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

# Visualizing daily sales

Line plots are one of the most frequently used data visualizations. We can discover the trends, seasonality, and cycles in time-series data using line plots. The x-axis of a line plot usually represents time with varying frequencies, such as an hour, day, month, year, and so on. The y-axis shows a quantity, so the line plot essentially tracks a quantity’s change over time.

For instance, we can visualize the daily sales of tomatoes in the `grocery`.



Learn how to create line plots 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

Line Plot

Visualizing daily sales