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

## Creating conditional columns

The `where` function can be used to update the values in a column based on some conditions. The `where` function evaluates the given condition and then updates the values. When the condition is `True`, the original values are kept the same. When it's `False`, the values are updated using the `other` parameter. 

Consider the `grocery` we've been using. Let's say we want to increase the prices of products cheaper than $3 by 10 percent. We can perform this operation with the `where` function as below:

# Creating conditional columns

The `where` function can be used to update the values in a column based on some conditions. The `where` function evaluates the given condition and then updates the values. When the condition is `True`, the original values are kept the same. When it's `False`, the values are updated using the `other` parameter. 

Consider the `grocery` we've been using. Let's say we want to increase the prices of products cheaper than $3 by 10 percent. We can perform this operation with the `where` function as below:

Learn how to use the Pandas "where" function.

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 "where" Function

Creating conditional columns