python 2.7 - Subtract value in one data frame from the next value in a second data frame -

i have data frame composed of several datasets (about 146 , counting). 2 of columns labeled "start_time" , "stop_time," represent start , stop of response (i.e., total duration of response). need "inter-response time" or start_time subtracted next corresponding value in start_time. if:

start_time = [1,4,7] stop_time = [2,5,8] 

i need:

stop_time[0] - start_time[1] stop_time[2] - start_time[3] 

in order get:

iri = [2,2] 

my code looks this:

iri_t = [] def grps():     grp in lset2_name_grps.groups:          beg_eng_t = pd.dataframe([lset2_name_grps.stop_time, lset2_name_grps.start_time], columns=['end_t','beg_t'])           end_t = [i in lset2_name_grps.stop_time]         beg_t = [i in lset2_name_grps.start_time]          beg_t = np.insert(beg_t, len(beg_t),0)         end_t = np.insert(end_t, 0,0)          iri_t.append(np.subtract(end_t, beg_t))  #         i,j in zip(end_t, beg_t): #             iri_t.append(np.subtract(i,j))   #         lset2_name_grps['iri'] = iri_t grps() 

essentially, doesn't close i'm trying accomplish , out either "not implemented" or error.

how this:

import pandas pd  starts = pd.series([1, 4, 7]) stops = pd.series([2, 5, 8]) iri_t = [0]  in range(1, len(starts)):     iri_t.append(starts[i] - ends[i-1])  times_df = pd.concat([starts, stops, pd.series(iri_t)], axis=1) 

this creates following data_frame:

   0  1  2 0  1  2  0 1  4  5  2 2  7  8  2