每次在 pandas dataframe 中满足某个条件时如何增加一个值

Question

I have a df that looks like this:

time  val
0      1
1      1
2      2
3      3
4      1
5      2

How do I create new columns that hold the cumulative sum of occurance of a condition? In this case, I want to create a column for each unique value in val that holds the cumulative sum at the given row of occurences. See below:

time  val  sum_1   sum_2    sum_3
0      1    1        0       0 
1      1    2        0       0
2      2    2        1       0
3      3    2        1       1
4      1    3        1       1
5      2    3        2       1

Answer 1

You can assign() the result of each cumsum() to its own column:

df = df.assign(**{f'sum_{v}': df.val.eq(v).cumsum() for v in df.val.unique()})

#    time  val  sum_1  sum_2  sum_3
# 0     0    1      1      0      0
# 1     1    1      2      0      0
# 2     2    2      2      1      0
# 3     3    3      2      1      1
# 4     4    1      3      1      1
# 5     5    2      3      2      1

Answer 2

df['sum_1'] = (df['val'] == 1).cumsum()
df['sum_2'] = (df['val'] == 2).cumsum()
df['sum_3'] = (df['val'] == 3).cumsum()

gives

   time  val  sum_1  sum_2  sum_3
0     0    1      1      0      0
1     1    1      2      0      0
2     2    2      2      1      0
3     3    3      2      1      1
4     4    1      3      1      1
5     5    2      3      2      1