Dataframe to plot different charts from groups in columns

Question

I have a dataframe that has multiple columns, containing different categories (['A'], ['1','2','3','4'])

Index1 Index2    X    Y
A      '1'       1    2
A      '1'       5    3
A      '1'       3    4
A      '2'       3    1
A      '2'       4    1
A      '2'       3    5 
A      '2'       1    2
A      '3'       5    3
A      '3'       3    4
A      '4'       3    1
A      '4'       4    1
A      '4'       3    5

I need to loop it so that it brings me four different splatter charts for each pair of indexes (in the future there will be a B index, that's the reason for the multiindex).

My code at the moment brings me one chart for every line (in this example would be 12 of them), if I break at the end it brings me only one

I tried .iterows() and .itertuples() both of them got me the same result (maybe have been using them wrong to)

import pandas as pd
from matplotlib import pyplot as plt

Index1 = ['A','A','A','A','A','A','A','A','A','A','A','A']
Index2 = ['1','1','1','2','2','2','2','3','3','4','4','4']
X = [1,5,3,3,4,3,1,5,3,3,4,3]
Y = [2,3,4,1,1,5,2,3,4,1,1,5]
df = pd.DataFrame(Index1)
df = df.assign(Index2 = Index2,X=X,Y=Y)
df.set_index(['Index1','Index2'])

second_index = 1     
for index in df.itertuples():
    df = df.groupby('Index2').get_group(second_index)
    df.plot.scatter(x = 'X', y = 'Y')
    plt.show()
    break  

I have a similar code runing on a dictionary that works on the same logic and it brings me all the charts that I need.

p.s.: that's not the real code just the general idea, and I might have made some mistakes

Answer 1

I don't see what the loop is doing, but if a loop variable is not used anywhere inside the loop it's a good sign that the loop is not even needed.

Here it seems you want to plot each group, hence

df.groupby("Index2").plot(x="X", y="Y", kind="scatter")

Complete example:

import pandas as pd
from matplotlib import pyplot as plt

Index1 = ['A','A','A','A','A','A','A','A','A','A','A','A']
Index2 = ['1','1','1','2','2','2','2','3','3','4','4','4']
X = [1,5,3,3,4,3,1,5,3,3,4,3]
Y = [2,3,4,1,1,5,2,3,4,1,1,5]
df = pd.DataFrame(Index1)
df = df.assign(Index2 = Index2,X=X,Y=Y)

df.groupby("Index2").plot(x="X", y="Y", kind="scatter")

plt.show()

However, if you really want to loop for whatever reason, you could loop over the groupby:

for (n, group) in df.groupby("Index2"):
    group.plot.scatter(x="X", y="Y")