Seaborn combining different data frames into one grouped bar plot-CodePudding

I'm trying to copy the answer from

Can someone show me where I'm going wrong?

CodePudding user response：

It's difficult to give a great answer because I know this is just demo data so dealing with your real data is going to be different. I think the way you are creating the dataframe is giving you the problem since you are plotting directly with pandas.

Currently, your dataframe looks like:

...but you need your X axis to be the index, and a separate column for Cat1 and Cat2 with their respective values. Something closer to:

The way you accomplish this will depend on your actual dataset, but using the example provided (I slightly changed your input values for better visualization), this was my approach:

import pandas as pd

cat1 = {'item1':4, 'item2':6, 'item3':7,'item4':8,'item5':10}
cat2 = {'item1':5, 'item2':4, 'item3':12,'item4':6,'item5':3}

df1 = pd.DataFrame.from_dict(cat1, orient='index', columns=['Cat1'])
df2 = pd.DataFrame.from_dict(cat2, orient='index', columns=['Cat2'])

df = pd.concat([df1, df2], axis=1)

ax = df.plot.bar(rot=0)

Output:

CodePudding user response：

You can plot your DataFrame with seaborn like below:

>>> import seaborn as sns
>>> sns.barplot(data=result, x='Area', y='Number', hue='Cat')

Or If you have DataFrame like in your question and you want to use