Cumulative monthly values

Question

I have a python list containing several lists:

A = [['1/1/1999', '3.0'], ['1/2/1999', '4.5'], ['1/3/1999', '6.8'], ...... ...... ['12/31/1999', '8.7']] 

I need to combine all the values ​​corresponding to each month, preferably in the form of a dictionary containing months as keys and their values ​​as values.

Example:

  >>> A['1/99'] >>> ['3.0', '4.5', '6.8'.....] 

Or as a list of a list to:

Example:

  >>> A[0] >>> ['3.0', '4.5', '6.8'.....] 

Thanks.

Answer 1

  from collections import defaultdict from datetime import date month_aggregate = defaultdict (list) for [d,v] in A: month, day, year = map(int, d.split('/')) date = date (year, month, 1) month_aggregate [date].append (v) 

I repeat every date and value, I pull out the year and month and create a date with these values. Then I add the value to the list associated with this year and month.

Alternatively, if you want to use a string as a key, you can

  from collections import defaultdict month_aggregate = defaultdict (list) for [d,v] in A: month, day, year = d.split('/') month_aggregate [month + "/" + year[2:]].append (v) 

Answer 2

Pandas is perfect for this if you don't mind another dependency:

For instance:

 import pandas import numpy as np # Generate some data dates = pandas.date_range('1/1/1999', '12/31/1999') values = (np.random.random(dates.size) - 0.5).cumsum() df = pandas.DataFrame(values, index=dates) for month, values in df.groupby(lambda x: x.month): print month print values 

The true neat thing, however, is the aggregation of a grouped DataFrame. For example, if we want to see the min, max, and mean values, grouped by month:

 print df.groupby(lambda x: x.month).agg([min, max, np.mean]) 

This gives:

  min max mean 1 -0.812627 1.247057 0.328464 2 -0.305878 1.205256 0.472126 3 1.079633 3.862133 2.264204 4 3.237590 5.334907 4.025686 5 3.451399 4.832100 4.303439 6 3.256602 5.294330 4.258759 7 3.761436 5.536992 4.571218 8 3.945722 6.849587 5.513229 9 6.630313 8.420436 7.462198 10 4.414918 7.169939 5.759489 11 5.134333 6.723987 6.139118 12 4.352905 5.854000 5.039873 

Answer 3

here is my solution without turning on

 def getKeyValue(lst): a = lst[0].split('/') return '%s/%s' % (a[0], a[2][2:]), lst[1] def createDict(lst): d = {} for e in lst: k, v = getKeyValue(e) if not k in d: d[k] = [v] else: d[k].append(v) return d A = [['1/1/1999', '3.0'], ['1/2/1999', '4.5'], ['1/3/1999', '6.8'], ['12/31/1999', '8.7']] print createDict(A) >>>{'1/99': ['3.0', '4.5', '6.8'], '12/99': ['8.7']}