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Using the pandas API to matplotlib, I'm making a plot - with four subplots - of quantities in a dataframe. Now it's working well, but I'm having problem getting control of the colorbar that is automatically added to each axis. (There's a colorbar added because I'm plotting hexbin plots).

See the example here: https://pandas.pydata.org/pandas-docs/stable/visualization.html#hexagonal-bin-plot .

My goal is to set the label of the colorbar, but I'm unsure how to even go about this using the pandas API. My code for the first subplot is below:

fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(8, 8))
p1 = go65.plot.hexbin(x='si10_hx', y='tcc_hx', C='dsst_amp_bias', reduce_C_function=np.mean,\
             gridsize=25, vmin=-1.5, vmax=1.5, cmap = plt.cm.PiYG,\
             xlim=(0, 35), ylim=(0, 1),\
             ax=axes[0,0])

fig.get_axes() returns 8 objects, so the colorbar axes are there... I just need to know how to find (get a handle on) them. Thanks

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After much searching, I found that a similar question was asked here: Getting Colorbar instance of scatter plot in pandas/matplotlib

Because of the way the pandas matplotlib API works when a plot (scatter or hexbin) requires a colorbar, this has to be done manually by returning the axes in the figure and then manually working out which correspond to the colorbars. This can be done using 

axes_list = fig.get_axes()
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