CODEWITHSUNDEEP
pythonpandasmatplotlibdata-visualizationseaborn
JA-pythonista
JA-pythonista

Reputation: 1323

How to plot multiple columns side by side with Seaborn countplot

I have a Pandas DataFrame, for example:

pd.DataFrame({
    "A": [165,166,920,920,920,165,162,162,166,165,755,469],
    "B": [1920,868,470,470,698,945,1670,575,701,1920,1920,470],
    "C": [1670,461,461,212,212,212,212,414,453,196,254,461]
})

I would like to have a seaborn countplot of each option A, B and C with the top 2 for each column plotted side by side.

Below is an image of something similar. My problem is getting the columns side by side with the legend.

Something similar to this

Thanks

Upvotes: 0

Views: 2629

Answers (1)

JP Maulion
JP Maulion

Reputation: 2504

Can you try this?

import pandas as pd
import seaborn as sns

df=pd.DataFrame({
"A": [165,166,920,920,920,165,162,162,166,165,755,469],
"B": [1920,868,470,470,698,945,1670,575,701,1920,1920,470],
"C": [1670,461,461,212,212,212,212,414,453,196,254,461]})


sns.set(style="darkgrid")
fig, ax =plt.subplots(3,1)
max_count = max([max(df[i].value_counts()) for i in df.columns])
A=sns.countplot(y=df['A'],ax=ax[0],order=df.A.value_counts().iloc[:2].index)
B=sns.countplot(y=df['B'],ax=ax[1],order=df.B.value_counts().iloc[:2].index)
C=sns.countplot(y=df['C'],ax=ax[2],order=df.C.value_counts().iloc[:2].index)
ax[0].set_xlim(0,max_count)
ax[1].set_xlim(0,max_count)
ax[2].set_xlim(0,max_count)
A.set(xticklabels=[])
B.set(xticklabels=[])

enter image description here

Upvotes: 2

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