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>

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Table of Contents (6 chapters)
Preface
Preface
Who this book is for
What this book covers
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Free Chapter
1
Working with Different Kinds of Datasets
Working with Different Kinds of Datasets
Using advanced options while reading data from CSV files
Reading data from Excel files
Handling missing data while reading
Reading data from other popular formats
Summary
2
Data Selection
Data Selection
Introduction to datasets
Selecting data from the dataset
Sorting a pandas DataFrame
Filtering rows of a pandas DataFrame
Applying multiple filter criteria to a pandas DataFrame
Using the axis parameter in pandas
Using string methods in pandas
Changing the datatype of a pandas series
Summary
3
Manipulating, Transforming, and Reshaping Data
Manipulating, Transforming, and Reshaping Data
Modifying a pandas DataFrame using the inplace parameter
Using the groupby method
Handling missing values in pandas
Indexing in pandas DataFrames
Renaming columns in a pandas DataFrame
Removing columns from a pandas DataFrame
Working with date and time series data
Handling SettingWithCopyWarning
Applying a function to a pandas series or DataFrame
Merging and concatenating multiple DataFrames into one
Summary
4
Visualizing Data Like a Pro
Visualizing Data Like a Pro
Controlling plot aesthetics
Choosing the colors for plots
Plotting categorical data
Plotting with Data-Aware Grids
Summary
5
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What this book covers

Chapter 1, Working with Different Kinds of Datasets, teaches you about using advanced options when reading data from CSV files and Excel files.

Chapter 2, Data Selection, looks at how to use the pandas series data structure to select data. You will also learn how to sort and filter data from pandas DataFrames and how to change datatypes in pandas series.

Chapter 3, Manipulating, Transforming, and Reshaping Data, explores how to modify pandas DataFrames. You will also learn how to use the GroupBy method, how to handle missing values, and how to index methods in pandas DataFrames. This chapter will also teach you how to work with dates and time data and how to apply functions to pandas series or DataFrames.

Chapter 4, Visualizing Data Like a Pro, will show you how to control plot aesthetics, including how to choose colors for plots. You will also learn how to plot categorical data and get to grips with plotting with data-aware grids.

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