Matplotlib table formatting

Question

Can't seem to locate in the documentation how to increase the line-height of the cells, as the text itself is very cramped.

Any help with code is appreciated! Table formatting doesn't seem to be well documented...

    # Plot line width     matplotlib.rc('lines', linewidth=3)      ind = np.arange(len(overall))      fig = pyplot.figure()     ax = fig.add_subplot(211)     ax.set_title('Overall Rating of Experience')     ax.set_ylabel('Score (0-100)')      # Plot data on chart     plot1 = ax.plot(ind, overall)     plot2 = ax.plot(ind, svc_avg)     plot3 = ax.plot(ind, benchmark)      ax.yaxis.grid(True, which='major', ls='-', color='#9F9F9F')     ax.set_ylim([min(overall + svc_avg + benchmark) - 3, 100])     ax.set_xlim([-.5,1.5])     ax.get_xaxis().set_ticks([])     ax.set_position([.25, .3, 0.7, 0.5])      colLabels = ['July', 'August']     rowLabels = ['Average', 'Service Average', 'Benchmark']     cellText = [overall, svc_avg, benchmark]     the_table = ax.table(cellText=cellText, rowLoc='right',                          rowColours=colors, rowLabels=rowLabels,                          colWidths=[.5,.5], colLabels=colLabels,                          colLoc='center', loc='bottom') 

EDIT: Thanks to Oz for the answer-- Looping through the properties of the table allows easy modification of the height property:

    table_props = the_table.properties()     table_cells = table_props['child_artists']     for cell in table_cells: cell.set_height(0.1) 

Answer 1

The matplotlib documentation says

Add a table to the current axes. Returns a matplotlib.table.Table instance. For finer grained control over tables, use the Table class and add it to the axes with add_table().

You could do is the following, look at the properties of your table (it's and object belonging to that class Table):

print  the_table.properties() # hint it's a dictionary do: type(the_table.properties() <type 'dict'>  

edit that dictionary the way you see right, and the update your table, with:

the_table.update(giveHereYourDictionary) 

Hint: if you work with IPython or interactive shell it's enough to do help(objectName), e.g. help(the_table) to see all the object's methods. This should, hopefully, work.

OK, I'm adding here a walk through of how to to that kind of stuff. I admit, it's not trivial, but I am using matplotlib for 3.5 years now, so ...

Do your code in IPython (I said it before, but I must emphasize again), it really helps to examine all the properties that objects have (type object name and then the key):

In [95]: prop=the_table.properties() In [96]: prop #This is a dictionary, it's not so trivial, but never the less one can understand how dictionaries work... Out[96]:  {'agg_filter': None,  'alpha': None,  'animated': False,  'axes': <matplotlib.axes.AxesSubplot at 0x9eba34c>,  'celld': {(0, -1): <matplotlib.table.Cell at 0xa0cf5ec>,   (0, 0): <matplotlib.table.Cell at 0xa0c2d0c>,   (0, 1): <matplotlib.table.Cell at 0xa0c2dec>,   (0, 2): <matplotlib.table.Cell at 0xa0c2ecc>,   (1, -1): <matplotlib.table.Cell at 0xa0cf72c>,   (1, 0): <matplotlib.table.Cell at 0xa0c2fac>,   (1, 1): <matplotlib.table.Cell at 0xa0cf08c>,   (1, 2): <matplotlib.table.Cell at 0xa0cf18c>,   (2, -1): <matplotlib.table.Cell at 0xa0cf84c>,   (2, 0): <matplotlib.table.Cell at 0xa0cf28c>,   (2, 1): <matplotlib.table.Cell at 0xa0cf3ac>,   (2, 2): <matplotlib.table.Cell at 0xa0cf4cc>},  'child_artists': [<matplotlib.table.Cell at 0xa0c2dec>,   <matplotlib.table.Cell at 0xa0cf18c>,   <matplotlib.table.Cell at 0xa0c2d0c>,   <matplotlib.table.Cell at 0xa0cf84c>,   <matplotlib.table.Cell at 0xa0cf3ac>,   <matplotlib.table.Cell at 0xa0cf08c>,   <matplotlib.table.Cell at 0xa0cf28c>,   <matplotlib.table.Cell at 0xa0cf4cc>,   <matplotlib.table.Cell at 0xa0cf5ec>,   <matplotlib.table.Cell at 0xa0c2fac>,   <matplotlib.table.Cell at 0xa0cf72c>,   <matplotlib.table.Cell at 0xa0c2ecc>],  'children': [<matplotlib.table.Cell at 0xa0c2dec>,   <matplotlib.table.Cell at 0xa0cf18c>,   ...snip snap ...   <matplotlib.table.Cell at 0xa0cf72c>,   <matplotlib.table.Cell at 0xa0c2ecc>],  'clip_box': TransformedBbox(Bbox(array([[ 0.,  0.],        [ 1.,  1.]])), CompositeAffine2D(BboxTransformTo(Bbox(array([[ 0.,  0.],        [ 1.,  1.]]))), BboxTransformTo(TransformedBbox(Bbox(array([[ 0.25,  0.3 ],        [ 0.95,  0.8 ]])), BboxTransformTo(TransformedBbox(Bbox(array([[ 0.,  0.],        [ 8.,  6.]])), Affine2D(array([[ 80.,   0.,   0.],        [  0.,  80.,   0.],        [  0.,   0.,   1.]])))))))),  'clip_on': True,  'clip_path': None,  'contains': None,  'figure': <matplotlib.figure.Figure at 0x9eaf56c>,  'gid': None,  'label': '',  'picker': None,  'rasterized': None,  'snap': None,  'transform': BboxTransformTo(TransformedBbox(Bbox(array([[ 0.25,  0.3 ],        [ 0.95,  0.8 ]])), BboxTransformTo(TransformedBbox(Bbox(array([[ 0.,  0.],        [ 8.,  6.]])), Affine2D(array([[ 80.,   0.,   0.],        [  0.,  80.,   0.],        [  0.,   0.,   1.]])))))),  'transformed_clip_path_and_affine': (None, None),  'url': None,  'visible': True,  'zorder': 0}  # we now get all the cells ...  [97]: cells = prop['child_artists']  In [98]: cells Out[98]:  [<matplotlib.table.Cell at 0xa0c2dec>,  <matplotlib.table.Cell at 0xa0cf18c>, ... snip snap...  <matplotlib.table.Cell at 0xa0cf72c>,  <matplotlib.table.Cell at 0xa0c2ecc>]  In [99]:cell=cells[0] In [100]: cell # press tab here to see cell's attributes  Display all 122 possibilities? (y or n) cell.PAD cell.add_callback ...snip snap ... cell.draw cell.eventson cell.figure ...snip snap ... In [100]: cell.set_h cell.set_hatch   cell.set_height   # this looks promising no? Hell, I love python ;-) wait, let's examine something first ... In [100]: cell.get_height() Out[100]: 0.055555555555555552 In [101]: cell.set_height(0.1) # we just 'doubled' the height... In [103]: pyplot.show() 

and TA DA:

Now, I challege you to change the height of all the cells, using a for loop. Should not be so hard. Would be nice to win that bounty ;-)