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up vote 4 down vote favorite
2

Is there a simple/clean way to iterate an array of axis returned by subplots like 

 nrow = ncol = 2
 a = []
 fig, axs = plt.subplots(nrows=nrow, ncols=ncol)
 for i, row in enumerate(axs):
     for j, ax in enumerate(row):
         a.append(ax)

 for i, ax in enumerate(a):
    ax.set_ylabel(str(i))

which even works for nrow or ncol = 1.

I tried list comprehension like:

[element for tupl in tupleOfTuples for element in tupl]

but that fails if nrows or ncols == 1

share|improve this question
up vote 9 down vote accepted

The ax return value is a numpy array, which can be reshaped, I believe, without any copying of the data. If you use the following, you'll get a linear array that you can iterate over cleanly.

nrow = 1; ncol = 2;
fig, axs = plt.subplots(nrows=nrow, ncols=nrow)

for ax in axs.reshape(-1):
  ax.set_ylabel(str(i))

This doesn't hold when ncols and nrows are both 1, since the return value is not an array; you could turn the return value into an array with one element for consistency, though it feels a bit like a cludge: 

nrow = 1; ncol = 1;
fig, axs = plt.subplots(nrows=nrow, ncols=nrow)
axs = np.array(axs)

for ax in axs.reshape(-1):
  ax.set_ylabel(str(i))

reshape docs. The argument -1 causes reshape to infer dimensions of the output.

share|improve this answer
    
For nrow=ncol=1 you can use squeeze=0. plt.subplots(nrows=nrow, ncols=nrow, squeeze=0) always returns a 2 dimensional array for the axes, even if both are one. – cronos Apr 6 at 11:26
up vote 1 down vote

The fig return value of plt.subplots has a list of all the axes. To iterate over all the subplots in a figure you can use:

nrow = 2
ncol = 2
fig, axs = plt.subplots(nrow, ncol)
for i, ax in enumerate(fig.axes):
    ax.set_ylabel(str(i))

This also works for nrow == ncol == 1.

share|improve this answer

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