Why do many examples use fig ax plt subplots in Matplotlib pyplot python

Question

I m learning to use matplotlib by studying examples  and a lot of examples seem to include a line like the following before creating a single plot     fig  ax   plt subplots     Here are some examples      Modify tick label text http   matplotlib org examples pylab examples boxplot demo2 html   I see this function used a lot  even though the example is only attempting to create a single chart  Is there some other advantage  The official demo for subplots   also uses f  ax   subplots when creating a single chart  and it only ever references ax after that  This is the code they use     Just a figure and one subplot f  ax   plt subplots   ax plot x  y  ax set title  Simple plot

User · Answer

As a supplement to the question and above answers there is also an important difference between plt.subplots() and plt.subplot(), notice the missing 's' at the end.

One can use plt.subplots() to make all their subplots at once and it returns the figure and axes (plural of axis) of the subplots as a tuple. A figure can be understood as a canvas where you paint your sketch.

# create a subplot with 2 rows and 1 columns
fig, ax = plt.subplots(2,1)

Whereas, you can use plt.subplot() if you want to add the subplots separately. It returns only the axis of one subplot.

fig = plt.figure() # create the canvas for plotting
ax1 = plt.subplot(2,1,1) 
# (2,1,1) indicates total number of rows, columns, and figure number respectively
ax2 = plt.subplot(2,1,2)

However, plt.subplots() is preferred because it gives you easier options to directly customize your whole figure

# for example, sharing x-axis, y-axis for all subplots can be specified at once
fig, ax = plt.subplots(2,2, sharex=True, sharey=True)

whereas, with plt.subplot(), one will have to specify individually for each axis which can become cumbersome.

User · Answer

Just a supplement here   The following question is that what if I want more subplots in the figure   As mentioned in the Doc  we can use fig   plt subplots nrows 2  ncols 2  to set a group of subplots with grid 2 2  in one figure object   Then as we know  the fig  ax   plt subplots   returns a tuple  let s try fig  ax1  ax2  ax3  ax4   plt subplots nrows 2  ncols 2  firstly   ValueError  not enough values to unpack  expected 4  got 2    It raises a error  but no worry  because we now see that plt subplots   actually returns a tuple with two elements  The 1st one must be a figure object  and the other one should be a group of subplots objects   So let s try this again   fig    ax1  ax2    ax3  ax4     plt subplots nrows 2  ncols 2    and check the type   type fig    lt class  matplotlib figure Figure  gt  type ax1    lt class  matplotlib axes  subplots AxesSubplot  gt    Of course  if you use parameters as  nrows 1  ncols 4   then the format should be   fig   ax1  ax2  ax3  ax4    plt subplots nrows 1  ncols 4    So just remember to keep the construction of the list as the same as the subplots grid we set in the figure   Hope this would be helpful for you

User · Answer

In addition to the answers above  you can check the type of object using type plt subplots    which returns a tuple  on the other hand  type plt subplot    returns matplotlib axes  subplots AxesSubplot which you can t unpack

User · Answer

plt subplots   is a function that returns a tuple containing a figure and axes object s   Thus when using fig  ax   plt subplots   you unpack this tuple into the variables fig and ax  Having fig is useful if you want to change figure-level attributes or save the figure as an image file later  e g  with fig savefig  yourfilename png     You certainly don t have to use the returned figure object but many people do use it later so it s common to see  Also  all axes objects  the objects that have plotting methods   have a parent figure object anyway  thus   fig  ax   plt subplots     is more concise than this   fig   plt figure   ax   fig add subplot 111

[python] Why do many examples use `fig, ax = plt.subplots()` in Matplotlib/pyplot/python

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