One of the possibilities to process timeseries in python is to use a simple list.
For example, we can have a list of lists like this:
series1 = [ ['01/01/1900',0.0],['01/02/1900',0.1],['01/03/1900',0.3],['01/04/1900',0.4],['01/05/1900',2.2]...]
In this case, the ['01/01/1900',0.0] is composed of lists with a string representing the date, and a float number representing a value.
To properly make computations with dates, including sorting and grouping, it is necessary to interpret the string as a datetime format.
import datetime for i in series1: i[0]=datetime.datetime.strptime(i[0], '%m/%d/%Y')
datetime objects accepts being sorted, making possible to sort the list based on the date, for example:
series1.sort(key=lambda x: x[0])
And we can make sums or averages based on specific months or years:
#eg. List of year 1900 lst1900 = [item for item in series1 if item[0].year==1900] #Sum of 1900's values: sum1900 = sum[item[1] for item in series1 if item[0].year==1900] # avg of 1900's values avg1900 = sum1900 / float(len(lst1900))
