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Seaborn — Course Map

Map of all 60 chapters in the Seaborn course.

Course map

Part 1: Foundations

  1. Chapter 1: What Seaborn Is
  2. Chapter 2: Installing and Importing Seaborn
  3. Chapter 3: Seaborn and Matplotlib
  4. Chapter 4: Loading a DataFrame
  5. Chapter 5: Themes
  6. Chapter 6: Styles
  7. Chapter 7: Contexts
  8. Chapter 8: Color Palettes Concepts
  9. Chapter 9: Setting a Theme
  10. Chapter 10: Figure-Level vs Axes-Level Functions

Part 2: Core Operations

  1. Chapter 11: Scatterplot
  2. Chapter 12: Lineplot
  3. Chapter 13: Relplot
  4. Chapter 14: Hue
  5. Chapter 15: Style Mapping
  6. Chapter 16: Size Mapping
  7. Chapter 17: Categorical Data
  8. Chapter 18: Stripplot
  9. Chapter 19: Swarmplot Concepts
  10. Chapter 20: Boxplot

Part 3: Data Analysis

  1. Chapter 21: Violinplot
  2. Chapter 22: Boxenplot Concepts
  3. Chapter 23: Barplot
  4. Chapter 24: Countplot
  5. Chapter 25: Pointplot
  6. Chapter 26: Catplot
  7. Chapter 27: Histplot
  8. Chapter 28: KDE Plot Concepts
  9. Chapter 29: ECDF Plot Concepts
  10. Chapter 30: Displot

Part 4: Advanced Techniques

  1. Chapter 31: Multiple Distributions
  2. Chapter 32: Bivariate Distributions
  3. Chapter 33: Jointplot
  4. Chapter 34: Pairplot
  5. Chapter 35: PairGrid Concepts
  6. Chapter 36: Regression Plots
  7. Chapter 37: Regplot
  8. Chapter 38: Lmplot
  9. Chapter 39: Residual Plot Concepts
  10. Chapter 40: Confidence Intervals Concepts

Part 5: AI Workflows

  1. Chapter 41: Heatmaps
  2. Chapter 42: Correlation Heatmaps
  3. Chapter 43: Annotations in Heatmaps
  4. Chapter 44: Clustermap Concepts
  5. Chapter 45: FacetGrid
  6. Chapter 46: Row and Column Facets
  7. Chapter 47: Facet Titles
  8. Chapter 48: Ordering Categories
  9. Chapter 49: Rotating Labels
  10. Chapter 50: Handling Missing Data

Part 6: Projects and Review

  1. Chapter 51: Visualizing Class Balance
  2. Chapter 52: Visualizing Feature Distributions
  3. Chapter 53: Visualizing Outliers
  4. Chapter 54: Visualizing Correlations
  5. Chapter 55: Visualizing Model Errors
  6. Chapter 56: Comparing Groups
  7. Chapter 57: Mini Project: Exploratory Data Analysis
  8. Chapter 58: Mini Project: Feature Relationship Report
  9. Chapter 59: Mini Project: Classification Data Review
  10. Chapter 60: Capstone: AI Statistical Visualization Dashboard