How to make flag column value 1 when 5 consective rows in other column are 1-CodePudding

I have one datafrmae which includes two columns flag and flag1, i want to check if flag column values greater than 1 for 5 times or greater than 5 times continuous flag1 value should change to 1

here is example

df=pd.DataFrame({'flag':[0,0,1,1,1,1,1,1,1,0,0,0],'flag1':[0,0,0,0,0,0,1,0,0,0,0,0]})

CodePudding user response：

Idea is create consecutive counts and then test 5 if equal:

a = df['flag'].eq(1)
#https://stackoverflow.com/a/52718619/2901002
b = a.cumsum()
df['new'] = b.sub(b.mask(a).ffill().fillna(0)).eq(5).astype(int)


print (df)
    flag  flag1  new
0      0      0    0
1      0      0    0
2      1      0    0
3      1      0    0
4      1      0    0
5      1      0    0
6      1      1    1
7      1      0    0
8      1      0    0
9      0      0    0
10     0      0    0
11     0      0    0

Detail:

print (b.sub(b.mask(a).ffill().fillna(0)))
0     0.0
1     0.0
2     1.0
3     2.0
4     3.0
5     4.0
6     5.0
7     6.0
8     7.0
9     0.0
10    0.0
11    0.0
Name: flag, dtype: float64

CodePudding user response：

setup

import pandas as pd
df=pd.DataFrame({'flag':[0,0,1,1,1,1,1,1,1,0,0,0],'flag1':[0,0,0,0,0,0,1,0,0,0,0,0]})

solution

rolling_sum = df["flag"].rolling(5).sum()
df["check"] = ((rolling_sum == 5) & (rolling_sum.diff() == 1)).astype(int)

    flag  flag1  check
0      0      0      0
1      0      0      0
2      1      0      0
3      1      0      0
4      1      0      0
5      1      0      0
6      1      1      1
7      1      0      0
8      1      0      0
9      0      0      0
10     0      0      0
11     0      0      0