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

# Problem statement

The values in the salary column of the `staff` (`DataFrame`) are stored as a string. We need to convert it to a numerical format to make calculations.

There are two issues that we need to solve before converting it to a numerical data type. 

* We need to remove the “$” sign at the beginning.
* We need to remove the “,” used as the thousands separator.


Learn how to combine multiple operations 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

Data Visualization with Seaborn for Walmart Sales Projection

Final Challenge and Quiz

Challenge: Make the Salary Column Proper