如何在 matplotlib 中绘制单个点

Question

I'd like to plot a single point on my graph, but it seems like they all need to plot as either a list or equation.

I need to plot like ax.plot(x, y) and a dot will be appeared at my x , y coordinates on my graph.

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import host_subplot
import mpl_toolkits.axisartist as AA
import numpy
fig = plt.figure()
plt.xlabel('Width')
plt.ylabel('Height')
ax = fig.gca()
ax.plot(105, 200)
plt.grid()
plt.show()

Answer 1

这对我有用：

plt.plot(105,200,'ro') 

Answer 2

• matplotlib.pyplot.plot and matplotlib.axes.Axes.plot plots y versus x as lines and/or markers.
• ax.plot(105, 200) attempts to draw a line, but two points are required for a line
  • plt.plot([105, 110], [200, 210])
• A third positional argument consists of line type, color, and/or marker
  • 'o' can be used to only draw a marker.
    • Specifying marker='o' does not work the same as the positional argument.
  • 'ro' specifies color and marker, respectively
  • '-o' or '-ro' will draw a line and marker if two or more x and y values are provided.
• matplotlib.pyplot.scatter and matplotlib.axes.Axes.scatter can also be used to add single or multiple points
• Tested in python 3.10 , matplotlib 3.5.1 , seaborn 0.11.2

import matplotlib.pyplot as plt

fig, ax = plt.subplots(3, 1, figsize=(8, 10))

# single point
ax[0].plot(105, 110, '-ro', label='line & marker - no line because only 1 point')
ax[0].plot(200, 210, 'go', label='marker only')  # use this to plot a single point
ax[0].plot(160, 160, label='no marker - default line - not displayed- like OP')
ax[0].set(title='Markers - 1 point')
ax[0].legend()

# two points
ax[1].plot([105, 110], [200, 210], '-ro', label='line & marker')
ax[1].plot([105, 110], [195, 205], 'go', label='marker only')
ax[1].plot([105, 110], [190, 200], label='no marker - default line')
ax[1].set(title='Line & Markers - 2 points')
ax[1].legend()

# scatter plot
ax[2].scatter(x=105, y=110, c='r', label='One Point')  # use this to plot a single point
ax[2].scatter(x=[80, 85, 90], y=[85, 90, 95], c='g', label='Multiple Points')
ax[2].set(title='Single or Multiple Points with using .scatter')
ax[2].legend()

fig.tight_layout()

Seaborn

• seaborn is a high-level api for matplotlib , and offers additional options for plotting single points.
• sns.lineplot and sns.scatterplot are axes-level plots.
  • sns.lineplot has keyword arguments, which are passed to matplotlib.axes.Axes.plot
  • sns.scatterplot has keyword arguments, which are passed to matplotlib.axes.Axes.scatter
• sns.relplot is a figure-level plot, with a kind= parameter.
  • kind='line' passes to sns.lineplot
  • kind='scatter' passes to sns.scatterplot
• x= and y= must be passed as a vector in the following cases.

axes-level plots

sns.lineplot(x=[1], y=[1], marker='o', markersize=10, color='r')

sns.scatterplot(x=[1], y=[1], s=100, color='r')

figure-level plots

sns.relplot(kind='line', x=[1], y=[1], marker='o', markersize=10, color='r')

sns.relplot(kind='scatter', x=[1], y=[1], s=100, color='r')

Answer 3

here is an example on how to do it with numpy on a 2d plot

import numpy as np
import matplotlib.pyplot as plt

# column 1 Age
# Column 2 Weight
x = np.array([[10, 40],
              [11, 35],
              [12, 40],
              [13, 41],
              [13, 70],
              [15, 60],
              [19, 64],
              [15, 60],
              [20, 80],
              [40, 100],
              [56, 85]])

for i in x:
    plt.plot(i[0], i[1], 'ro')
plt.xlabel("Age")
plt.ylabel("Weight")
plt.show()