[FIXED] Pandas hist subplots - adding colour bar for the colours of each histogram

Issue

I have the columns of a dataframe plotted as separate histogram subplots. For each subplot, I want the bars coloured according to the value in a separate list. I have managed this by making a cmap of it and manually cycling those colours, however, is there a way to add a colorbar to the side to show what values these colours belong to? This is what I have right now:

import pandas as pd
import matplotlib as mpl
from matplotlib.colors import rgb2hex

#reading in the data
df = pd.read_csv( "shortlist_temp.dat", sep='\t',header=(0), usecols=(range(1,13)))

#separate list of values
orig_star_teff = [4308.0, 5112.0, 4240.0, 4042.0, 4411.0, 4100.0, 4511.0, 4738.0, 4630.0, 4870.0, 4442.0, 4845.0]

#Colormapping the values. I did not like the result from the original values so I reduced by 4000.
orig_star_teff_norm = [i - 4000 for i in orig_star_teff] 
orig_star_teff_norm = [float(i)/max(orig_star_teff_norm) for i in orig_star_teff_norm]
cmap = mpl.cm.plasma
color_list = cmap(orig_star_teff_norm)
color_list2 = [ rgb2hex(color_list[i,:]) for i in range(color_list.shape[0]) ]
mpl.rcParams['axes.prop_cycle'] = mpl.cycler(color = color_list2)

ax = df.plot.hist(subplots=True, bins = 12, legend=False, layout=(3, 4), figsize = (15,10), sharey = True)

ax[0,0].set_title('ABOO')
ax[0,1].set_title('EpsVIR')
ax[0,2].set_title('HIP 96014')
ax[0,3].set_title('2M16113361')

ax[1,0].set_title('KIC 3955590')
ax[1,1].set_title('KIC 5113061')
ax[1,2].set_title('KIC 5859492')
ax[1,3].set_title('KIC 6547007')
    
ax[2,0].set_title('KIC 11444313')
ax[2,1].set_title('KIC 11657684')
ax[2,2].set_title('HD102328-K3III')
ax[2,3].set_title('HD142091-K0III')

Resulting plot

Solution

Instead of doing all the normalization steps manually, it probably is easier to create a norm. In this case a norm that maps the values from 4000 till max to the range 0,1 needed for the colormap. Note that converting to hex isn't necessary.

With the norm and the colormap a ScalarMapple can be created with all the necessary information for a colorbar:

import pandas as pd
import matplotlib as mpl
from matplotlib.cm import ScalarMappable

# reading in the data
# df = pd.read_csv("shortlist_temp.dat", sep='\t', header=(0), usecols=(range(1, 13)))
# generating some dummy data
df = pd.DataFrame(np.random.randn(100, 12))

# separate list of values
orig_star_teff = [4308.0, 5112.0, 4240.0, 4042.0, 4411.0, 4100.0, 4511.0, 4738.0, 4630.0, 4870.0, 4442.0, 4845.0]

norm = plt.Normalize(4000, max(orig_star_teff))
cmap = mpl.cm.plasma
color_list = cmap(norm(orig_star_teff))
mpl.rcParams['axes.prop_cycle'] = mpl.cycler(color=color_list)


axs = df.plot.hist(subplots=True, bins=12, legend=False, layout=(3, 4), figsize=(15, 10), sharey=True)
titles = ['ABOO', 'EpsVIR', 'HIP 96014', '2M16113361',
          'KIC 3955590', 'KIC 5113061', 'KIC 5859492', 'KIC 6547007',
          'KIC 11444313', 'KIC 11657684', 'HD102328-K3III', 'HD142091-K0III']
for ax, title in zip(axs.flat, titles):
    ax.set_title(title)
plt.colorbar(ScalarMappable(cmap=cmap, norm=norm), ax=axs[:, -1])
plt.show()

Answered By - JohanC