在 pandas df 中查找 A 列中的 True 值是否是自 B 列中最后一个 True 以来他的第一次出现

Question

I'm searching for the most efficient way to find if True value in column A is the first occurrence since last True value in column B . In this example the result would be column C .

df = pd.DataFrame({
    'A': [False, False, True, False, True, False, True, False, True],
    'B': [True, False, False, False, False, True, False, False, False],
    'C': [False, False, True, False, False, False, True, False, False]
})

	A	B	C
0	False	True	False
1	False	False	False
2	True	False	True
3	False	False	False
4	True	False	False
5	False	True	False
6	True	False	True
7	False	False	False
8	True	False	False

Answer 1

You can use a groupby operation on the cumulative sum of column "B" to group your dataframe how you described. Then you can use idxmax to get the index where each of those first occurrences exist within column "A". Once you have those indices, you can create your new column "C".

Using idxmax is a little trick because we're not actually interested in the maximum value since column "A" only ever has True and False as its values. idxmax will return the index of the first occurrence of the maximum (in this case, the first occurrence of True within each group), which is what we're specifically interested in.

df = pd.DataFrame({
    'A': [False, False, True, False, True, False, True, False, True],
    'B': [True, False, False, False, False, True, False, False, False],
})

indices = df["A"].groupby(df["B"].cumsum()).idxmax()
df["C"] = False
df.loc[indices, "C"] = True

print(df)
       A      B      C
0  False   True  False
1  False  False  False
2   True  False   True
3  False  False  False
4   True  False  False
5  False   True  False
6   True  False   True
7  False  False  False
8   True  False  False

Answer 2

What I've tried until now is:

is_occurred = False
def is_first_occurrence_since(column_to_check, column_occurence):
    global is_occurred
    if is_occurred and column_to_check == True:
        is_occurred = False
        return True
    elif not is_occurred and column_occurence == True:
        is_occurred = True
    return False
df.apply(lambda row: is_first_occurrence_since(row['A'], row['B']), axis=1)

Is there a better way?