Matplot library using plot the correlation matrix in Python | S-Logix

List of Topics:

How to Plot the Correlation Matrix Using Matplotlib Library

Correlation Matrix Heatmap

Condition for Plotting the Correlation Matrix Using Matplotlib Library

Description:
A correlation matrix is a table that shows the correlation coefficients between many variables. It is a useful tool for identifying relationships between different variables in a dataset. The correlation matrix is often plotted as a heatmap to visualize the strength of correlations.

Step-by-Step Process

Import the Required Libraries:
Use Pandas for handling the dataset, Matplotlib for basic plotting, and Seaborn for enhanced heatmap visualization.
Prepare the Data:
Load or create the dataset and ensure it's in a numerical format for correlation analysis.
Compute the Correlation Matrix:
Use the .corr() method from Pandas to compute the correlation matrix of the dataset.
Plot the Correlation Matrix:
Use Matplotlib to generate a heatmap of the correlation matrix.

Sample Source Code

import pandas as pd

import matplotlib.pyplot as plt
import seaborn as sns

data = {
"Height": [5.5, 6.0, 5.7, 5.8, 6.2],
"Weight": [150, 160, 155, 158, 170],
"Age": [25, 30, 28, 35, 40]
}
df = pd.DataFrame(data)

# Calculate the correlation matrix
correlation_matrix = df.corr()

plt.figure(figsize=(8, 6))
sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt='.2f', linewidths=0.5)

plt.title('Correlation Matrix Heatmap')
plt.show()

Screenshots

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