dataframe - timespan between timestamps based on value of other column - pandas

Question

I have a pandas dataframe with the index containing years and a column containing dividend payouts. I now want to determine how many years the company has continuously paid out dividends (column dividend > 0).
As an example, for the following table I want the result to be 2 (2019+2018)
year dividend
2019 1.89
2018 1.70
2017 0
2016 1.5
And for this one 4
year dividend
2019 1.89
2018 1.70
2017 1.6
2016 1.58

Answer 1

Eventhough the below answer is a round about, yet it can solve your problem.
Convert it to pd.df and use idxmin() with ne() wrapper to find the continuous divident pay.
year dividend
2019 1.89
2018 1.70
2017 0
2016 1.5
df = pd.DataFrame({'dividend' : [1.89,1.70,0,1.5]}, index=[2019,2018,2017,2016])
print('Continuous Divident value :', df.loc[ : df.dividend.idxmin()].ne(0).sum()[0])
Continuous Divident value : 2
year dividend
2019 1.89
2018 1.70
2017 1.6
2016 1.58
df = pd.DataFrame({'dividend' : [1.89,1.70,1.6,1.58]}, index=[2019,2018,2017,2016])
print('Continuous Divident value :', df.loc[ : df.dividend.idxmin()].ne(0).sum()[0])
Continuous Divident value : 4
Edit
Based on your comment, I just played with loops, I hope this satisfy your requiremnts. If not let me know..
value = 0 if df['bool'].iloc[0] == 0 else (len(df) if len(df) == df.iloc[-1::]['bool'].values[0] else len(df.loc[: df[df['bool'].duplicated(keep = 'last')].index[0]]))
print('Continous divident value : ', value)