使用 import numpy as np import matplotlib.pyplot as plt plt.rcParams['legend.fontsize'] = 10 fig = plt.figure() ax = fig.gca(projection='3d') # Prepare arrays x, y, z theta = np.linspace(-4 * np.pi, 4 * np.pi, 100) z = np.linspace(-2, 2, 100) r = z**2 + 1 x ...
# Change the legend frame facecolour, edgecolour, and transparency colour_legend = ax.legend(*scatter.legend_elements(**kw), title="Earnings [USD]", reverse=True, markerscale=1.5, facecolor='#EEEEEE', labelcolor='#555555', edgecolor='#757575', framealpha=0.5) # Set the legend title c...
plt.legend() In the above-represented 3D graph, a line graph is illustrated in a 3-dimensional manner. We make use of a special library to plot 3D graphs which is given in the following syntax. Syntax for plotting 3D graphs: import matplotlib.pyplot as plt from mpl_toolkits.mplot3d impo...
plt.title('Sin and Cos Waves') # Add a graph title. plt.show() To add legends to our graph, inside the plot() function we add the named argument ‘label’ and assign it what we want the line to be labelled with. We then call the legend() function and a legend will be placed ...
Optionally, you could add ax.legend() to display the labels for each wave. In this example, we've plotted the values created by applying a sine and cosine function to the sequence generated using NumPy's arange() Function. The sequence starts at 0 and ends at 10 with a step of 0.1....