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Distribution Analysis with Seaborn

Visualize distributions like a pro - Master Seaborn's statistical plotting power!

4.4
Intermediate

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Distribution Analysis with Seaborn
4 Modules

Course Curriculum

4 Modules · 10 Chapters · 10 Topics · 67 Sub-topics

01
Foundation
2 Chapters · 2 Topics · 12 Sub-topics
Introduction to Seaborn
1 Topics
Getting Started with Seaborn
6 Sub-topics
What is Seaborn and Why Use It
Seaborn vs Matplotlib
Installing Seaborn
Importing Seaborn and Initial Setup
Understanding Seaborn's Philosophy
Overview of Seaborn Plot Types
First Steps with Seaborn
1 Topics
Creating Your First Plots
6 Sub-topics
Loading Built-in Datasets
Creating Your First Scatter Plot
Creating Your First Line Plot
Understanding Figure and Axes
Basic Plot Customization
Saving Your First Plot
02
Distribution Techniques
3 Chapters · 3 Topics · 20 Sub-topics
Seaborn Plot Interface
1 Topics
Understanding Plot Functions
6 Sub-topics
Understanding Figure-Level vs Axes-Level Functions
Using relplot() - The Relational Plot Function
Using displot() - The Distribution Plot Function
Using catplot() - The Categorical Plot Function
When to Use Each Interface Type
Converting Between Interface Types
Distribution Plots
1 Topics
Visualizing Data Distributions
7 Sub-topics
Histograms with histplot()
Kernel Density Estimation with kdeplot()
Empirical Cumulative Distribution with ecdfplot()
Rug Plots for Data Density
Combining Multiple Distribution Plots
Bivariate Distribution Plots
Customizing Bins and Bandwidth
Regression Plots
1 Topics
Statistical Regression Visualization
7 Sub-topics
Linear Regression with regplot()
Advanced Regression with lmplot()
Adding Confidence Intervals
Polynomial Regression Visualization
LOWESS Smoothing
Residual Plots with residplot()
Logistic Regression Visualization
03
Advanced Analysis
3 Chapters · 3 Topics · 21 Sub-topics
Multi-Plot Grids Part 2
1 Topics
Advanced Grid Visualizations
7 Sub-topics
PairGrid for Pairwise Relationships
Creating Pair Plots with pairplot()
Customizing Diagonal and Off-Diagonal Plots
JointGrid for Bivariate Analysis
Creating Joint Plots with jointplot()
Adding Marginal Distributions
Combining Different Plot Types in Grids
Statistical Estimation in Plots
1 Topics
Statistical Analysis in Visualization
7 Sub-topics
Understanding Estimators in Seaborn
Confidence Intervals and Error Bars
Using Different Statistical Functions
Bootstrapping in Seaborn
Controlling CI with ci Parameter
Seed and n_boot for Reproducibility
Aggregation Functions (mean, median, etc.)
Advanced Statistical Visualizations
1 Topics
Statistical Analysis Plots
7 Sub-topics
Probability Plots
Quantile-Quantile (Q-Q) Plots
Survival Analysis Plots
Effect Size Visualization
Statistical Test Result Plots
Distribution Comparison Techniques
Hypothesis Testing Visualization
04
Professional Development
2 Chapters · 2 Topics · 14 Sub-topics
Working with DataFrames
1 Topics
Data Preparation for Seaborn
7 Sub-topics
Long-Form vs Wide-Form Data
Preparing Data for Seaborn
Using the data Parameter
Column-Based Plotting with x and y
Handling Missing Values
Using Index as Plot Variable
Melting and Reshaping Data for Seaborn
Best Practices and Optimization
1 Topics
Professional Visualization Development
7 Sub-topics
Code Organization for Visualization
Reusable Plotting Functions
Plot Validation and Testing
Performance Optimization Tips
Memory Management
Documentation and Commenting
Version Control for Visualizations

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