How to make an axes occupy multiple subplots with pyplot (Python)

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I would like to have three plots in single figure. The figure should have a subplot layout of two by two, where the first plot should occupy the first two subplot cells (i.e. the whole first row of plot cells) and the other plots should be positioned underneath the first one in cells 3 and 4. I know that matlab allows this by using the subplot command like so

subplot(2,2,[1,2]) % the plot will span subplots 1 and 2

Is it also possible in pyplot to have a single axes occupy more than one subplot? The docstring of pyplot.subplot doesn't talk about it.

Anyone got an easy solution? Thanks in advance

You can simply do:

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(0, 7, 0.01)

plt.subplot(2, 1, 1)
plt.plot(x, np.sin(x))

plt.subplot(2, 2, 3)
plt.plot(x, np.cos(x))

plt.subplot(2, 2, 4)
plt.plot(x, np.sin(x)*np.cos(x))

i.e., the first plot is really a plot in the upper half (the figure is only divided into 2*1 = 2 cells), and the following two smaller plots are done in a 2*2=4 cell grid. The third argument to subplot() is the positon of the plot inside the grid: for example in the second subplot (subplot(2, 2, 3)), the axes will go to the third section of the 2*2 matrix i.e, to the bottom-left corner.

Using Gridspec to make multi-column/row subplot layouts, import matplotlib.pyplot as plt from matplotlib.gridspec import GridSpec def format_axes(fig): for i, ax in enumerate(fig.axes): ax.text(0.5, 0.5,� Thus, if the ranges are different the tick values of the subplots do not align. fig, (ax1, ax2) = plt.subplots(2) fig.suptitle('Axes values are scaled individually by default') ax1.plot(x, y) ax2.plot(x + 1, -y) You can use sharex or sharey to align the horizontal or vertical axis.

To have multiple subplots with an axis occupy, you can simply do:

from matplotlib import pyplot as plt
import numpy as np

b=np.linspace(-np.pi, np.pi, 100)




plt.plot(b, a1)

plt.plot(b, a2)

plt.plot(b, a3)

Another way is

plt.plot(b, a1)

plt.plot(b, a2)

plt.plot(b, a3)

Combining two subplots using subplots and GridSpec — Matplotlib , We can get the GridSpec from the axes and then remove the covered axes and fill the gap with a new bigger axes. Here we create a layout with� fig, (ax1, ax2) = plt.subplots(2) fig.suptitle('Vertically stacked subplots') ax1.plot(x, y) ax2.plot(x, -y) Out: [<matplotlib.lines.Line2D object at 0x7f0a07bde5b0>] To obtain side-by-side subplots, pass parameters 1, 2 for one row and two columns.

For finer-grained control you might want to use the subplot2grid module of matplotlib.pyplot.

Multiple Subplots, To this end, Matplotlib has the concept of subplots: groups of smaller axes that that Matplotlib has several convenience routines that make them easy to create. Dict with keywords passed to the add_subplot call used to create each subplot. gridspec_kw dict, optional. Dict with keywords passed to the GridSpec constructor used to create the grid the subplots are placed on. **fig_kw. All additional keyword arguments are passed to the pyplot.figure call. Returns: fig Figure ax axes.Axes object or array of

The Using Gridspec to make multi-column/row subplot layouts shows a way to do this with GridSpec. A simplified version of the example with 3 subplots would look like

import matplotlib.pyplot as plt

fig = plt.figure()

gs = fig.add_gridspec(2,2)
ax1 = fig.add_subplot(gs[0, 0])
ax2 = fig.add_subplot(gs[0, 1])
ax3 = fig.add_subplot(gs[1, :])

Advanced plotting, In Matplotlib, we learned about making plots using a procedural method, e.g.: it allows users to easily handle multiple figures/axes without getting confused as to will show a subplot that occupies all the figure (and the axis labels will in fact� read the documentation: matplotlib.pyplot.subplots. pyplot.subplots() returns a tuple fig, ax which is unpacked in two variables using the notation. fig, axes = plt.subplots(nrows=2, ncols=2) the code. fig = plt.figure() axes = fig.subplots(nrows=2, ncols=2) does not work because subplots()is a function in pyplot not a member of the object Figure.

There are three main options in matplotlib to make separate plots within a figure:

  1. subplot: access the axes array and add subplots
  2. gridspec: control the geometric properties of the underlying figure (demo)
  3. subplots: wraps the first two in a convenient api (demo)

The posts so far have addressed the first two options, but they have not mentioned the third, which is the more modern approach and is based on the first two options. See the specific docs Combining two subplots using subplots and GridSpec.

Multiple maps using subplots — Basemap tutorial 0.1 documentation, Drawing multiple maps in the same figure is possible using matplotlib's Creating the axis using subplot directly with add_subplot; Creating the subplots with pylab. So, to create the plots at the beginning and using them later, pyplot. subplots the example, where the second column has only one cell occupying two rows. import matplotlib.pyplot as plt fig, axes = plt.subplots(nrows=4, ncols=4) fig.tight_layout() # Or equivalently, "plt.tight_layout()"

num: This parameter is the pyplot.figure keyword that sets the figure number or label. subplot_kwd: This parameter is the dict with keywords passed to the add_subplot call used to create each subplot. gridspec_kw: This parameter is the dict with keywords passed to the GridSpec constructor used to create the grid the subplots are placed on.

Je sais que matlab le permet en utilisant la commande subplot comme ceci . subplot(2,2,[1,2]) % the plot will span subplots 1 and 2 Est-il également possible dans pyplot d'avoir un seul axe occupant plus d'une sous-parcelle? Le docstring de pyplot.intrigue secondaire n'en parle pas. Quelqu'un a une solution facile? Merci d'avance

plt. subplot (221) # equivalent but more general ax1 = plt. subplot (2, 2, 1) # add a subplot with no frame ax2 = plt. subplot (222, frameon = False) # add a polar subplot plt. subplot (223, projection = 'polar') # add a red subplot that shares the x-axis with ax1 plt. subplot (224, sharex = ax1, facecolor = 'red') # delete ax2 from the figure plt. delaxes (ax2) # add ax2 to the figure again plt. subplot (ax2)

  • Possible duplicate of…
  • While this answers the specific example given in the question, it's unclear how this applies to layouts which are not powers of 2. For my code I would like to split the layout into thirds. A plot to fill right 2 thirds and another plot filling a left third.
  • This answer actually applies to regular layouts (no "power of 2" constraint): subplot(3, 1, 1), for instance, cuts in thirds. Now, what you want is handled by the axes_grid toolkit.
  • @EOL, I'm thinking of 2 thirds, not 1 thirds. For example, I have two subplot , with only 1 column, the 1st spans 2/3, the 2nd spans 1/3. How could this be done? THanks.
  • I am not fully sure, but it looks like the appropriate method is described in a specific Matplotlib toolkit (axes_grid1):….
  • very cool, didn't know about this, exactly what I need, especially the colspan and rowspan features.
  • so so so SO. awesome! thanks a million. this is necessary if you have for instance 6 rows... and you want one plot on row 1. and another plot to span rows 2,3,4. you can't use the usual subplot tricks (i.e. subplot(611) and subplot(612)... because subplot doesn't have any idea of span).