How to iterate through each probability column of a dataframe and find the row number from where the probability goes below 50% in python

I have a dataframe which is the output of predict_survival_function() from cox propotional model, which gives the probability of survival of customers for every month (index row number) and in columns we have the customers. So I would like to get the month number for each customers when the probability goes below 0.50. Below is the screenshot of the table.

The output I am looking for is something like below -
Suppose for first customer No. 4 (First column in the dataframe) If the probability goes less than 0.50 at row number 55. Then the output should be

And similar for all the other columns in the data frame.
Any help is appreciated

Suppose the following dataframe:

>>> df
          4         5         7
0  0.974789  0.976546  0.913151
1  0.918408  0.815823  0.909577
2  0.748928  0.801727  0.856562
3  0.691171  0.791815  0.794988
4  0.442441  0.669530  0.750395  # Customer 4, first value below 0.5 -> row 4
5  0.378585  0.568831  0.561721
6  0.285419  0.287814  0.521966  # Customer 5, first value below 0.5 -> row 6
7  0.240335  0.216207  0.176980  # Customer 7, first value below 0.5 -> row 7
8  0.191656  0.095793  0.118300
9  0.183290  0.087297  0.035063

IIUC, you can use idxmax:

>>> (df <= 0.5).idxmax()
4    4
5    6
7    7
dtype: int64

Full output:

out = ((df <= 0.5).idxmax().rename_axis('Customer Number')
                  .rename('Row Number').reset_index())
print(out)
# Output
   Customer Number  Row Number
0                4           4
1                5           6
2                7           7