CODEWITHSUNDEEP
pythonpython-3.xpandas
Ajay Chinni
Ajay Chinni

Reputation: 840

Select only the bottom continuous rows where specific value is present Pandas

I have this data frame

lst = [['A',1],['B',0],['C',1],['D',0],['E',1],['F',1],['G',1]]
df = pd.DataFrame(lst,columns = ['name','val'])

Looks like this

  name  val
0    A    1
1    B    0
2    C    1
3    D    0
4    E    1
5    F    1
6    G    1

I want to get the rows where val is 1 but they should be bottom continuous rows.

Desired output

  name  val
4    E    1
5    F    1
6    G    1

I am doing, which will give all val with 1.

df[df.val == 1]

Upvotes: 1

Views: 48

Answers (2)

Landmaster
Landmaster

Reputation: 1053

Another way to do this is by taking the bit difference and seeing the last time it goes from 0 to 1, and using that as an index to the array.

df.iloc[(df.val.diff().drop_duplicates(keep='last') == 1)
           .idxmax():]

Output:

  name  val
4    E    1
5    F    1
6    G    1

Upvotes: 1

Quang Hoang
Quang Hoang

Reputation: 150745

You can use cumsum to get the last block:

# blocks separated by `0`
s = df.val.ne(1).cumsum()

# last blocks and only value 1
df[s.eq(s.max()) & df['val'].eq(1)]

Output:

  name  val
4    E    1
5    F    1
6    G    1

Upvotes: 2

Related Questions