How to Create Scatter Plots in Python using Matplotlib?

how to plot a scatter plot in matplotlib

By Cheerful Cheetah on May 28, 2020

# Import matplotlib
import matplotlib.pyplot as plt

# Set plot space as inline for inline plots and qt for external plots
%matplotlib inline


# Set the figure size in inches
plt.figure(figsize=(10,6))

plt.scatter(x, y, label = "label_name" )

# Set x and y axes labels
plt.xlabel('X Values')
plt.ylabel('Y Values')

plt.title('Scatter Title')
plt.legend()
plt.show()

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scatter plot of a dataframe in python

By Famous Flamingo on Dec 17, 2020

>>> ax2 = df.plot.scatter(x='length',
...                       y='width',
...                       c='species',
...                       colormap='viridis')

Source: pandas.pydata.org

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scatter plot python

By febo101 on Oct 24, 2020

df.plot('x_axis', 'y_axis', kind='scatter')

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how to do scatter plot in pyplot

By Odd Okapi on Aug 29, 2020

import numpy as npimport matplotlib.pyplot as plt
# Create data
N = 500x = np.random.rand(N)
y = np.random.rand(N)
colors = (0,0,0)
area = np.pi*3
# Plot
plt.scatter(x, y, s=area, c=colors, alpha=0.5)
plt.title('Scatter plot pythonspot.com')
plt.xlabel('x')
plt.ylabel('y')
plt.show()

Source: pythonspot.com

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matplotlib scatter plot python

By Homely Hare on Sep 10, 2020

import numpy as np
np.random.seed(19680801)
import matplotlib.pyplot as plt


fig, ax = plt.subplots()
for color in ['tab:blue', 'tab:orange', 'tab:green']:
    n = 750
    x, y = np.random.rand(2, n)
    scale = 200.0 * np.random.rand(n)
    ax.scatter(x, y, c=color, s=scale, label=color,
               alpha=0.3, edgecolors='none')

ax.legend()
ax.grid(True)

plt.show()

Source: matplotlib.org

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plot scatter python

By Average Alligator on Mar 10, 2021

import numpy as np
np.random.seed(19680801)
import matplotlib.pyplot as plt


fig, ax = plt.subplots()
for color in ['tab:blue', 'tab:orange', 'tab:green']:
    n = 750
    x, y = np.random.rand(2, n)
    scale = 200.0 * np.random.rand(n)
    ax.scatter(x, y, c=color, s=scale, label=color,

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