[FIXED] Seaborn multiple barplots

Issue

I have a pandas dataframe that looks like this:

    class       men       woman   children
0   first   0.91468    0.667971   0.660562
1   second  0.30012    0.329380   0.882608
2   third   0.11899    0.189747   0.121259

How would I create a plot using seaborn that looks like this? Do I have to rearrange my data in some way?

_{(source: mwaskom at stanford.edu)}

Solution

Tested in python 3.12.0, pandas 2.1.1, matplotlib 3.8.0, seaborn 0.13.0

Reshape the DataFrame with pandas.DataFrame.melt or pandas.melt:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# convert the dataframe to a long format
dfm = pd.melt(df, id_vars="class", var_name="sex", value_name="survival rate")
dfm
Out: 
    class       sex  survival rate
0   first       men       0.914680
1  second       men       0.300120
2   third       men       0.118990
3   first     woman       0.667971
4  second     woman       0.329380
5   third     woman       0.189747
6   first  children       0.660562
7  second  children       0.882608
8   third  children       0.121259

Consolidate the plot by creating a single facet with grouped bars, instead of multiple facets with single bars.

Plot with the figure-level method sns.catplot

g = sns.catplot(x='class', y='survival rate', hue='sex', data=dfm, kind='bar', height=5, aspect=1)

Plot with the axes-level method sns.barplot

# the following code matches the plot produced by catplot
plt.figure(figsize=(5, 5))
ax = sns.barplot(x='class', y='survival rate', hue='sex', data=dfm)
ax.spines[['top', 'right']].set_visible(False)
sns.move_legend(ax, bbox_to_anchor=(1, 0.5), loc='center left', frameon=False)

---

Deprecated

factorplot (v0.8.1 or earlier):

sns.factorplot(x='class', y='survival rate', hue='sex', data=df, kind='bar')

Answered By - ayhan