Ebook: Mastering Exploratory Analysis with Pandas
Author: Harish Garg
- Genre: Mathematics // Mathematicsematical Statistics
- Tags: Statistics Data Analysis Exploratory Data Analysis Python Pandas
- Year: 2018
- Publisher: Packt Publishing
- Language: English
- epub
The pandas is a Python library that lets you manipulate, transform, and analyze data. It is a popular framework for exploratory data visualization and analyzing datasets and data pipelines based on their properties.
This book will be your practical guide to exploring datasets using pandas. You will start by setting up Python, pandas, and Jupyter Notebooks. You will learn how to use Jupyter Notebooks to run Python code. We then show you how to get data into pandas and do some exploratory analysis, before learning how to manipulate and reshape data using pandas methods. You will also learn how to deal with missing data from your datasets, how to draw charts and plots using pandas and Matplotlib, and how to create some effective visualizations for your audience. Finally, you will wrapup your newly gained pandas knowledge by learning how to import data out of pandas into some popular file formats.
By the end of this book, you will have a better understanding of exploratory analysis and how to build exploratory data pipelines with Python.
This book will be your practical guide to exploring datasets using pandas. You will start by setting up Python, pandas, and Jupyter Notebooks. You will learn how to use Jupyter Notebooks to run Python code. We then show you how to get data into pandas and do some exploratory analysis, before learning how to manipulate and reshape data using pandas methods. You will also learn how to deal with missing data from your datasets, how to draw charts and plots using pandas and Matplotlib, and how to create some effective visualizations for your audience. Finally, you will wrapup your newly gained pandas knowledge by learning how to import data out of pandas into some popular file formats.
By the end of this book, you will have a better understanding of exploratory analysis and how to build exploratory data pipelines with Python.
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