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Matplotlib with Python: E-commerce Data Visualization

EDUCBA via Coursera

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Details

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

5 hours 30 minutes
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

Found in

Part of

Matplotlib: Python Data Visualization & Wrangling

Overview

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Matplotlib E-commerce Data Visualization with Python is an intermediate-level course that teaches you how to analyze e-commerce datasets and create meaningful visualizations using Python and Matplotlib. Through a practical case study, you will build the skills to set up your analysis environment, prepare data, and transform raw business data into clear visual insights. You will begin by installing and configuring Anaconda and Matplotlib, exploring dataset characteristics, identifying unique values, and preparing data for analysis. Next, you will learn the fundamentals of Matplotlib, including figures, axes, and state-based versus object-oriented plotting approaches. Building on this foundation, you will construct line graphs, histograms, bar graphs, scatter plots, pie charts, and boxplots to interpret trends, compare categories, evaluate relationships, and analyze statistical summaries such as quartiles and outliers. Designed for learners interested in data science, business analytics, or Python-based data visualization, this course emphasizes hands-on application using real e-commerce datasets. By the end of the course, you will be able to analyze e-commerce data, apply Matplotlib visualization techniques, and interpret patterns that support informed business insights and data-driven decision-making.

Syllabus

Foundations of E-commerce Data Analysis

This module introduces learners to the foundational concepts and tools required to perform e-commerce data analysis with Python and Matplotlib. Students will begin by setting up the project environment, installing essential software, and preparing the dataset for analysis. The lessons progressively cover inline functions, unique value identification, and data preprocessing for effective handling of real-world datasets. Finally, the module establishes a strong base in visualization principles, explaining figures, axes, and object-oriented plotting methods in Matplotlib. By the end of this module, learners will have the skills to set up their environment, explore datasets, and apply basic visualization techniques for business insights.

Visualizing E-commerce Data with Matplotlib

This module focuses on applying Matplotlib to create meaningful and professional visualizations for e-commerce datasets. Learners will progress from plotting simple line graphs to more advanced techniques including histograms, bar graphs, scatter plots, pie charts, and boxplots. Each lesson demonstrates how to interpret data visually, customize graphs with parameters, and highlight key insights for business decision-making. By completing this module, learners will develop the ability to transform raw e-commerce data into clear, visually appealing insights using Matplotlib.