Learn about DataFrames in the pandas library and how we can perform different operations on them.

Pandas: Python for Data Analysis

In this module, we’ll learn about DataFrames and their functions in detail. We’ll also learn to perform data manipulation and data visualization using pandas. We’ll solve several exercises that focus on how to use a DataFrame and its methods. By the end of this module, we’ll be able to do data analysis and manipulation with pandas easily and efficiently.

A Comprehensive Practical Guide to Python Pandas

## Problem statement

Up to this point, we’ve covered:

* How to find the number of unique values in a column.
* How to find the average value of a column.
* How to filter the values in a `DataFrame`.

The challenge is to find the number of products that are priced higher than the average product price in the sales data frame. As a hint, keep in mind that you need to use the operations specified with the bullet points above.

## Solution

Write your solution in the specified place and click on "test".

* Make sure to uncomment the lines before execution.

# Problem statement

Up to this point, we’ve covered:

* How to find the number of unique values in a column.
* How to find the average value of a column.
* How to filter the values in a `DataFrame`.

The challenge is to find the number of products that are priced higher than the average product price in the sales data frame. As a hint, keep in mind that you need to use the operations specified with the bullet points above.

# Solution

Write your solution in the specified place and click on "test".

* Make sure to uncomment the lines before execution.

Learn how to find values below average in a column of a DataFrame.

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

Conclusion

Challenge: Filter Out the Values Below Average

Problem statement