python - Query in pandas for closest object (in time) which meets a set of conditions -

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i using pandas manage set of files have several properties:

import pandas pd  data = {'objtype'   : ['bias', 'bias', 'flat', 'flat', 'stdstar', 'flat', 'arc', 'target1', 'arc', 'flat', 'flat', 'flat', 'bias', 'bias'],          'ut'        :  pd.date_range("11:00", "12:05", freq="5min").values,         'position'  : ['p0', 'p0', 'p0', 'p0', 'p1', 'p1','p1', 'p2','p2','p2', 'p0', 'p0', 'p0', 'p0']}  df   = pd.dataframe(data=data)

which gives me dataframe one:

    objtype position                  ut 0      bias       p0 2016-07-15 11:00:00 1      bias       p0 2016-07-15 11:05:00 2      flat       p0 2016-07-15 11:10:00 3      flat       p0 2016-07-15 11:15:00 4   stdstar       p1 2016-07-15 11:20:00 5      flat       p1 2016-07-15 11:25:00 6       arc       p1 2016-07-15 11:30:00 7   target1       p2 2016-07-15 11:35:00 8       arc       p2 2016-07-15 11:40:00 9      flat       p2 2016-07-15 11:45:00 10     flat       p0 2016-07-15 11:50:00 11     flat       p0 2016-07-15 11:55:00 12     bias       p0 2016-07-15 12:00:00 13     bias       p0 2016-07-15 12:05:00

i index objects meet temporal condition in addition one. example:

i want the closest object target1 objtype 'arc'. query 2 candidates: 6 , 8.

if example query closest object target1 objtype 'arc' , shares same position (p2). 8.

i trying slice data frame according initial conditions , using numpy making non-pythonic mess.

any advice?

let's build function

def get_closest(df, idx, bool_cond, to_this):     others = df.loc[bool_cond, to_this]     target = df.loc[idx, to_this]     return df.ix[(others - target).abs().idxmin()]

first, assume when looking somethihg closest else have unique index. if don't, it. in case, index 7 corresponding value 'target1'. next, build boolean series representing conditions care about.

cond1 = df.objtype == 'arc' cond2 = df.position == df.loc[7, 'position']

then can call our function like:

get_closest(df, 7, cond1, 'ut')  objtype                     arc position                     p1 ut          2016-07-15 11:30:00 name: 6, dtype: object

perfect! mentioned there 2 items close, didn't care deliver both. i'll leave exercise you. function did deliver row closest , satisfied conditions.

what about:

get_closest(df, 7, cond1 & cond2, 'ut')  objtype                     arc position                     p2 ut          2016-07-15 11:40:00 name: 8, dtype: object

great! that's wanted.

explanation of get_closest

  • df dataframe care about.
  • idx index represents our target.
  • bool_cond true/false series slice our df
  • to_this column name use measure distance from.
def get_closest(df, idx, bool_cond, to_this):     # filter dataframe     others = df.loc[bool_cond, to_this]     # to_this value target row     target = df.loc[idx, to_this]     # index value smallest absolute difference     # , use resulting row     return df.ix[(others - target).abs().idxmin()]

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