CODEWITHSUNDEEP
pythonmatplotlibbar-chartsubplot
Paws
Paws

Reputation: 85

Create subplots of bar chart for each row in dataframe

I have a dataframe for example the following, where Material, A and B are all column headings:

    Material    A           B
0   Iron        20.30000    5.040409
1   Antimony    0.09200     0.019933
2   Chromium    1.70000     0.237762
3   Copper      8.10000     2.522951

I want to be able to have a 2x2 subplots consisting of bar graphs based on the 4 rows. The heading of each of the 4 subplots would be the material. Each subplot would have two bars for each value of A and B, each bar is in the subplot have a colour associated to A and B. Finally also would be nice to have a legend showing the colour and what it represents i.e. A and B. 

import matplotlib.pyplot as plt
import pandas as pd 
import seaborn as sns
import matplotlib.style as style 
sns.set_style("darkgrid")

fig, ax = plt.subplots(2,2)

#Enter for loop

I think a for loop would be the best way to do it, but simply cannot figure out the for loop. Thanks.

Upvotes: 3

Views: 2728

Answers (2)

Joe
Joe

Reputation: 12417

You can do in this way:

df = df.set_index('Material')
fig = plt.figure(figsize=(10,8))

for i, (name, row) in enumerate(df.iterrows()):
    ax = plt.subplot(2,2, i+1)
    ax.set_title(row.name)
    ax.get_xaxis().set_visible(False)
    df.iloc[i].plot.bar(color=['C0', 'C1'])
fig.legend(ax.bar([0,0],[0,0], color=['C0','C1']),['A','B'], loc=5)

plt.show()

enter image description here

Upvotes: 0

Diziet Asahi
Diziet Asahi

Reputation: 40747

fig, axs = plt.subplots(2,2, constrained_layout=True)
for ax,(idx,row) in zip(axs.flat, df.iterrows()):
    row[['A','B']].plot.bar(ax=ax, color=['C0','C1'])
    ax.set_title(row['Material'])

proxy = ax.bar([0,0],[0,0], color=['C0','C1'])
fig.legend(proxy,['A','B'], bbox_to_anchor=(1,1), loc='upper right')

enter image description here

Note that the same result can be achieved using pandas only, but first you need to reshape your data

df2 = df.set_index('Material').T

>>
Material       Iron  Antimony  Chromium    Copper
A         20.300000  0.092000  1.700000  8.100000
B          5.040409  0.019933  0.237762  2.522951

df2.plot(kind='bar', subplots=True, layout=(2,2), legend=False, color=[['C0','C1']])

enter image description here

Upvotes: 2

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