python - 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 ;-)