How to get the min and the max index where a pandas column has the same value

Question

I have the following pandas dataframe

foo = pd.DataFrame({'step': [1,2,3,4,5,6,7,8], 'val': [1,1,1,0,0,1,0,1]})

I would like to get the 1st and last step for each of the sequence of 1s in the val column. Explanation:

• The first sequence of ones happens at steps 1,2,3 -> first step is 1 last step is 3

• The second sequence of ones happens at step 6 -> first step is 6 last step is 6

• The last sequence of ones happens at step 8 -> first step is 8 last step is 8

So the output is the list [1,3,6,6,8,8]

Any ideas how to do that ?

Answer 1

foo.assign(col1=foo.val.diff().eq(1).cumsum()).query("val==1")\
    .groupby(['col1'],as_index=False).step.agg(['first','last'])\
    .stack().tolist()

output: [1, 3, 6, 6, 8, 8]

Answer 2

IIUC, you can use a groupby aggregation, flatten using numpy and convert to list:

# compute groups of consecutive numbers
group = foo['val'].ne(foo['val'].shift()).cumsum()

out = (foo
 .loc[foo['val'].eq(1), 'step']         # keep step only where vale is 1
 .groupby(group).agg(['first', 'last']) # get first and last
 .to_numpy().ravel().tolist()           # reshape
)

output: [1, 3, 6, 6, 8, 8]