Pandas

Analyze data with the Pandas data analysis library for Python. Start from the basics or see real-life examples of pros using Pandas to solve problems.

Recasting Low-Cardinality Columns as Categoricals

Recasting Low-Cardinality Columns as Categoricals

Downcast strings in Pandas to their proper data-types using HDF5.
Removing Duplicate Columns in Pandas

Removing Duplicate Columns in Pandas

Dealing with duplicate column names in your Pandas DataFrame.
Using Hierarchical Indexes With Pandas

Using Hierarchical Indexes With Pandas

Use Panda's Multiindex to make your data work harder for you.
Reshaping Pandas DataFrames

Reshaping Pandas DataFrames

A guide to DataFrame manipulation using groupby, melt, pivot tables, pivot, transpose, and stack.
Plotting Data With Seaborn and Pandas

Plotting Data With Seaborn and Pandas

Create beautiful data visualizations out-of-the-box with Python’s Seaborn.
Building an ETL Pipeline: From JIRA to SQL

Building an ETL Pipeline: From JIRA to SQL

An example data pipeline which extracts data from the JIRA Cloud API and loads it to a SQL database.
Downcast Numerical Data Types with Pandas

Downcast Numerical Data Types with Pandas

Using an Example Where We Downcast Numerical Columns.
Liberating Data from PDFs with Tabula and Pandas

Liberating Data from PDFs with Tabula and Pandas

Making 'open' data more open.
Importing Excel Datetimes Into Pandas, Part II

Importing Excel Datetimes Into Pandas, Part II

Import dates & times from Excel .xlsx files into Pandas!
Importing Excel Datetimes Into Pandas, Part I

Importing Excel Datetimes Into Pandas, Part I

Pandas & Excel, Part 1.