Book Image

Mastering Exploratory Analysis with pandas

By : Harish Garg
Book Image

Mastering Exploratory Analysis with pandas

By: Harish Garg

Overview of this book

<p>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. </p><p> </p><p>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. </p><p> </p><p>By the end of this book, you will have a better understanding of exploratory analysis and how to build exploratory data pipelines with Python. </p><p></p>
Table of Contents (6 chapters)

To get the most out of this book

Some programming experience in Python would help you get the most out of this course.

Download the example code files

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

  1. Log in or register at www.packt.com.
  2. Select the SUPPORT tab.
  3. Click on Code Downloads & Errata.
  4. Enter the name of the book in the Search box and follow the onscreen instructions.

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The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Mastering-Exploratory-Analysis-with-pandas. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

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Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "How to use advanced options of the read_excel method."

A block of code is set as follows:

df = pd.read_csv('IMDB.csv', encoding = "ISO-8859-1")
df.head()

Any command-line input or output is written as follows:

conda install sqlite

Bold: Indicates a new term, an important word, or words that you see on screen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Select System info from the Administration panel."

Warnings or important notes appear like this.
Tips and tricks appear like this.