I am looking to apply a bin across a number of columns.

a = [1, 2, 9, 1, 5, 3]
b = [9, 8, 7, 8, 9, 1]c = [a, b]print(pd.cut(c, 3, labels=False))

which works great and creates:

[[0 0 2 0 1 0]
[2 2 2 2 2 0]]

However, i would like to apply the 'cut' to create a dataframe with number and bin it as below.

   Values  bin
0       1    0
1       2    0
2       9    2
3       1    0
4       5    1
5       3    0Values  bin
0       9    2
1       8    2
2       7    2
3       8    2
4       9    2
5       1    0 

This is a simple example of what im looking to do. In reality i 63 separate dataframes and a & b are examples of a column from each dataframe.

Use zip with a list comp to build a list of dataframes -

c = [a, b]
r = pd.cut(c, 3, labels=False)df_list = [pd.DataFrame({'Values' : v, 'Labels' : l}) for v, l in zip(c, r)]

df_list[   Labels  Values0       0       11       0       22       2       93       0       14       1       55       0       3,    Labels  Values0       2       91       2       82       2       73       2       84       2       95       0       1]