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

# Introduction
Data visualizations are of great importance and are frequently used in data science. They can be used to analyze and explore the data. They also serve as great tools for delivering results. A well-designed data visualization has much more informative power than plain numbers.

Pandas isn’t a data visualization library, but it can be used to create frequently used basic plots. The `plot` function and its parameters can be used to create and customize different kinds of plots. In many cases, it saves us from having to use an additional data visualization library.

# Visualizing data distribution with a histogram

Histograms are used to visualize the distribution of values. They divide the entire value range into bins and show how many values exist in each bin. They can be considered the visual version of the `cut` function. Let’s start by creating a histogram of the `price` column in the `grocery`.

Learn how to create a histogram 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

Histogram

Introduction