P2D6: Open programming time

The age variable

[1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1126, 1999, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 4001, 4002, 4003, 4004, 4005, 4006, 4007, 4008, 4009, 4010, 4011, 4012, 4013, 4014, 4015, 4016, 4017, 4018, 4019, 4020, 4021, 4022, 4023, 4024, 4025, 4026, 4027, 5001, 5002, 5003, 5004, 5005, 5006, 5007, 5008, 5009, 5010, 5011, 5012, 5013, 5014, 5015, 5016, 5017, 5018, 5019, 5020, 5021, 5022, 5023, 5999, 6001, 6002, 6003, 6004, 6005, 6006, 6007, 6008, 6009, 6010, 6011, 6012, 6013, 6014, 6015, 6016, 6017, 6018, 6019, 6020, 6021, 6022, 6023, 6024, 6025, 6026, 6027, 6028, 6029, 6030, 6031, 6032, 6033, 6034, 6035, 6036, 6037, 6038, 6039, 6040, 6041, 6042, 6043, 6044, 6045, 6046, 6047, 6048, 6049, 6050, 6051, 6052, 6053, 6054, 6055, 6056, 6057, 6058, 6059, 6999, 9999]

R code

Don’t try to mimic the code. Try to write out the logic.

What numbers are an age?
What numbers are mapped to zero?
What numbers are mapped to missing?

538 Code

mutate(age = ifelse(
        substr(detail_age, 1, 1) == "1", 
        as.numeric(substr(detail_age, 2, 4)), # Year
        ifelse(detail_age == 9999, NA, 0)),
       age = ifelse(age == 999, NA, age))

Hathaway’s code

age = dplyr::case_when(
        stringr::str_sub(detail_age, 1, 1) == "1" ~
          as.numeric(stringr::str_sub(detail_age, 2, 4)),
        detail_age == 9999 ~ NA_real_,
        TRUE ~ 0),
      age = ifelse(age == 999, NA, age),
      year = year)

Python

Saving the pickle

Some Python snippets

Setting up the conditions to use with .assign().

gun_ids = ["W32", "W33", "W34", "X72", "X73", "X74", "U014", "X93", "X94", "X95", "Y22", "Y23", "Y24", "Y350"]

intent_cond = [
    (raw_file.underlying_cause.isin(["W32", "W33", "W34"])),
    (raw_file.underlying_cause.isin(["X72", "X73", "X74"])),
    (raw_file.underlying_cause.isin(["*U01.4", "X93", "X94", "X95",
          "Y350"])),
    (raw_file.underlying_cause.isin(["Y22", "Y23", "Y24"]))
]

intent_val = ["Accidental", "Suicide", "Homicide", "Undetermined"]

weapon_cond = [
    (raw_file.underlying_cause.isin(["W32", "X72", "X93", "Y22"])),
    (raw_file.underlying_cause.isin(["W33", "X73", "X94", "Y23"]))
]
weapon_val = ["Handgun", "Rifle"]

Our file save DataFrame

# %%
year = 2014
folder_path = "death_data"
# %%
l2 = str(year)[2:]
fnames = ["deaths", "guns", "suicide"]

tnames = pd.DataFrame({
    "folder":folder_path,
    "start_name":fnames,
    "year":l2
}).assign(
    name = lambda x: x.start_name + "_" + x.year,
    file_path_feather = lambda x: x.folder + "/" + x.name + ".feather",
    file_path_pickle = lambda x: x.folder + "/" + x.name + ".pkl",
)

Pulling value from Pandas DataFrame

tnames.query('start_name == "suicide"').file_path_pickle.to_numpy()[0]