Python scatter plot with labels

Question

I would love to add that you can even use arrows /text boxes to annotate the labels. Here is what I mean:

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Automated legend creation#
How do you add labels to a scatter plot in Python?
How do you add a label to a scatter plot?
How do you make a legend on a scatter plot?
How do you make a scatter plot in Python?

import random
import matplotlib.pyplot as plt


y = [2.56422, 3.77284, 3.52623, 3.51468, 3.02199]
z = [0.15, 0.3, 0.45, 0.6, 0.75]
n = [58, 651, 393, 203, 123]

fig, ax = plt.subplots()
ax.scatter(z, y)

ax.annotate(n[0], (z[0], y[0]), xytext=(z[0]+0.05, y[0]+0.3), 
    arrowprops=dict(facecolor='red', shrink=0.05))

ax.annotate(n[1], (z[1], y[1]), xytext=(z[1]-0.05, y[1]-0.3), 
    arrowprops = dict(  arrowstyle="->",
                        connectionstyle="angle3,angleA=0,angleB=-90"))

ax.annotate(n[2], (z[2], y[2]), xytext=(z[2]-0.05, y[2]-0.3), 
    arrowprops = dict(arrowstyle="wedge,tail_width=0.5", alpha=0.1))

ax.annotate(n[3], (z[3], y[3]), xytext=(z[3]+0.05, y[3]-0.2), 
    arrowprops = dict(arrowstyle="fancy"))

ax.annotate(n[4], (z[4], y[4]), xytext=(z[4]-0.1, y[4]-0.2),
    bbox=dict(boxstyle="round", alpha=0.1), 
    arrowprops = dict(arrowstyle="simple"))

plt.show()

Which will generate the following graph:

Note

Click here to download the full example code

To create a scatter plot with a legend one may use a loop and create one scatter plot per item to appear in the legend and set the label accordingly.

The following also demonstrates how transparency of the markers can be adjusted by giving alpha a value between 0 and 1.

import numpy as np
import matplotlib.pyplot as plt

np.random.seed(19680801)


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()

Automated legend creation#

Another option for creating a legend for a scatter is to use the PathCollection.legend_elements method. It will automatically try to determine a useful number of legend entries to be shown and return a tuple of handles and labels. Those can be passed to the call to legend.

N = 45
x, y = np.random.rand(2, N)
c = np.random.randint(1, 5, size=N)
s = np.random.randint(10, 220, size=N)

fig, ax = plt.subplots()

scatter = ax.scatter(x, y, c=c, s=s)

# produce a legend with the unique colors from the scatter
legend1 = ax.legend(*scatter.legend_elements(),
                    loc="lower left", title="Classes")
ax.add_artist(legend1)

# produce a legend with a cross section of sizes from the scatter
handles, labels = scatter.legend_elements(prop="sizes", alpha=0.6)
legend2 = ax.legend(handles, labels, loc="upper right", title="Sizes")

plt.show()

Further arguments to the PathCollection.legend_elements method can be used to steer how many legend entries are to be created and how they should be labeled. The following shows how to use some of them.

volume = np.random.rayleigh(27, size=40)
amount = np.random.poisson(10, size=40)
ranking = np.random.normal(size=40)
price = np.random.uniform(1, 10, size=40)

fig, ax = plt.subplots()

# Because the price is much too small when being provided as size for ``s``,
# we normalize it to some useful point sizes, s=0.3*(price*3)**2
scatter = ax.scatter(volume, amount, c=ranking, s=0.3*(price*3)**2,
                     vmin=-3, vmax=3, cmap="Spectral")

# Produce a legend for the ranking (colors). Even though there are 40 different
# rankings, we only want to show 5 of them in the legend.
legend1 = ax.legend(*scatter.legend_elements(num=5),
                    loc="upper left", title="Ranking")
ax.add_artist(legend1)

# Produce a legend for the price (sizes). Because we want to show the prices
# in dollars, we use the *func* argument to supply the inverse of the function
# used to calculate the sizes from above. The *fmt* ensures to show the price
# in dollars. Note how we target at 5 elements here, but obtain only 4 in the
# created legend due to the automatic round prices that are chosen for us.
kw = dict(prop="sizes", num=5, color=scatter.cmap(0.7), fmt="$ {x:.2f}",
          func=lambda s: np.sqrt(s/.3)/3)
legend2 = ax.legend(*scatter.legend_elements(**kw),
                    loc="lower right", title="Price")

plt.show()

Total running time of the script: ( 0 minutes 1.840 seconds)

Gallery generated by Sphinx-Gallery

How do you add labels to a scatter plot in Python?

text() function to add the text labels to the scatterplot points..

Add Label to Scatter Plot Points Using the matplotlib. pyplot. annotate() Function..

Add Label to Scatter Plot Points Using the matplotlib. pyplot. text() Function..

Related Article - Matplotlib Scatter Plot..

How do you add a label to a scatter plot?

Do add the data labels to the scatter chart, select the chart, click on the plus icon on the right, and then check the data labels option. This will add the data labels that will show the Y-axis value for each data point in the scatter graph.

How do you make a legend on a scatter plot?

To create a scatter plot with a legend one may use a loop and create one scatter plot per item to appear in the legend and set the label accordingly. The following also demonstrates how transparency of the markers can be adjusted by giving alpha a value between 0 and 1.