I have dataframe like this:
| point | switch_on |
|---|---|
| A | True |
| B | True |
| C | True |
| A | False |
| D | False |
| N | True |
| O | False |
| O | False |
| S | False |
I want to add another column which will determine groups of rows that contain the same boolean before switching. Like this:
| point | switch_on | group |
|---|---|---|
| A | True | 1 |
| B | True | 1 |
| C | True | 1 |
| A | False | 2 |
| D | False | 2 |
| N | True | 3 |
| O | False | 4 |
| O | False | 4 |
| S | False | 4 |
Identify every time there's a change:
df.switch_on doesn't equal the previous value df.switch_on.shift().Then take the cumsum:
True is interpreted as 1, and False as 0.df['group'] = df.switch_on.ne(df.switch_on.shift()).cumsum()
print(df)
Output:
point switch_on group
0 A True 1
1 B True 1
2 C True 1
3 A False 2
4 D False 2
5 N True 3
6 O False 4
7 O False 4
8 S False 4