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)
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()
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': , 'celld': {(0, -1): , (0, 0): , (0, 1): , (0, 2): , (1, -1): , (1, 0): , (1, 1): , (1, 2): , (2, -1): , (2, 0): , (2, 1): , (2, 2): }, 'child_artists': [, , , , , , , , , , , ], 'children': [, , ...snip snap ... , ], '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': , '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]: [, , ... snip snap... , ] 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 ;-)
You can also play with the bbox (bounding box) property directly at function's call, so just add the bbox argument in the .table method as follow:
the_table = ax.table(cellText=cellText, rowLoc='right', rowColours=colors, rowLabels=rowLabels, colWidths=[.5,.5], colLabels=colLabels, colLoc='center', loc='bottom', bbox=[0, -0.3, 1, 0.275]) #
Where bbox is : [left, bottom, width, height]
So you can put the table a bit lower (-0.3), and setting the height to 0.275 (
Anyway, the idea is that you can play with bbox parameter to move and adjust your table fairly easily (at least more easily than the accepted answer)
If your table happens to disappear when saving the figure, you can re-adjust the entire figure with:
plt.tight_layout(rect=[0.11, 0.3, 0.95, .95])
Which obey to the same rules as a bbox (l, b, w, h). This (0.3) will let some space for the table below the axe, and the 0.11 will allow the rowLabel to fit in the figure. You'll have to fiddle around with the values so it looks best for you.
This gives (I use fig.add_suplot(111) btw):
As a matter of comparison, the same figure without changing the bbox properties:
Hope this helps.
Can't seem to locate in the documentation how to increase the line-height of the cells, as the text itself is very cramped. 
