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

We often need to find the most frequent values in a column. There are multiple ways to perform this operation with Pandas. 

In the following exercise, we'll find the three most frequent values in a column by using the functions and methods that we've learned so far. The `find_most_frequents` function below is designed to find the three most frequent values (in order) of the given column in the `sales`.

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

* Make sure to uncomment the lines before execution.

* If we give `last_week_sales` as input to the `find_most_frequents` function, the output should be a list that contains the most frequent three values in this column, which is `[13, 12, 14]`.

Learn how to find the most frequent values in columns of a DataFrame.

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: Find the Most Frequent Values in a Column

Problem statement