How to create a scatter plot with markers differentiated by category in a Pandas DataFrame?

How to create a scatter plot by category using Pandas DataFrame

Question:

How can I efficiently create a scatter plot using a Pandas DataFrame, where the markers are dictated by a third column in the DataFrame?

Answer:

Using matplotlib.pyplot.scatter() to differentiate markers by category can be inefficient. Instead, consider using matplotlib.pyplot.plot() for discrete categories:

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

# Generate Data
num = 20
x, y = np.random.random((2, num))
labels = np.random.choice(['a', 'b', 'c'], num)
df = pd.DataFrame(dict(x=x, y=y, label=labels))

# Group by labels
groups = df.groupby('label')

# Plot
fig, ax = plt.subplots()
ax.margins(0.05)  # Optional padding

# Use different markers and colors for each group
for name, group in groups:
    ax.plot(group.x, group.y, marker='o', linestyle='', ms=12, label=name)
ax.legend()

# Specify custom colors and styles
plt.rcParams.update(pd.tools.plotting.mpl_stylesheet)
colors = pd.tools.plotting._get_standard_colors(len(groups), color_type='random')
ax.set_color_cycle(colors)
ax.legend(numpoints=1, loc='upper left')

plt.show()

This code generates a scatter plot with markers color-coded by category.

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