Gain insights into using Python Pandas for efficient data analysis and manipulation. Delve into detailed functions, parameters, and methods to elevate your data handling skills.

A Comprehensive Practical Guide to Python Pandas_ .png

There are several exercises that focus on how to use a particular function and method. The functions are covered in detail by explaining the important parameters and how to use them. By completing this course, you will be able to do data analysis and manipulation with Pandas easily and efficiently.

Mastering Data Analysis with Python Pandas

# What is a pivot table?

A **pivot table** is a summary table obtained by grouping and aggregating values of a more extensive table. Suppose we have an orders table that contains the day, order amount, and customer code for each order. A pivot table can be created to show the daily total order amounts. We need to group the rows by day and then aggregate by taking the sum.

# Creating pivot tables with Pandas

A pivot table is a great tool to summarize, sort, group, and aggregate tabular data. Thanks to the `pivot_table` function, we can easily create pivot tables with Pandas. It has several parameters that provide flexibility comparable to Excel.

Let's create a pivot table to see the weekly total sales quantities of the product groups in the `grocery`.

Learn how to create pivot tables with Pandas.

Course Introduction

Pandas Data Structures

Creating a Data Frame

Exploring a Data Frame

Filtering a Data Frame

String Manipulation with Pandas

Date Manipulation with Pandas

Handling Missing Values with Pandas

Data Analysis with Pandas

Data Visualization with Pandas

Combining DataFrames with Pandas

Final Challenge and Quiz

The Pivot Table Function

What is a pivot table?

Creating pivot tables with Pandas