Subplot multiple combination of categories in python

Question

I have the following example dataset where 'Type1 has 2 categories 'A' and 'B' and 'Type2' has 3 categories 'Red', 'Blue', and ' Green'. I would like to plot 3 subplots where subplot 1 has 'Type1', subplot 2 has 'Type2' and subplot3 has the combination of 'Type1' and 'Type2'. The x axis is the 'Time' and the y axis is the 'Amount'. The combination subplot should be at the bottom of the first 2 subplot. And the subplot should be lineplot.

Time, Type1, Type2, Amount 
0, A, Red, 1000
1, A, Red, 1002
2, A, Red, 1003
0, B, Blue, 50
1, B, Blue, 54
2, B, Blue, 60
0, A, Green, 89
1, A, Green, 90
2, A, Green, 100

I did not find anything useful in this regard. Any help is appreciated. Note: A resulting subplot should look like the answer in the subplot 3 graphs matplotlib

What should be the aggregated function per type (mean, sum, ...)? — Corralien
– Corralien, Commented Jan 8, 2023 at 10:03

Corralien · Accepted Answer · 2023-01-08 10:13:37Z

IIUC:

import matplotlib.pyplot as plt

fig = plt.figure(constrained_layout=True, figsize=(8, 8))
gs = fig.add_gridspec(2, 2)

ax1 = fig.add_subplot(gs[0, 0])
df.groupby(['Time', 'Type1'])['Amount'].mean().unstack('Type1').plot(ax=ax1)

ax2 = fig.add_subplot(gs[0, 1])
df.groupby(['Time', 'Type2'])['Amount'].mean().unstack('Type2').plot(ax=ax2)

ax3 = fig.add_subplot(gs[1, :])
df.groupby(['Time', 'Type1', 'Type2'])['Amount'].mean().unstack(['Type1', 'Type2']).plot(ax=ax3)

plt.show()

Output:

Note: groupby_unstack can be replaced by pivot_table:

>>> df.groupby(['Time', 'Type1', 'Type2'])['Amount'].mean().unstack(['Type1', 'Type2'])

Type1      A             B
Type2  Green     Red  Blue
Time                      
0       89.0  1000.0  50.0
1       90.0  1002.0  54.0
2      100.0  1003.0  60.0

>>> df.pivot_table(index='Time', columns=['Type1', 'Type2'], 
                   values='Amount', aggfunc='mean')
Type1     A          B
Type2 Green   Red Blue
Time                  
0        89  1000   50
1        90  1002   54
2       100  1003   60

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