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Im trying to plot a scatter matrix. I'm building on the example given in this thread Is there a function to make scatterplot matrices in matplotlib?. Here I have just modified the code slightly to make the axis visible for all the subplots. The modified code is given below

import itertools import numpy as np import matplotlib.pyplot as plt def main(): np.random.seed(1977) numvars, numdata = 4, 10 data = 10 * np.random.random((numvars, numdata)) fig = scatterplot_matrix(data, ['mpg', 'disp', 'drat', 'wt'], linestyle='none', marker='o', color='black', mfc='none') fig.suptitle('Simple Scatterplot Matrix') plt.show() def scatterplot_matrix(data, names, **kwargs): """Plots a scatterplot matrix of subplots. Each row of "data" is plotted against other rows, resulting in a nrows by nrows grid of subplots with the diagonal subplots labeled with "names". Additional keyword arguments are passed on to matplotlib's "plot" command. Returns the matplotlib figure object containg the subplot grid.""" numvars, numdata = data.shape fig, axes = plt.subplots(nrows=numvars, ncols=numvars, figsize=(8,8)) fig.subplots_adjust(hspace=0.05, wspace=0.05) for ax in axes.flat: # Hide all ticks and labels ax.xaxis.set_visible(True) ax.yaxis.set_visible(True) # # Set up ticks only on one side for the "edge" subplots... # if ax.is_first_col(): # ax.yaxis.set_ticks_position('left') # if ax.is_last_col(): # ax.yaxis.set_ticks_position('right') # if ax.is_first_row(): # ax.xaxis.set_ticks_position('top') # if ax.is_last_row(): # ax.xaxis.set_ticks_position('bottom') # Plot the data. for i, j in zip(*np.triu_indices_from(axes, k=1)): for x, y in [(i,j), (j,i)]: axes[x,y].plot(data[x], data[y], **kwargs) # Label the diagonal subplots... for i, label in enumerate(names): axes[i,i].annotate(label, (0.5, 0.5), xycoords='axes fraction', ha='center', va='center') # Turn on the proper x or y axes ticks. for i, j in zip(range(numvars), itertools.cycle((-1, 0))): axes[j,i].xaxis.set_visible(True) axes[i,j].yaxis.set_visible(True) fig.tight_layout() plt.xticks(rotation=45) fig.show() return fig main()

I cant seem to be able to rotate the x-axis text of all the subplots. As it can be seen, i have tried the plt.xticks(rotation=45) trick. But this seems to perform the rotation for the last subplot alone.

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3 Answers 3

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Just iterate through the axes tied to the figure, set the active axes to the iterated object, and modify:

for ax in fig.axes: matplotlib.pyplot.sca(ax) plt.xticks(rotation=90)
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plt only acts on the current active axes. You should bring it inside your last loop where you set some of the labels visibility to True:

# Turn on the proper x or y axes ticks. for i, j in zip(range(numvars), itertools.cycle((-1, 0))): axes[j,i].xaxis.set_visible(True) axes[i,j].yaxis.set_visible(True) for tick in axes[i,j].get_xticklabels(): tick.set_rotation(45) for tick in axes[j,i].get_xticklabels(): tick.set_rotation(45)
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+1 On a side note, it's much easier to just iterate over axes.flat instead of cycling over all i,j pairs. Also, you could use plt.setp(ax.get_xticklabels(), rotation=45) instead of iterating over each tick label. That's just a matter of style, though.
Agree, but the i,j iteration was already there, and only uses a subset of all the axes, there is no need to rotate hidden labels. The setp is a good addition indeed, i couldnt think of an ax. way of doing it at once, this does the trick!
21 
for ax in fig.axes: ax.tick_params(labelrotation=90)
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Code only answers can almost always be improved by adding some explanation. Without some explanation answers end up in the review queues.

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