handbook Essential Tools for Working with Data 2n… 2024-09-11 19.7 MB 97 16 indexFroggy
Python for Data Science Pro The Complete Mastery Course DevCourseWeb 2024-09-11 1.0 GB 13 17 FreeCourseWeb
Python Data Visualizations New DevCourseWeb 2024-09-11 1.6 GB 12 22 FreeCourseWeb
Web Scraping with Python Learn Data Extraction and Automation with Py… 2024-09-11 141.3 MB 15 12 FreeCourseWeb
Uploader: Source1337
Downloads: 452
Type: E-Books
Images:
A Python Data Analyst’s Toolkit: Learn Python and Python-based Libraries with Applications in Data Analysis and Statistics
Info Hash: B6EEDD754A38819F8B59F6F0940019B2CC179527
Language: English
Description: 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 scientific computation library), Pandas (the data wrangling library) and visualization libraries like Matplotlib and Seaborn. Case studies will be included as examples to help readers understand some real-world applications of data analysis.
The final chapters of book focus on statistics, elucidating important principles in statistics that are relevant to data science. These topics include probability, Bayes theorem, permutations and combinations, and hypothesis testing (ANOVA, Chi-squared test, z-test, and t-test), and how the Scipy library enables simplification of tedious calculations involved in statistics.
What You'll Learn
Further your programming and analytical skills with Python
Solve mathematical problems in calculus, and set theory and algebra with Python
Work with various libraries in Python to structure, analyze, and visualize data
Tackle real-life case studies using Python
Review essential statistical concepts and use the Scipy library to solve problems in statistics
Who This Book Is For
Professionals working in the field of data science interested in enhancing skills in Python, data analysis and statistics.
Category: Other
Size: 7.9 MB
Added: June 1, 2023, 10:53 p.m.
Peers: Seeders: 27, Leechers: 0,

Comment below