Merge branch 'master' of https://git.uwaterloo.ca/pjentsch/covidalertabm

CovidAlertVaccinationModel/data/canada-network-data/Timeuse/Community/CData.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on 2021-02-08
+
+Short script to organize the community duration data from the timeuse survey.
+Community = non-household
+Aggregates reported durations according to age bracket of respondent
+Duration keys 206, 207, 208 and 209 must be aggregated using the expected coverage
+derived from the Intervals model. 
+
+@author: mark
+"""
+import numpy as np
+import pandas as pd
+import Intervals_Model as INT
+import itertools
+def Flatten(A):
+    return list(itertools.chain.from_iterable(A))
+
+#  load the full dataset.
+Maindf = pd.read_csv("../gss-89M0034-E-2015-c-29-main_F2.csv")
+
+#create the community dataframe
+commdf = Maindf[['PUMFID','WGHT_PER', 'AGEGR10', 'DURS206', 'DURS207',
+                 'DURS208', 'DURS209']].copy()
+
+# Function to add age bracket of respondent
+def BRACADD(row):
+    age = row['AGEGR10']
+    if age ==1 :
+        return 'Y'
+    elif age < 6:
+        return 'M'
+    else:
+        return 'O'
+
+# Function to add the aggregated duration
+durkeys = ['DURS206', 'DURS207', 'DURS208', 'DURS209']
+def DURSADD(row):
+    durs = row[durkeys].to_numpy()
+    rounded = [int(np.around(durs[i]/10)) for i in range(len(durs))]
+    out = np.round(np.average(INT.TotDurSample(50, [60,12], rounded)))
+    return out
+
+def COMBINED(row):
+    return pd.Series(BRACADD(row)).append(pd.Series(DURSADD(row)), ignore_index=True)
+
+commdf[['AGERESP', 'DUR']] = commdf.apply(COMBINED, axis=1)
+
+# Then slice the data by age
+Brac = ('Y', 'M', 'O')
+CData = {}
+for x in Brac:
+    DF = commdf
+    CData[x] = DF[DF['AGERESP']==x][['PUMFID','WGHT_PER', 'DUR']]
+    
+
+# Save to csv    
+for x in Brac:
+    Datadf = pd.DataFrame(CData[x])
+    Datadf.to_csv('CData'+x+'.csv', index=False)