❮ Previous Next ❯

Heatmap

  • This module teaches how to create heatmaps in Seaborn. You will learn to visualize correlation matrices, apply color mapping, add annotations, and use custom color maps to enhance data analysis in Python.

  • What is a Heatmap?

    Theory

    A Heatmap is a graphical representation of data where:

    ✔ Values are shown using colors
    ✔ Darker/Lighter colors represent magnitude
    ✔ Used for matrix-type data

    Most common use:
     Correlation Matrix Visualization


    Correlation Matrix

    What is Correlation?

    Correlation shows:

    • Relationship between two numerical variables

    • Value range: -1 to +1

    Value

    Meaning

    +1

    Perfect positive correlation

    -1

    Perfect negative correlation

    0

    No correlation

    Example — Correlation Matrix

Correlation Matrix Heatmap

This visualization uses Seaborn’s heatmap to display the correlation between numerical variables in the dataset. 

import seaborn as sns
import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

correlation = tips.corr(numeric_only=True)

sns.heatmap(correlation)
plt.title("Correlation Matrix Heatmap")
plt.show()
Lesson image

  • Output Explanation

    • Rows & Columns → Numerical variables

    • Each cell → Correlation value

    • Dark color → Strong relationship

    • Light color → Weak relationship

    Example Insight:

    • total_bill & tip → Strong positive correlation

    • size & tip → Moderate correlation


    Color Mapping

    What is Color Mapping?

    Heatmap uses color intensity to represent data values.

    Default:

    • Dark → Higher value

    • Light → Lower value

    Add Color Map

Correlation Matrix Heatmap with Color Map

This visualization uses Seaborn’s heatmap with a color map to display correlations between numerical variables. 

sns.heatmap(correlation, cmap="coolwarm")
plt.show()

  • Popular color maps:

    • coolwarm

    • viridis

    • plasma

    • YlGnBu

    • Blues

    Center Parameter

    sns.heatmap(correlation, cmap="coolwarm", center=0)

    Centering at 0 helps highlight:

    • Positive (red side)

    • Negative (blue side)

    Very useful for correlation matrix.


    Annotations

    What are Annotations?

    Annotations display actual values inside each cell.

    Add Annotations

Correlation Heatmap with Values (Annotations)

This visualization uses Seaborn’s heatmap with annotations to display correlation values between numerical variables. 

sns.heatmap(correlation,
           cmap="coolwarm",
           annot=True)
plt.title("Correlation Heatmap with Values")
plt.show()
Lesson image

  • Format Values

Formatted Correlation Heatmap

This visualization uses Seaborn’s heatmap with annotated correlation values formatted to two decimal places. 

sns.heatmap(correlation,
           cmap="coolwarm",
           annot=True,
           fmt=".2f")
Lesson image

  • .2f → Shows 2 decimal places.


    Custom Color Maps

    Change Color Theme

Correlation Heatmap with Custom Color Theme

This visualization uses Seaborn’s heatmap with a custom color palette to display correlations between numerical variables. 

sns.heatmap(correlation,
           cmap="YlGnBu",
           annot=True)
Lesson image

  • Reverse Color Map

Correlation Heatmap with Reversed Color Map

This visualization uses Seaborn’s heatmap with a reversed color palette to display correlations between numerical variables. 

sns.heatmap(correlation,
           cmap="coolwarm_r",
           annot=True)
Lesson image

  • _r → Reverses color scheme.

    Remove Color Bar

Correlation Heatmap without Color Bar

This visualization uses Seaborn’s heatmap to display correlations between numerical variables without showing the color bar. 

sns.heatmap(correlation,
           cmap="coolwarm",
           annot=True,
           cbar=False)
Lesson image

  • Add Line Separators

Correlation Heatmap with Line Separators

This visualization uses Seaborn’s heatmap to display correlations between numerical variables with grid lines between cells. 

sns.heatmap(correlation,
           cmap="coolwarm",
           annot=True,
           linewidths=1)
Lesson image
❮ Previous Next ❯