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All LessonsFree Lessons (3)

Introduction

Before We Start Data Structures Series Introduction NaN Values in Series Similarities in pandas and NumPy Categorical Data in pandas Exercise: Series in pandas Solution: Series in pandas Summary Quiz: pandas Series

Series Deep Dive

Data Loading and Series Attributes Operators and Dunder Methods Aggregate Methods Exercise: Aggregate Methods Solution: Aggregate Methods Conversion Methods Manipulation Methods Quiz: Methods in Series Conditional Methods Handling Missing Data Other Manipulation Methods Data Cleaning Quiz: Duplicate values and NaN Indexing Operations Indexing Operations (.iloc)Exercise: Data Manipulation and Indexing Solution: Data Manipulation and Indexing Quiz: Indexing, Manipulation Methods, and Data Cleaning String Manipulation Optimizing Manipulations Using Cython Date and Time Manipulation Dates in the Index Quiz: String Manipulation, Date-Time Manipulation, and DT Indexing Plotting with a Series: Histogram, Box Plot, and Kernel Density Plotting with a Series: Line, Bar, and Pie Plots Categorical Manipulation Quiz: Plotting and Categorical Data

DataFrames

Introduction to DataFrames Similarities between Series and DataFrame Math Methods on DataFrames Quiz: DataFrames and Math Methods on DataFrames Exercise: DataFrames in pandas Solution: DataFrames in pandas Looping and Aggregation The apply() Method Exercise: Looping, Aggregation and apply() Method Solution: Looping, Aggregation, and apply() Method Columns Types, .assign, and Memory Usage Creating and Updating Columns Dealing with Missing and Duplicated Data Quiz: Missing and Duplicated Data Sorting Columns and Indexes Filtering and Indexing Operations Indexing by Position Indexing by Name Filtering with Function and .loc Line and Bar Plots Scatter, Area, and Stacked Bar Plots Exercise: Sorting, Columns, Filtering, and Indexing Operations.Solution: Sorting, Columns, Filtering, and Indexing Operations Exercise: Plotting Solution: Plotting Quiz: Sorting Columns, Filtering, and Indexing Operations.Reshaping DataFrames with Dummies Reshaping by Pivoting and Grouping Aggregations

Manipulating Data

More Aggregations

Cross-tabulation Deep Dive

Exercise: Reshaping/Aggregations

Solution: Reshaping/Aggregations

Quiz: Reshaping, Pivot Tables, Aggregations

Melting and Transposing Data

Stacking and Flattening Data

Quiz: Melting, Transposing, Stacking, and Unstacking Data

Working with Time Series

Adding Rows and Columns in a DataFrame

Joins in DataFrames

Joining Real-World Datasets

Quiz: Joining in pandas

Exporting Data to CSV and Excel

Exporting Data to Feather, SQL, and JSON

Styling DataFrames

Checking if DataFrames are Equal

Debugging Chains

Debugging apply (and friends)

Debugging Memory Usage and Timing Information

Wrapping Up

Appendix

Effective Data Manipulation with pandas/

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Debugging apply (and friends)

Debugging apply (and friends)

Explore various techniques for debugging pandas.

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It can be confusing to keep track of what pandas passes around when we call apply, assign, groupby(...)apply, groupby(...)agg, groupby(...)transform, pipe, and others. What’s getting passed in? A Series, DataFrame, group? One answer is to look at the ...