Scatter plot in python with labels
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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
The following also demonstrates how transparency of the markers can be adjusted by giving 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 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
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 show labels on a scatter plot in Python?To label the scatter plot points in Matplotlib, we can use the matplotlib. pyplot. annotate() function, which adds a string at the specified position. Similarly, we can also use matplotlib.
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 add labels to graphs in Python?With Pyplot, you can use the xlabel() and ylabel() functions to set a label for the x- and y-axis.. Add labels to the x- and y-axis: import numpy as np. ... . Add a plot title and labels for the x- and y-axis: import numpy as np. ... . Set font properties for the title and labels: import numpy as np. ... . Position the title to the left:. How do I make a scatter plot in Python?Machine Learning - Scatter Plot. Example. Use the scatter() method to draw a scatter plot diagram: import matplotlib.pyplot as plt. x = [5,7,8,7,2,17,2,9,4,11,12,9,6] y = [99,86,87,88,111,86,103,87,94,78,77,85,86] ... . Example. A scatter plot with 1000 dots: import numpy. import matplotlib.pyplot as plt. ... . ❮ Previous Next ❯. |
