How to change the Boolean between two similar Booleans in a column in dataframe-CodePudding

I am working on dataframes with different sizes. I need to change the 'True' Boolean in a column in a dataframe to 'False' boolean if the 'True' boolean found between two 'False' booleans at the same column in dataframe.

This is an example of one of dataframes:

df =

 index        DATE     S_N        A  timestamp  delta   time  \
0      7  2021-01-05  78          4 2021-01-05    NaT    NaN   
1      8  2021-01-07  78          3 2021-01-07 2 days   48.0   
2      9  2021-01-08  78          3 2021-01-08 1 days   24.0   
3     10  2021-01-10  78          3 2021-01-10 2 days   48.0   
4     11  2021-01-11  78          6 2021-01-11 1 days   24.0   
5     12  2021-01-12  78          5 2021-01-12 1 days   24.0   
6     13  2021-01-16  78          4 2021-01-16 4 days   96.0   
7     14  2021-01-17  78          4 2021-01-17 1 days   24.0   
8     15  2021-01-22  78          3 2021-01-22 5 days  120.0   
9     16  2021-01-24  78          3 2021-01-24 2 days   48.0   

   label_number_hours  
0                True  
1                True  
2               False  
3                True  
4               False  
5               False  
6                True  
7               False  
8                True  
9                True

This is what I am looking for:

df1 =

 index        DATE   S_N          A  timestamp  delta   time  \
0      7  2021-01-05  78          4 2021-01-05    NaT    NaN   
1      8  2021-01-07  78          3 2021-01-07 2 days   48.0   
2      9  2021-01-08  78          3 2021-01-08 1 days   24.0   
3     10  2021-01-10  78          3 2021-01-10 2 days   48.0   
4     11  2021-01-11  78          6 2021-01-11 1 days   24.0   
5     12  2021-01-12  78          5 2021-01-12 1 days   24.0   
6     13  2021-01-16  78          4 2021-01-16 4 days   96.0   
7     14  2021-01-17  78          4 2021-01-17 1 days   24.0   
8     15  2021-01-22  78          3 2021-01-22 5 days  120.0   
9     16  2021-01-24  78          3 2021-01-24 2 days   48.0   

   label_number_hours  
0                True  
1                True  
2               False  
3               False  
4               False  
5               False  
6               False  
7               False  
8                True  
9                True

This is my code:

df1 = df (subset = 'label_number_hours')

This is the result which I got:

0    False
1     True
2    False
3     True
4     True
5     True
6     True
7     True
8     True
9     True

I am looking to be the output similar to df1 as above.

I need really to your help

CodePudding user response：

You can find indices of all False values with np.where and overwrite boolean values between the first and the last one:

import pandas as pd
import numpy as np

df = pd.DataFrame([True, False, True, False, True, False, True], columns=["label_number_hours"])
df["some_other_column"] = np.random.rand(df.shape[0])

falses_idx, = np.where(~df["label_number_hours"])
if falses_idx.size > 0:
  df.iloc[falses_idx[0]:falses_idx[-1], df.columns.get_loc("label_number_hours")] = False