Matplotlib - scatter()

https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.scatter.html

SCATTER PLOT

A scatter plot of y vs x with varying marker size and/or color. The 'plot' function will be faster for scatterplots where markers don't vary in size or color.

# matplotlib.pyplot.scatter(x, y, s=None, c=None, marker=None, cmap=None,
#     norm=None, vmin=None, vmax=None, alpha=None, linewidths=None,
#     verts=None, edgecolors=None, *, plotnonfinite=False, data=None, **kwargs)
#
# x, y : float or array-like
# s : the marker size in points^2, float or array-like
# c : the marker color, several possible values;
#     array-like or list of colors or color
# marker : the marker style (default: 'o')
# cmap : str or Colormap (default: 'viridis');
#     cmap is only used if c is an array of floats
# alpha : the alpha blending value, between 0 (transparent) and 1 (opaque)

x = np.arange(1, 6)
y = x**2      # a numpy function

# Doubling width of marker in scatter plot.
#area = [10*(4**n) for n in range(len(x))]   # [10, 40, 160, 640, 2560]

# Doubling area of marker in scatter plot.
area = [10*(2**n) for n in range(len(x))]   # [10, 20, 40, 80, 160]

plt.scatter(x, y, s=area)

PLOTTING WITH KEYWORD STRINGS

https://matplotlib.org/tutorials/introductory/pyplot.html

There are some instances where you have data in a format that lets you access particular variables with strings. For example, with numpy.recarray or pandas.DataFrame. Matplotlib allows you provide such an object with the data keyword argument.

n = 50
datadict = {'x': np.arange(n),
        'y': np.arange(n) + 10*np.random.randn(n),
        'c': np.random.randn(n),   # cmap will be used
        's': np.random.randint(36, 100, n)}   # 3 to 5 point radii

plt.scatter('x', 'y', c='c', s='s', data=datadict)

import pandas as pd

n = 100   # n random points in a unit square [0,1]x[0,1]
df = pd.DataFrame(np.random.rand(n,2), columns=['x', 'y'])

plt.scatter('x', 'y', data=df)
#plt.scatter(df['x'], df['y'])   # the same

EXAMPLES

# scatter1.py
import numpy as np
import matplotlib.pyplot as plt

# Fixing random state for reproducibility
np.random.seed(19680801)

n = 50
x = np.random.rand(n)
y = np.random.rand(n)

colors = np.random.rand(n)   # cmap will be used
#colors = np.random.choice(['r', 'g', 'b'], n) # color names

area = (30 * np.random.rand(n))**2   # 0 to 15 point radii

plt.scatter(x, y, s=area, c=colors, alpha=0.5)   # cmap='viridis'
#plt.scatter(x, y, s=area, c=colors, alpha=0.5, cmap='hot')
#plt.colorbar()   # optional
plt.show()

# scatter2.py
import numpy as np
import matplotlib.pyplot as plt

# Fixing random state for reproducibility
np.random.seed(19680801)

n = 100
x = np.random.rand(n)
y = np.random.rand(n)

#colors = [('r' if cond else 'g') for cond in np.logical_and(x > 0.5, y > 0.5)]
colors = np.where(np.logical_and(x > 0.5, y > 0.5) ,'r', 'g')

plt.scatter(x, y, c=colors)
plt.show()