python 3.x - A vectorized solution producing a new column in DataFrame that depends on conditions of existing columns and also the new column itself -

my current dataframe data follows:

df=pd.dataframe([[1.4,3.5,4.6],[2.8,5.4,6.4],[7.8,6.5,5.8]],columns=['t','i','m'])

    t     m 0  14  35  46 1  28  54  64 2  28  34  64 3  78  65  58 

my goal apply vectorized operations on df conditions follows (pseudo code):

new column of answer starts value of 1.

for row in df.itertuples():     if (m > i) & (answer in row-1 odd number):         answer in row = answer in row-1 + m     elif (m > i):         answer in row = answer in row-1 - m     else:         answer in row = answer in row-1 

the desired output follows:

    t     m  answer 0  14  35  46       1 1  28  54  59      60 2  78  12  58       2 3  78  91  48       2 

any elegant solution appreciated.