Python For Data Analysis
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Python for Data Analysis
Author: Wes McKinney
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2022-08-12
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
Python for Data Science For Dummies
Author: John Paul Mueller
language: en
Publisher: John Wiley & Sons
Release Date: 2019-01-25
The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud. Get started with data science and Python Visualize information Wrangle data Learn from data The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.
Python for Data Analytics
Learn data analysis using Python with this easy to follow beginners guide. It covers all aspects of processing, manipulation, crunching, and cleaning data using Python programming language. It has been designed to prepare you for: analyzing data creating relevant data visualizations carrying out statistical analyses for large data estimating the upcoming future trends by using current data and lots more! This book will help you learn the various parts of Python programming language, its libraries, and scientific computation using Python. Learn to practically solve extensive sets of problems related to data analysis. Python is on par with other programming languages like MATLAB, Stata, R, SAS, and others when it comes to data analysis and data visualization. Python's rich set of libraries (mainly Pandas) has grown rapidly in recent years and is considered one of the best among its competitors for tasks related to data manipulation. When combined with Python's own internal solidity, as a general purpose programming language, we can say that it is an excellent choice to build data centric web applications. You will learn how to use the essential Python libraries required for data analysis like NumPy, Pandas, matplotlib, IPython, and SciPy. Each one of them performs a particular functionality for data analysis and you will be surprised at how easy it is. So what are you waiting for? Now is your chance to learn hands on Python with ease. Click the BUY NOW button to get started on your Python journey.