Keep all rows before first occurrence of a value

I have a pandas dataframe and the opposite question to Drop all rows before first occurrence of a value

Instead of drop all rows before the first occurence of a value, I want to keep the rows before the first occurence of a value. so for example, i want to keep all the rows before the occurence 1 in the column count:

Year  ID Count
1997  1  0
1998  2  0
1999  3  1
2000  4  0
2001  5  1

leads to:

Year  ID Count
1997  1  0
1998  2  0

>Solution :

Use cummax and negate its output (~) to form a boolean Series for boolean indexing:

out = df[~df['Count'].eq(1).cummax()]

Output:

   Year  ID  Count
0  1997   1      0
1  1998   2      0

Intermediates:

   Year  ID  Count  eq(1)  cummax      ~
0  1997   1      0  False   False   True
1  1998   2      0  False   False   True
2  1999   3      1   True    True  False
3  2000   4      0  False    True  False
4  2001   5      1   True    True  False

Variant, if you are sure that there is at least one 1:

out = df.iloc[:np.argmax(df['Count'].eq(1))]