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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.
pyplot.subplots creates a figure and a grid of subplots with a single call, while providing reasonable control over how the individual plots are created. For more advanced use cases you can use GridSpec for a more general subplot layout or Figure.add_subplot for adding subplots at arbitrary locations within the figure.
There are three main options in matplotlib to make separate plots within a figure: subplot: access the axes array and add subplots. gridspec: control the geometric properties of the underlying figure (demo) subplots: wraps the first two in a convenient api (demo)
22 lip 2020 · Subplots mean groups of axes that can exist in a single matplotlib figure. subplots() function in the matplotlib library, helps in creating multiple layouts of subplots. It provides control over all the individual plots that are created.
Try this: fig, ax = plt.subplots (10, 10) where ax will contain one hundred axis in a list (of lists). It is a really handy function, from the docs: Definition: plt.subplots (nrows=1, ncols=1, sharex=False, sharey=False, squeeze=True, subplot_kw=None, **fig_kw) Create a figure with a set of subplots already made.
plt.subplot(1, 2, 2) #the figure has 1 row, 2 columns, and this plot is the second plot. So, if we want a figure with 2 rows an 1 column (meaning that the two plots will be displayed on top of each other instead of side-by-side), we can write the syntax like this:
Subplots can also be generated one at a time using subplot (): plt.subplot(2,1,1)plt.plot(x1,y1,'o-')plt.title('A tale of 2 subplots')plt.ylabel('Damped oscillation')plt.subplot(2,1,2)plt.plot(x2,y2,'.-')plt.xlabel('time (s)')plt.ylabel('Undamped')plt.show() Total running time of the script: (0 minutes 1.022 seconds)
