How do I use Seaborn to concatenate two columns to be displayed as one in a boxplot?

Question

I have the following dataset:

pd.DataFrame({'With': data_a[' time'], 'Without': data_b[' time']})

the float number is the time in ms

With means one experiment completed with help

Without means one experiment done without help

       With       Without
0     270147.0    317665.0
1     275627.0    323294.0
2     278488.0    327733.0
3     280900.0    331134.0
4     283299.0    333294.0
5     286000.0    335873.0
6     288231.0    338292.0
7     290408.0    342418.0
8     292512.0    344527.0
9     295838.0    347096.0
10    298021.0    349104.0
11    299893.0    350911.0
12    303356.0    353363.0
13    306205.0    356038.0
14    309123.0    358461.0
15    312196.0    361041.0

I want to display in the x-axis the time taken

I want to display in the y-axis the type of time (With, Without)

this is what I've found that I should use:

seaborn.catplot(
    data=<your data variable here>, x = "your x axis name here", y = "your y axis name here", kind="box"
)

however, my x should be the time taken, and my y should be the type (with, without)

What should in order to have it as I need?

Answer 1

You may want to stack the dataframe, so that the column headers become a categorical feature.

import pandas as pd
import seaborn as sns
df = pd.DataFrame({'With': [270147.0,      275627.0,
  278488.0,      280900.0,
  283299.0,      286000.0,
  288231.0,      290408.0,
  292512.0,      295838.0,
  298021.0,      299893.0,
  303356.0,      306205.0,
  309123.0,      312196.0],
 'Without': [317665.0,
  323294.0,      327733.0,
  331134.0,      333294.0,
  335873.0,      338292.0,
  342418.0,      344527.0,
  347096.0,      349104.0,
  350911.0,      353363.0,
  356038.0,      358461.0,
  361041.0]})



df = df.stack().reset_index()

df.columns=['index','type','time']
sns.catplot(data=df, x='time', y='type')