Introduction
This tutorial will guide you through creating an annotated scatter plot with a text arrow using Matplotlib in Python.
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Import libraries and generate random data
First, we need to import the necessary libraries and generate some random data for our scatter plot.
import matplotlib.pyplot as plt
import numpy as np
## Fixing random state for reproducibility
np.random.seed(19680801)
fig, ax = plt.subplots(figsize=(5, 5))
ax.set_aspect(1)
x1 = -1 + np.random.randn(100)
y1 = -1 + np.random.randn(100)
x2 = 1. + np.random.randn(100)
y2 = 1. + np.random.randn(100)
ax.scatter(x1, y1, color="r")
ax.scatter(x2, y2, color="g")
Add text annotations to the plot
Next, we'll add text annotations to the plot using the ax.text() function. We'll create two annotations, one for "Sample A" and one for "Sample B".
bbox_props = dict(boxstyle="round", fc="w", ec="0.5", alpha=0.9)
ax.text(-2, -2, "Sample A", ha="center", va="center", size=20,
bbox=bbox_props)
ax.text(2, 2, "Sample B", ha="center", va="center", size=20,
bbox=bbox_props)
Add a text arrow to indicate direction
To indicate the direction of the data, we'll add a text arrow using the ax.text() function and the bbox parameter with the boxstyle set to "rarrow".
bbox_props = dict(boxstyle="rarrow", fc=(0.8, 0.9, 0.9), ec="b", lw=2)
t = ax.text(0, 0, "Direction", ha="center", va="center", rotation=45,
size=15,
bbox=bbox_props)
bb = t.get_bbox_patch()
bb.set_boxstyle("rarrow", pad=0.6)
Set plot limits and show the plot
Finally, we'll set the x and y limits of the plot and show the plot using the ax.set_xlim(), ax.set_ylim(), and plt.show() functions.
ax.set_xlim(-4, 4)
ax.set_ylim(-4, 4)
plt.show()
Summary
In this tutorial, we learned how to create an annotated scatter plot with a text arrow using Matplotlib in Python. We used the ax.text() function to add annotations and a text arrow to the plot, and the ax.set_xlim(), ax.set_ylim(), and plt.show() functions to set plot limits and show the plot.