Getting Colorbar instance of scatter plot in pandas/matplotlib

Question

How do I get the internally created colorbar instance of a plot created by pandas.DataFrame.plot?

Here is an example for generating a colored scatter plot:

Answer 1

pandas does not return the axis for the colorbar, therefore we have to locate it:

1st, let's get the figure instance: i.e., use plt.gcf()

In [61]:

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import itertools as it

# [ (0,0), (0,1), ..., (9,9) ]
xy_positions = list( it.product( range(10), range(10) ) )

df = pd.DataFrame( xy_positions, columns=['x','y'] )

# draw 100 floats
df['score'] = np.random.random( 100 )

ax = df.plot( kind='scatter',
              x='x',
              y='y',
              c='score',
              s=500)
ax.set_xlim( [-0.5,9.5] )
ax.set_ylim( [-0.5,9.5] )

f = plt.gcf()

2, how many axes does this figure have?

In [62]:

f.get_axes()
Out[62]:
[<matplotlib.axes._subplots.AxesSubplot at 0x120a4d450>,
 <matplotlib.axes._subplots.AxesSubplot at 0x120ad0050>]

3, The first axes (that is, the first one created), contains the plot

In [63]:

ax
Out[63]:
<matplotlib.axes._subplots.AxesSubplot at 0x120a4d450>

4, Therefore, the second axis is the colorbar axes

In [64]:

cax = f.get_axes()[1]
#and we can modify it, i.e.:
cax.set_ylabel('test')

Answer 2

It's not quite the same but you could just plot using matplotlib:

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import itertools as it

# [ (0,0), (0,1), ..., (9,9) ]
xy_positions = list( it.product( range(10), range(10) ) )

df = pd.DataFrame( xy_positions, columns=['x','y'] )

# draw 100 floats
df['score'] = np.random.random( 100 )

fig = plt.figure()
ax = fig.add_subplot(111)

s = ax.scatter(df.x, df.y, c=df.score, s=500)
cb = plt.colorbar(s)
cb.set_label('desired_label')

ax.set_xlim( [-0.5,9.5] )
ax.set_ylim( [-0.5,9.5] )

plt.show()