Seaborn and Pandas, grouped box plot

Question

I'm pretty new to Python/data in general and I'm having a hard time wrapping my head around this

I currently have 3 data frames which look like this

| A | B | C | Type | | 1 | 2 | 6 | Worst | | 3 | 4 | 5 | Worst | | A | B | C | Type | | 1 | 2 | 3 | Medium | | A | B | C | Type | | 1 | 5 | 20 | Worst|

I'm trying to create a grouped boxplot in which each A from the 3 types gets a boxplot and are grouped together, the same goes for B and C

I'm unsure of how to join all these data frames together so that I can send them into the seaborn catplot function. There doesn't seem to be much documentation on how to set up the data.

Since the dataframes all have the same columns, you can use concat to combine them. pandas.pydata.org/pandas-docs/stable/reference/api/… — Eric Truett
– Eric Truett, Commented Apr 20, 2020 at 15:20

jcaliz · Accepted Answer · 2020-04-20 16:50:47Z

First concat the three dataframes with concat and then use seaborn to generate the boxplots from the resulting dataframe

import seaborn as sns # generate the new data frame df4 = pd.concat([df1, df2, df3]) # Do the boxplot sns.boxplot(data=df4, x='Type', y='A')

Sammiti Yadav · Accepted Answer · 2020-04-20 19:06:44Z

data1 = pd.DataFrame({'A':[1,3], 'B':[2,6], 'C':[6,5] , 'Type':['Worst','Worst']}) data2 = pd.DataFrame({'A':[1], 'B':[2], 'C':[3], 'Type':['Medium']}) data3 = pd.DataFrame({'A':[1], 'B':[5], 'C':[20], 'Type':['Worst']}) df=pd.concat([data1,data2,data3], join='inner') plt.figure(figsize= (6,10) plt.subplot(3,1,1) sns.boxplot(data=df, x ='A', y='Type') plt.subplot(3,1,2) sns.boxplot(data=df, x ='B', y='Type') plt.subplot(3,1,2) sns.boxplot(data=df, x ='C', y='Type') plt.show()

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