find the first occurrence of a value (from a list of values)in a pandas dataframe and return the index of the row

Question

I have a pandas DataFrame (the actual data set is far larger and contains numbers from 1-50):

          date           main   N1  N2  N3  N4  N5
0   2020-09-18  7-12-14-40-42   7   12  14  40  42
1   2020-09-11  2-5-24-43-45    2   5   24  43  45
2   2020-09-04  5-23-28-38-49   5   23  28  38  49
3   2020-08-28  8-11-22-38-41   8   11  22  38  41
4   2020-08-21  26-27-30-46-49  26  27  30  46  49

I want to return the row index for the first occurrence of each number. So far the only way that I have been able to achieve this is by "manually" using

lotteryData.loc[(lotteryData.N5==1)].head(49)

which in this example gives row index number 2. This is obviously very clumsy and does not take advantage of the Pandas DataFrame capability at all. Is there a way of iterating through the list in the format 5-23-28-38-49 directly to capture this information or a way to iterate through the columns to find the first occurrence of all numbers between 1 and 50

Answer 1

We can do stack the drop_duplicates

out = df.loc[:,'N2':].stack().drop_duplicates()
0  N2    12
   N3    14
   N4    40
   N5    42
1  N2     5
   N3    24
   N4    43
   N5    45
2  N2    23
   N3    28
   N4    38
   N5    49
3  N2    11
   N3    22
   N5    41
4  N2    27
   N3    30
   N4    46
dtype: int64