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Matplotlib for Data Scientists

Transform data into visual stories with Matplotlib mastery!

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Matplotlib for Data Scientists
4 Modules

Course Curriculum

4 Modules · 13 Chapters · 14 Topics · 95 Sub-topics

01
Foundation
3 Chapters · 3 Topics · 18 Sub-topics
Introduction to Matplotlib
1 Topics
Introduction to Matplotlib
5 Sub-topics
What is Matplotlib and Why Use It
Installing Matplotlib and Verifying Setup
Understanding Pyplot vs Object-Oriented Interface
Your First Plot - Hello Matplotlib
Jupyter Notebook Integration and Magic Commands
Basic Plotting Fundamentals
1 Topics
Basic Plotting Fundamentals
6 Sub-topics
Understanding plot() Function Basics
Creating Simple Line Plots
Plotting Multiple Lines on One Graph
Setting X and Y Axis Data
Understanding Matplotlib's State Machine
Quick Styling with Format Strings
Figure and Axes Architecture
1 Topics
Figure and Axes Architecture
7 Sub-topics
Understanding Figure Objects
Understanding Axes Objects
Creating Figures with plt.figure()
Creating Figures with plt.subplots()
Figure Size and DPI Settings
Axes vs Axis - Clearing the Confusion
The Anatomy of a Matplotlib Plot
02
Statistical Plots
4 Chapters · 4 Topics · 28 Sub-topics
Scatter Plots
1 Topics
Scatter Plots
7 Sub-topics
Creating Basic Scatter Plots
Marker Size Variation by Data
Color Mapping by Data Values
Adding Color Bars
Marker Transparency and Overlapping Data
Scatter Plot with Different Marker Types
Bubble Charts
Histograms and Distributions
1 Topics
Histograms and Distributions
7 Sub-topics
Creating Basic Histograms
Controlling Bin Number and Width
Histogram Customization and Styling
Multiple Histograms with Transparency
Cumulative Histograms
2D Histograms
Density Plots and KDE Overlays
Box Plots and Violin Plots
1 Topics
Box Plots and Violin Plots
7 Sub-topics
Creating Box Plots
Understanding Box Plot Components
Horizontal Box Plots
Multiple Box Plots for Comparison
Customizing Box Plot Appearance
Violin Plots Basics
Box Plots vs Violin Plots
Statistical Plots and Analysis
1 Topics
Statistical Plots and Analysis
7 Sub-topics
Regression Lines
Confidence Intervals
Moving Averages
Statistical Annotations
Probability Plots
Quantile Plots
Residual Plots
03
Advanced Visualizations
3 Chapters · 3 Topics · 25 Sub-topics
Heatmaps and 2D Representations
1 Topics
Heatmaps and 2D Representations
8 Sub-topics
Creating Heatmaps with imshow()
Creating Heatmaps with pcolor() and pcolormesh()
Adding Color Bars and Labels
Custom Color Maps
Interpolation Methods
Contour Plots
Filled Contour Plots
Contour Labels and Customization
Subplots and Multiple Plots
1 Topics
Subplots and Multiple Plots
8 Sub-topics
Creating Subplots with plt.subplots()
Creating Subplots with plt.subplot()
Unequal Subplot Sizes with GridSpec
Nested Subplots
Sharing Axes Between Subplots
Tight Layout and Spacing
Subplot Labels and Titles
Creating Inset Plots
Advanced Plot Types
1 Topics
Advanced Plot Types
9 Sub-topics
Stream Plots
Quiver Plots (Vector Fields)
Polar Plots
Radar Charts (Spider Plots)
Stem Plots
Step Plots
Fill Between and Fill Betweenx
Error Bands
Broken Axis Plots
04
Data Integration
3 Chapters · 4 Topics · 24 Sub-topics
Dates and Times in Plots
1 Topics
Dates and Times in Plots
7 Sub-topics
Plotting Time Series Data
Date Formatting on Axes
Date Locators and Formatters
Time Zones Handling
Date Range Selection
Custom Date Formats
Multiple Time Scales
Integration with Other Libraries
1 Topics
Integration with Other Libraries
7 Sub-topics
Matplotlib with NumPy Arrays
Matplotlib with Pandas DataFrames
Plotting Directly from Pandas
Matplotlib with SciPy
Combining with Seaborn
Exporting to Plotly
Integration Best Practices
Real-World Applications and Best Practices
2 Topics
Real-World Applications and Best Practices - Part 1
5 Sub-topics
Scientific Publication Plots
Business Dashboard Components
Data Exploration Workflows
Report Automation
Common Mistakes to Avoid
Real-World Applications and Best Practices - Part 2
5 Sub-topics
Code Organization for Plotting
Documentation and Reproducibility
Testing Plot Functions
Accessibility and Universal Design
Future of Matplotlib and Alternatives

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