Random lists plot with Scatter Plot

matplotlib.pyplot.sca(ax)
Set the current Axes instance to ax.
The current Figure is updated to the parent of ax.

Syntax

matplotlib.pyplot.scatter(x, y, s=20, c=’b’, marker=’o’, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, verts=None, hold=None, **kwargs)

Parameters

x, y : array_like, shape (n, ) Input data
s : scalar or array_like, shape (n, ), optional, default: 20 size in points^2.
c : color or sequence of color, optional, default c can be a single color format string, or a sequence of color specifications of length N, or a sequence of N numbers to be mapped to colors using the cmap and norm specified via kwargs (see below). Note that c should not be a single numeric RGB or RGBA sequence because that is indistinguishable from an array of values to be colormapped. c can be a 2-D array in which the rows are RGB or RGBA, however.
marker : MarkerStyle, optional, default: ‘o’
cmap : Colormap, optional, default: None A Colormap instance or registered name. cmap is only used if c is an array of floats. If None, defaults to rc image.cmap.
norm : Normalize, optional, default: None A Normalize instance is used to scale luminance data to 0, 1. norm is only used if c is an array of floats. If None, use the default normalize().
vmin, vmax : scalar, optional, default: None vmin and vmax are used in conjunction with norm to normalize luminance data. If either are None, the min and max of the color array is used. Note if you pass a norm instance, your settings for vmin and vmax will be ignored.
alpha : scalar, optional, default: None The alpha blending value, between 0 (transparent) and 1 (opaque)
linewidths : scalar or array_like, optional, default: None If None, defaults to (lines.linewidth,). Note that this is a tuple, and if you set the linewidths argument you must set it as a sequence of floats, as required by RegularPolyCollection.
Returns: paths : PathCollection, Other Parameters: kwargs : Collection properties

Example

import matplotlib.pyplot as plt
import numpy

# Generating random lists
abc1 = numpy.random.randint(100,size=100)
abc2 = numpy.random.randint(100,size=100)

# Plotting Figure
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(abc1.tolist(), abc2.tolist())
plt.show()

Output

1