How to remove text before a graph in Python using Matplotlib

To remove text before a graph in Matplotlib using Python, you can use the following steps:

Step 1: Import necessary libraries
First, make sure you have Matplotlib and sklearn installed on your system. If not, you can install them using pip:

pip install matplotlib
pip install scikit-learn

Next, import the required libraries in your Python script:

import matplotlib.pyplot as plt
from sklearn.datasets import make_classification

Step 2: Create a sample dataset
To create a sample dataset for plotting a graph, you can use the make_classification function from sklearn. This function generates a random n-class classification problem.

X, y = make_classification(n_samples=100, n_features=2, n_informative=2, n_redundant=0, n_clusters_per_class=1)

Step 3: Plot the graph
Next, plot the graph using Matplotlib. You can use the scatter function to create a scatter plot of the dataset.

plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Paired)
plt.xlabel('Feature 1')
plt.ylabel('Feature 2')
plt.title('Sample Dataset')
plt.show()

This code will generate a scatter plot of the sample dataset with the text "Feature 1" and "Feature 2" on the x and y axes, respectively.

Step 4: Remove text before the graph
To remove the text that appears before the graph, you can add the following line of code before plotting the graph:

plt.figure().suptitle('')

This will remove the text that appears before the graph.

Step 5: Put it all together
Here is the complete code that creates a sample dataset, plots the graph, and removes the text before the graph:

import matplotlib.pyplot as plt
from sklearn.datasets import make_classification

X, y = make_classification(n_samples=100, n_features=2, n_informative=2, n_redundant=0, n_clusters_per_class=1)

plt.figure().suptitle('')
plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Paired)
plt.xlabel('Feature 1')
plt.ylabel('Feature 2')
plt.title('Sample Dataset')
plt.show()

By following these steps, you can easily create a graph using Matplotlib in Python and remove any text that appears before the graph.