Mastering Exploratory Analysis With Pandas by Garg, Harish -- Read -- Imperial Library of Trantor

Index

Title Page Copyright and Credits

Mastering Exploratory Analysis with pandas

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Preface

Who this book is for What this book covers To get the most out of this book

Download the example code files Download the color images Conventions used

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Working with Different Kinds of Datasets

Using advanced options while reading data from CSV files

Importing modules Advanced read options

Manipulating columns, index locations, and names

Specifying a different row as a header Specifying a column as an index Choosing a subset of columns to be read Handling missing and NA data Choosing whether to skip over blank rows

Data parsing options

Skipping rows from the footer or end of the file Reading the subset of a file or a certain number of rows

Reading data from Excel files

Basic Excel read Specifying which sheet should be read Reading data from multiple sheets

Finding out sheet names Choosing header or column labels No header Skipping rows at the beginning Skipping rows at the end Choosing columns Column names Setting an index while reading data

Handling missing data while reading Reading data from other popular formats

Reading a JSON file Reading JSON data into pandas Reading HTML data Reading a PICKLE file Reading SQL data Reading data from the clipboard

Summary

Data Selection

Introduction to datasets Selecting data from the dataset

Multi-column selection Dot notation Selecting multiple rows and columns from a pandas DataFrame Selecting a single row and multiple columns Selecting values from a range of rows and all columns

Sorting a pandas DataFrame Filtering rows of a pandas DataFrame Applying multiple filter criteria to a pandas DataFrame

Filtering based on multiple conditions – AND Filtering based on multiple conditions – OR Filtering using the isin method

Using the isin method with multiple conditions

Using the axis parameter in pandas

Usage of the axis parameter

Axis usage examples More examples of the axis keyword

The axis keyword

Using string methods in pandas

Checking for a substring Changing the values of a series or column into uppercase

Changing the values into lowercase Finding the length of every value of a column Removing white spaces

Replacing parts of a column's values

Changing the datatype of a pandas series

Changing an int datatype column to a float Changing the datatype while reading data Converting string to datetime

Summary

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

Visualizing Data Like a Pro

Controlling plot aesthetics

Our first plot with seaborn Changing the plot style with set_style

Setting the plot background to a white grid Setting the plot background to dark Setting the background to white Adding ticks

Customizing styles

Style parameters Plotting context presets

Choosing the colors for plots

Changing the color palette Building custom color palettes

Plotting categorical data

Scatterplot Swarm plot Box plot Violin plot Bar plot Wide-form plot

Plotting with Data-Aware Grids

Plotting with the FacetGrid() method Plotting with the PairGrid() method Plotting with the PairPlot() method

Summary

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