Making the labels of the scatterplot vertical and horizontal in Pandas

Question

I'm using Pandas to draw a scatterplot matrix: from pandas.tools.plotting import scatter_matrix. The problem is that the names of the columns in the DataFrame are too long and I need them to be vertical in the x-axis and horizontal in the y-axis so they can fit. I'm not able to figure out at all how to do that in Pandas. I know how to do it in matplotlib but not in Pandas.

My code:

pylab.clf()
df = pd.DataFrame(X, columns=the_labels)
axs = scatter_matrix(df, alpha=0.2, diagonal='kde')

Edit: I need to use pylab.clf() because I'm plotting a lot of figures, so calling pylab.figure() each time is too memory consuming.

Answer 1

Major help from this answer: https://stackoverflow.com/a/18994338/2632856

a = [[1,2], [2,3], [3,4], [4, 5], [1, 6], [2,7], [1,8]]
df = pd.DataFrame(a,columns=['askdabndksbdkl','aooweoiowiaaiwi'])
axs = pd.scatter_matrix( df, alpha=0.2, diagonal='kde')
n = len(df.columns)
for x in range(n):
    for y in range(n):
        # to get the axis of subplots
        ax = axs[x, y]
        # to make x axis name vertical  
        ax.xaxis.label.set_rotation(90)
        # to make y axis name horizontal 
        ax.yaxis.label.set_rotation(0)
        # to make sure y axis names are outside the plot area
        ax.yaxis.labelpad = 50

Answer 2

scatter_matrix returns a two-dimensional array of matplotlib subplots. This means you should be able to iterate over the two arrays and use matplotlib functions to rotate axes. Based on the source used to implement scatter_matrix and the private helper function _label_axis, it looks as though you should be able to perform your rotations for all the plots with:

from matplotlib.artist import setp

x_rotation = 90
y_rotation = 90

for row in axs:
    for subplot in row:
        setp(subplot.get_xticklabels(), rotation=x_rotation)
        setp(subplot.get_yticklabels(), rotation=y_rotation)

I don't have a good way to test this so it may require a bit of playing around.