I have the following dataframe:
df = pd.DataFrame(dict(
A=[1, 0, 0, 1],
B=[0, 1, 1, 1],
C=[1, 0, 0, 0]
))
How to plot a barplot where I sea number of 1s and 0s in one graph see:
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1 Answer
Starting from the dataset you provided:
df = pd.DataFrame(dict(
A=[1, 0, 0, 1],
B=[0, 1, 1, 1],
C=[1, 0, 0, 0]
))
you should re-shape the dataframe with pandas.melt:
df = pd.melt(frame = df,
var_name = 'class',
value_name = 'survived')
class survived
0 A 1
1 A 0
2 A 0
3 A 1
4 B 0
5 B 1
6 B 1
7 B 1
8 C 1
9 C 0
10 C 0
11 C 0
So you can use seaborn.countplot to get the plot you want:
fig, ax = plt.subplots()
sns.countplot(ax = ax, data = df, x = 'class', hue = 'survived')
plt.show()
Complete Code
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.DataFrame(dict(
A=[1, 0, 0, 1],
B=[0, 1, 1, 1],
C=[1, 0, 0, 0]
))
df = pd.melt(frame = df,
var_name = 'class',
value_name = 'survived')
fig, ax = plt.subplots()
sns.countplot(ax = ax, data = df, x = 'class', hue = 'survived')
plt.show()
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