Grouping items by time-series bins in Python

Question

I have data that looks like:

[[datetime1, label1],
 [datetime2, label2],
 [datetime3, label3]]

The labels are strings. I have a binning parameter (delta) that's a datetime.timedelta.

What I'm trying to do:

1. Come up with the set of datetime bins, equally spaced by delta. In other words, below, datetimebin2 - datetimebin1 = datetimebin3 - datetimebin2 = delta .
2. Bin the labels into those bins.

So I would end up with something like:

[[datetimebin1, [label1, label2],
 [datetimebin2, []],
 [datetimebin3, []],
 [datetimebin4, [label3]]

I've been pointed to pandas, but haven't found what I'm looking for. Any help is much appreciated!

Answer 1

Something along these lines should do:

# data: a lists of lists (length 2) of measurements
# res: resulting list of lists
# delta: time delta

# output list (will be a list of lists, as in the question

res = []
# end of first bin:
binstart = data[0][0]
res.append([binstart, []])

# iterate through the data item
for d in data:
    # if the data item belongs to this bin, append it into the bin
    if d[0] < binstart + delta:
        res[-1][1].append(d[1])
        continue

    # otherwise, create new empty bins until this data fits into a bin
    binstart += delta
    while d[0] > binstart + delta:
        res.append([binstart, [])
        binstart += delta

    # create a bin with the data
    res.append([binstart, [d[1]]])