python - One colorbar for multiple pandas subplots

Question

I cannot for the life of me figure out how to attach one colorbar for multiple pandas subplots. Almost all the other questions that resolve the issue of putting one colorbar for multiple subplots use np arrays, not dataframes, to plot.

There is one question, One colorbar for seaborn heatmaps in subplot, which seems like it could be useful, however I could not figure out how to extend it to my case.

Could anyone help? Below is an example of my current code. Thanks in advance!

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

# If you're using a notebook:
# %matplotlib inline

df = pd.DataFrame({"BASE": np.random.randn(10),
            "A": np.random.randn(10),
            "B": np.random.randn(10),
             "C": np.random.randn(10), 
             "D": np.random.randn(10),
            "color_col": [1,1,2,2,1,1,2,1,2,2]})




plt.figure(1, figsize = (15,15))

plt.subplot(2,2,1)
df.plot.scatter(x = "BASE", y = "A", c = df["color_col"], ax = plt.gca())

plt.subplot(2,2,2)
df.plot.scatter(x = "BASE", y = "B", c = df["color_col"], ax = plt.gca())

plt.subplot(2,2,3)
df.plot.scatter(x = "BASE", y = "C", c = df["color_col"], ax = plt.gca())

plt.subplot(2,2,4)
df.plot.scatter(x = "BASE", y = "D", c = df["color_col"], ax = plt.gca())

Answer 1

The question Matplotlib 2 Subplots, 1 Colorbar is probably more what you are looking for. The problem is however that you do not directly have access to the mappable that is created in the pandas scatter plot.

The solution here would be to distill this mappable (in this case a PatchCollection) from the axes using it plt.gca().get_children()[0], which takes the first child artist from the axes.

This method is save as long as all scatterplots share the same colors and as long as there are no other artists in the axes.

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

df = pd.DataFrame({"BASE": np.random.randn(10),
            "A": np.random.randn(10),
            "B": np.random.randn(10),
             "C": np.random.randn(10), 
             "D": np.random.randn(10),
            "color_col": np.random.randn(10)})

fig = plt.figure(1, figsize = (6,6))
plt.subplots_adjust(wspace=0.5, right=0.8, top=0.9, bottom=0.1)
for i, col in enumerate("ABCD"):
    plt.subplot(2,2,i+1)
    df.plot.scatter(x = "BASE", y = col, ax = plt.gca(), 
                    c = df["color_col"], cmap="jet", colorbar=False)

# we now take the first axes and 
# create a colorbar for it's first child (the PathCollection from scatter)
# this is save as long as all scatterplots share the same colors and
# as long as there are no other artists in the axes.
im = plt.gca().get_children()[0]
cax = fig.add_axes([0.85,0.1,0.03,0.8]) 
fig.colorbar(im, cax=cax)

plt.show()