python - Filter data using pandas -

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i have data

     id       date                  sec        buy 5211153  2016-06-13 18:48:55             119    1   5211153  2016-06-13 18:50:54              66    0   5211153  2016-06-13 18:57:09               2    1   5211154  2016-06-13 18:57:12             118    0   5211154  2016-06-13 18:59:08              20    0   5211154  2016-06-13 18:59:34              25    0   5211154  2016-06-13 18:59:59              11    0   5211154  2016-06-13 19:00:11              12    1

i want print data buy = 0 before every buy = 1. try code

for i, (id, date, buy) in enumerate(zip(ids, dates, buys)):     if buys[i] == 1:          print ids[i], dates[i]          while buys[i-1] != 1:             print dates[i - 1], buys[i - 1]

but return not want desire output:

5211153  2016-06-13 18:57:09      1: 5211153  2016-06-13 18:50:54   5211154  2016-06-13 19:00:11      1: 5211154  2016-06-13 18:57:12    5211154  2016-06-13 18:59:08      5211154  2016-06-13 18:59:34     5211154  2016-06-13 18:59:59

update: should work current sample df, i'm not sure have alternate ones , zeroes in buy column (for example if have following sequence in buy column belonging same id: 1,0,1,1,0 - desired output in case?)

in [20]: df.sort_values(['id', 'date'],ascending=[1,0])[df.sort_values(['id', 'date'], ascending=[1,0]).groupby('id')['buy'].cumsum() < 2] out[20]:         id                date  sec  buy 2  5211153 2016-06-13 18:57:09    2    1 1  5211153 2016-06-13 18:50:54   66    0 7  5211154 2016-06-13 19:00:11   12    1 6  5211154 2016-06-13 18:59:59   11    0 5  5211154 2016-06-13 18:59:34   25    0 4  5211154 2016-06-13 18:59:08   20    0 3  5211154 2016-06-13 18:57:12  118    0

old answer:

iiuc can way:

df.loc[(df.buy==0) & (df.buy.shift(-1)==1)]

yields:

in [77]: df.loc[(df.buy==0) & (df.buy.shift(-1)==1)] out[77]:         id                date  sec  buy 1  5211153 2016-06-13 18:50:54   66    0 6  5211154 2016-06-13 18:59:59   11    0

please post desired data set if need else


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