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This is most useful for two subplots (e.g.: fig, (ax1, ax2) = plt.subplots(1, 2) or fig, (ax1, ax2) = plt.subplots(2, 1)). For more subplots, it's more efficient to flatten and iterate through the array of axes.
You can use sharex or sharey to align the horizontal or vertical axis. fig,(ax1,ax2)=plt.subplots(2,sharex=True)fig.suptitle('Aligning x-axis using sharex')ax1.plot(x,y)ax2.plot(x+1,-y)
22 lip 2020 · # make subplots plt.subplot (grid [0, 0]) plt.subplot (grid [0, 1:]) plt.subplot (grid [1, :2]) plt.subplot (grid [1, 2]); This can be used in a wide variety of cases for plotting multiple plots in matplotlib.
plt.GridSpec: More Complicated Arrangements¶ To go beyond a regular grid to subplots that span multiple rows and columns, plt.GridSpec() is the best tool. The plt.GridSpec() object does not create a plot by itself; it is simply a convenient interface that is recognized by the plt.subplot() command. For example, a gridspec for a grid of two ...
Simple demo with multiple subplots. For more options, see Creating multiple subplots using plt.subplots . import matplotlib.pyplot as plt import numpy as np # Create some fake data. x1 = np . linspace ( 0.0 , 5.0 ) y1 = np . cos ( 2 * np . pi * x1 ) * np . exp ( - x1 ) x2 = np . linspace ( 0.0 , 2.0 ) y2 = np . cos ( 2 * np . pi * x2 )
Draw 2 plots on top of each other: import matplotlib.pyplot as plt. import numpy as np. #plot 1: x = np.array ( [0, 1, 2, 3]) y = np.array ( [3, 8, 1, 10]) plt.subplot (2, 1, 1) plt.plot (x,y) #plot 2:
7 wrz 2012 · Instead of counting your own number of rows and columns, I found it easier to create the subplots using plt.subplots first, then iterate through the axes object to add plots.
