def createFeatures():
"""
This is just a sample script function showing the functionality of
widen_on_fields
avg_and_max_fields
"""
data = clean.readH5Store("HHP_release3.h5")
claim = data["claim"]
drug = data["drug"]
lab = data["lab"]
member = data["member"]
dih = data["dih"]
dih = dih.join(pd.DataFrame({"Year":np.repeat("Y1",len(dih.index))}))
dih_3 = data["dih_y3"]
dih_3 = dih_3.join(pd.DataFrame({"Year":np.repeat("Y2",len(dih_3.index))}))
days_in_hospital = dih.append(dih_3)
days_in_hospital = days_in_hospital.set_index(["MemberID","Year"])
days_in_hospital.columns = ["NextYearTruncated","Target"]
drug = member.merge(drug,on="MemberID")
drug_lab = drug.merge(lab,how="outer",on=["MemberID","Year","DSFS"])
drug_start = datetime.datetime.now()
drug_lab_count = count_drug_lab(drug_lab)# now indexed by MemberID and Year
drug_end = datetime.datetime.now()
logging.debug("drug_done. IT took %d seconds" % (drug_end - drug_start).seconds)
claim_counting_fields = [["Specialty","PlaceSvc"],"LengthOfStay", "PrimaryConditionGroup", "CharlsonIndex","ProcedureGroup"]
widen_start = datetime.datetime.now()
claims_counted = widen_on_fields(claim,claim_counting_fields)
widen_end = datetime.datetime.now()
logging.debug("widen_done. it took %d seconds"% (widen_end - widen_start).seconds)
avg_fields = ["PayDelay"]
avg_start = datetime.datetime.now()
avg_frame = avg_and_max_fields(claim,avg_fields)
avg_end = datetime.datetime.now()
logging.debug("avg_done. it took %d seconds" % (avg_end - avg_start).seconds)
features_frame = drug_lab_count.join(claims_counted,how="outer").join(avg_frame,how="outer").join(days_in_hospital,how="outer")
data["features"] = features_frame
clean.storeAsH5("HHP_release3.h5",data)
#!/usr/bin/env python
import clean
data = clean.loadRawData('./data')
clean.storeAsH5('HHP_release3.h5', data)
