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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.
fig, axs = plt. subplots (3, sharex = True, sharey = True) fig. suptitle ('Sharing both axes') axs [0]. plot (x, y ** 2) axs [1]. plot (x, 0.3 * y, 'o') axs [2]. plot (x, y, '+') For subplots that are sharing axes one set of tick labels is enough.
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.
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.
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 )
matplotlib.pyplot. subplots (nrows = 1, ncols = 1, *, sharex = False, sharey = False, squeeze = True, width_ratios = None, height_ratios = None, subplot_kw = None, gridspec_kw = None, ** fig_kw) [source] # Create a figure and a set of subplots.
fig = plt. figure fig. subplots_adjust (hspace = 0.4, wspace = 0.4) for i in range (1, 7): ax = fig. add_subplot (2, 3, i) ax. text (0.5, 0.5, str ((2, 3, i)), fontsize = 18, ha = 'center') We've used the hspace and wspace arguments of plt.subplots_adjust , which specify the spacing along the height and width of the figure, in units of the ...
