This course transports you to the captivating world of Data Visualization and Reporting. It extensively familiarizes you with various techniques and tools for creating meaningful, interactive and visually appealing reports and dashboards using libraries like Matplotlib and Seaborn.
Overview
Syllabus
- Lesson 1: Crafting Stories with Data: An Introduction to Line Plots in Python
- Sprouts Growth Over a Week Line Plot
- Mark the Growth
- Plotting the Rainfall Data
- Final Challenge: Plotting the Garden's Thirst
- Lesson 2: Creating and Customizing Pie Charts in Python with Matplotlib
- Visualizing Market Preferences with Pie Charts
- Exploding the Electronics Slice
- Adding Details to the Ice Cream Preferences Pie Chart
- Creating a Consumer Preferences Pie Chart
- Lesson 3: Exploring Data Visualization: Building Bar Plots and Histograms in Python
- Bookstore Genre Sales Visualization
- What The barh Does?
- Plotting the Readership by Genre
- Age Analysis in Readers' Habits
- Plotting the Distribution of Reading Time
- Lesson 4: Mastering Plot Styling in Python Using Matplotlib
- Visualizing Squares with Style
- Styling the Fibonacci Plot
- Styling Your Way Through Matplotlib
- Styling the Fibonacci Plot
- Styling the Fibonacci Plot
- Lesson 5: Grouping Data Narratives: Mastering Subplots and Figures in Matplotlib
- Visual Comparison of Student Scores in Math and Science
- Charting Academic Paths with Line Plots
- Academic Performance Plots Mastery
- Comparing Academic Progress with Subplots
- Adding a Bar Plot to Compare Student Grades
- Lesson 6: Mastering Scatter Plots with Seaborn in Python
- Exploring the Correlation: Study Time vs Student Performance
- Scatter Plot Creation: Study Habits Unveiled
- Scatter Plot Mastery: Study Time vs Exam Score
