time series with alternative ways of index

Question

I am now processing time series like data which is in the following shape:

It has three columns say t_1, t_2, att. And t_1 and t_2 are ordered observations of time and att is numerical value.

Toy example of data:

    t_1           t_2        att
    12:30:32      12:33:12   1
    12:30:55      12:33:43   3
    12:31:21      12:34:34   2

The object I want to build is stick to the following rule:

1. If t_1 is "continuous" then I build a time series object with t_1 as time Index, att and t_2 as value.

2. If t_1 is not "continuous" and t_2 is "continuous" then I build a time series object with t_2 as time index, t_1 and att as value

3. If t_1 and t_2 both not continuous, then report message back and build nothing

4. define interval< 1 hour, say, as continuous

An example of non-continuous t_1 but continuous t_2:

    t_1           t_2        att
    12:30:32      12:33:12   1
    12:30:55      12:33:43   3
    14:31:21      12:34:34   2
    14:33:24      12:35:34   -12

Any ideas for implementation either in python or R will be super welcome. The data will be imported in as dataframe, either pandas dataframe or R dataframe.

Time series object like xts or ts in R

Answer 1

Hopefully, you can build time series objects from the tuples built from this:

import itertools as it
import datetime
data = [['12:30:32', '12:33:12', 1],
        ['12:30:55', '12:33:43', 3],
        ['14:31:21', '12:34:34', 2],
        ['14:33:24', '12:35:34', -12]]

def continuous(series, time_format = '%H:%M:%S', criteria = 3600):
    '''Returns True if time series is continuous.

    series -- sequence of strings
    time_format -- str (default '%H:%M:%S')
    criteria -- int (default 3600)
    '''
    # make datetime objects
    t = [datetime.datetime.strptime(thing, time_format) for thing in series]
    # find the deltas
    t2 = (two - one for one, two in it.izip(t, t[1:]))
    # apply the criteria
    return all(item.seconds <= criteria for item in t2)

# extract the time series data
one, two, values = zip(*data)
if continuous(one):
    # make tuples - (t1, (t2, att))
    time_series_data = [(t1, (t2, att)) for t1, t2, att in it.izip(one, two, values)]
elif continuous(two):
    # make tuples - (t2, (t1, att))
    time_series_data = [(t2, (t1, att)) for t1, t2, att in it.izip(one, two, values)]
else:
    raise ValueError('No Continuous Data')