如何在 Matplotlib 的子图中添加多个条形图

Question

I have a Pandas data frame that is dynamic. and I am trying to place a bar graph in a subplot that will show multiple graphs in a single window. On the x-axis, there is 'Area' and on the y-axis, there is Area Count.

   Names                 Area         Area Count
0  Info 1        [LOCATION, PERSON]   [130, 346]
1  Info 2              [NRP]          [20]

rows = len(df1['Names']) 
fig, ax = plt.subplots(nrows=rows, ncols=1) 
df1['Area'].plot(ax=ax[0,0])
df1['Area Count'].plot(ax=ax[0,1]) 

Answer 1

• It's not exactly clear what you're attempting, however, given that the data shown is discreet (not continuous), it should be plotted as a bar plot, not a line plot.
• All of the values should be removed from lists by using pandas.Series.explode .

import pandas as pd
import seaborn as sns

# test dataframe
data = {'Names': ['Info 1', 'Info 2'], 'Area': [['LOCATION', 'PERSON'], ['NRP']], 'Area Count': [[130, 346], [20]]}
df = pd.DataFrame(data)

# display(df)
    Names                Area  Area Count
0  Info 1  [LOCATION, PERSON]  [130, 346]
1  Info 2               [NRP]        [20]

# explode the lists
df = df.set_index('Names').apply(pd.Series.explode).reset_index()

# display(df)
    Names      Area Area Count
0  Info 1  LOCATION        130
1  Info 1    PERSON        346
2  Info 2       NRP         20

Plotting

df.plot.bar(x='Area', y='Area Count')

sns.barplot(data=df, x='Area', y='Area Count', hue='Names', dodge=False)

df.pivot(index='Area', columns='Names', values='Area Count').plot.bar()

df.pivot(index='Names', columns='Area', values='Area Count').plot.bar()

sns.catplot(data=df, col='Names', x='Area', y='Area Count', kind='bar', estimator=sum)

rows = len(df.Names.unique())
fig, ax = plt.subplots(nrows=rows, ncols=1, figsize=(6, 8))
for i, v in enumerate(df.Names.unique()):
    data = df[df.Names == v]
    data.plot.bar(x='Area', y='Area Count', title=v, ax=ax[i], legend=False)
plt.tight_layout()
plt.show()