Seaborn Setup: Tools, Data Prep & EDA for Visualization

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Seaborn Setup: Tools, Data Prep & EDA for Visualization

This course is part of Seaborn Python Data Visualization & Analysis Specialization

Instructor: EDUCBA

Included with

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2 modules

Gain insight into a topic and learn the fundamentals.

5 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

5 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Configure Python and Seaborn to prepare and explore census datasets.
Generate scatter, violin, heatmap, and multivariate visualizations.
Enhance plots for readability and interpret data insights effectively.

Skills you'll gain

Tools you'll learn

NumPy

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

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This course is part of the Seaborn Python Data Visualization & Analysis Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
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There are 2 modules in this course

This hands-on course teaches learners how to prepare, analyze, and visually interpret data using Python’s Seaborn library, with a focus on census datasets. Beginning with foundational setup—such as installing Anaconda, configuring Jupyter Notebook, and loading libraries—the course progresses into exploratory data analysis and practical visualization techniques.

Learners will gain proficiency in generating a range of plots including scatter plots, line graphs, swarm plots, violin plots, heatmaps, and advanced visual grids. Emphasis is placed on enhancing plot readability through axis formatting, label alignment, and plot configuration to support data storytelling. Throughout the course, learners will apply Bloom’s Taxonomy skills such as identifying trends (Understand), configuring tools (Apply), modifying visuals (Analyze), and interpreting relationships (Evaluate). Ideal for data enthusiasts and analysts, this course equips learners to effectively visualize multivariate data, uncover insights, and support data-driven decision-making.

This module introduces learners to the foundational setup required for performing data visualization using Seaborn on census datasets. It covers essential technical prerequisites including tool installation, library setup, environment management, and preliminary data preparation. Learners will install necessary software, configure a Python environment using Anaconda and Jupyter Notebook, and explore the structure and purpose of the dataset. The module also walks through the beginning stages of exploratory data analysis (EDA), including understanding data structures and manipulating datasets to prepare them for visualization in later modules.

What's included

5 videos1 reading3 assignments

5 videos Total 29 minutes

Introduction of Project 2 minutes
Installation of Tools 7 minutes
Libraries 8 minutes
Exploratory Data Analysis 6 minutes
Add Columns to Dataset 6 minutes

1 reading Total 10 minutes

Laying the Groundwork: Tools, Data Prep, and EDA for Reliable Visualizations 10 minutes

3 assignments Total 50 minutes

Preparing the Data and Essential Tools 30 minutes
Introduction and Setup 10 minutes
Working with Data 10 minutes

This module explores advanced data visualization techniques using Seaborn to analyze census data. Learners will apply core and advanced plotting tools to generate meaningful visual interpretations, manage axis readability, and derive statistical insights through categorical and continuous data relationships. The focus includes creating scatter plots, line plots, swarm plots, violin plots, point plots, heatmaps, and grid-based multivariate plots, with an emphasis on enhancing plot clarity and interpretability.

What's included

10 videos4 assignments

10 videos Total 73 minutes

Data Visualization Scatterplot 11 minutes
Multiple Line Plot 4 minutes
Swarm plot 10 minutes
X and Y Tick Label Setting 9 minutes
Violin Plot and Bar plot 9 minutes
Point plot 6 minutes
Heat map 6 minutes
Pair plot 6 minutes
lmplot 7 minutes
Pair grid 5 minutes

4 assignments Total 60 minutes

Visualizing Census Data with Seaborn 30 minutes
Core Plotting Techniques 10 minutes
Enhancing Plot Readability 10 minutes
Advanced Visual Exploration 10 minutes

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Instructor

EDUCBA

1,035 Courses 229,970 learners

Offered by

EDUCBA

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