Here we will calculate totals by occasion, user, and day.
This will be useful if a researcher wants to look at the sum of each eating occasion per participant. In contrast, the totals file we generated summed all the occasions of a certain day into one datapoint.
Name the path to DietR directory where input files are pulled.
main_wd <- "~/GitHub/DietR"Load the necessary functions.
source("lib/specify_data_dir.R")
source("lib/calc_ASA24totals_by_occasion.R")You can come back to the main directory by:
setwd(main_wd)Specify the directory where the data is.
SpecifyDataDirectory(directory.name= "eg_data/VVKAJ/")Load your items data.
items_f_id_s_m_QCed <- read.delim("VVKAJ_Items_f_id_s_m_QCed.txt", sep="\t", header=T)Generate sum of foods consumed by each user, by day, and by occasion.
Output will be saved as: Items_by_User_Occ.
SumByOccasion(items.data=items_f_id_s_m_QCed, User.Name='UserName',
Recall.No='RecallNo', Occ.No='Occ_No')Take a look at the first 10 rows of the first 6 columns.
Items are summed by occasion number for each participant’s RecallNo.
Items_by_User_Occ[1:10, 1:6]## User_Day_OccNo UserName RecallNo Occ_No FoodAmt KCAL
## 1 VVKAJ101_1_1 VVKAJ101 1 1 510.60 626.2670
## 2 VVKAJ101_1_2 VVKAJ101 1 2 252.00 0.0000
## 3 VVKAJ101_1_3 VVKAJ101 1 3 249.75 366.0425
## 4 VVKAJ101_1_4 VVKAJ101 1 4 651.65 539.1745
## 5 VVKAJ101_1_5 VVKAJ101 1 5 738.50 783.4200
## 6 VVKAJ101_2_1 VVKAJ101 2 1 509.50 337.6500
## 7 VVKAJ101_2_2 VVKAJ101 2 2 415.00 177.4900
## 8 VVKAJ101_2_3 VVKAJ101 2 3 155.00 139.5000
## 9 VVKAJ101_2_4 VVKAJ101 2 4 304.15 258.9555
## 10 VVKAJ101_2_5 VVKAJ101 2 5 288.00 0.0000The Items_by_User_Occ function adds occasion names (breakfast, snacks etc.) to items.data.
Output will be saved as: Sum_by_User_Day_Occ.
AddOccNames(items.data=items_f_id_s_m_QCed, User.Name='UserName',
Recall.No='RecallNo', Occ.No='Occ_No', Occ.Name='Occ_Name')The output Sum_by_User_Day_Occ has the sum of foods consumed by each user, day, and occasion, with occasion names in words.
Take a look at the first 6 rows. Spelled-out occasion names corresponding to occasion name have been added at the end.
head(Sum_by_User_Day_Occ)## User_Day_OccNo UserName RecallNo Occ_No FoodAmt KCAL PROT TFAT
## 1 VVKAJ101_1_1 VVKAJ101 1 1 510.60 626.2670 9.80520 12.29440
## 2 VVKAJ101_1_2 VVKAJ101 1 2 252.00 0.0000 0.00000 0.00000
## 3 VVKAJ101_1_3 VVKAJ101 1 3 249.75 366.0425 15.50113 29.88700
## 4 VVKAJ101_1_4 VVKAJ101 1 4 651.65 539.1745 26.30972 3.04656
## 5 VVKAJ101_1_5 VVKAJ101 1 5 738.50 783.4200 28.54115 37.74925
## 6 VVKAJ101_2_1 VVKAJ101 2 1 509.50 337.6500 11.35115 7.59715
## CARB MOIS ALC CAFF THEO SUGR FIBE CALC IRON
## 1 127.39081 358.4300 0 26.784 0 62.543290 12.76850 52.0460 18.27292
## 2 0.00000 251.7480 0 0.000 0 0.000000 0.00000 7.5600 0.00000
## 3 10.44857 190.2593 0 0.000 0 4.002825 4.18575 149.2175 3.96320
## 4 112.74497 502.1475 0 0.000 0 68.438860 11.69125 289.2370 2.89618
## 5 87.21295 577.0344 0 0.000 0 9.223500 23.98000 391.7850 6.14970
## 6 56.95900 428.4122 0 76.800 0 27.929000 5.42250 262.2300 1.62895
## MAGN PHOS POTA SODI ZINC COPP SELE VC
## 1 107.0550 345.879 424.0100 308.8130 2.751890 0.4731170 43.95210 2.7230
## 2 2.5200 0.000 0.0000 10.0800 0.025200 0.0252000 0.00000 0.0000
## 3 95.6800 270.885 666.8725 491.0725 2.268950 0.2304475 31.64950 55.9875
## 4 195.6315 497.930 2013.7475 104.4170 2.550075 0.5184195 11.84765 70.7256
## 5 188.5000 672.760 1510.7700 1384.2800 4.180400 0.6888000 26.46600 79.5960
## 6 101.7700 334.690 669.5650 262.8800 1.837000 0.2415200 19.57600 81.2500
## VB1 VB2 NIAC VB6 FOLA FA FF FDFE
## 1 0.7595200 0.8724350 10.508905 1.1006350 206.785 179.92 26.865 333.665
## 2 0.0000000 0.0000000 0.000000 0.0000000 0.000 0.00 0.000 0.000
## 3 0.2496500 0.6627575 1.249625 0.3829275 178.535 0.00 178.535 178.535
## 4 0.4174145 1.0105790 3.330598 1.6560110 182.521 0.00 182.521 182.521
## 5 0.4558950 0.4255350 3.638800 0.6902500 151.525 0.00 151.525 151.525
## 6 0.5046850 0.8888150 5.556840 0.6375500 121.865 85.07 36.795 181.555
## VB12 VARA RET BCAR ACAR CRYP LYCO LZ ATOC
## 1 3.01600 449.1700 447.200 32.780 0.0000 1.040 0.00 209.460 1.242400
## 2 0.00000 0.0000 0.000 0.000 0.0000 0.000 0.00 0.000 0.000000
## 3 1.01010 467.9200 134.310 3994.325 1.4400 18.070 13.35 7889.358 3.043125
## 4 0.84672 255.4215 30.240 2660.808 93.3965 21.168 0.00 5640.164 1.630535
## 5 0.29920 89.1550 61.435 316.635 11.8800 15.840 0.00 534.600 3.935250
## 6 2.23350 103.4300 82.350 225.435 7.0000 28.875 353.50 140.035 0.536400
## VK CHOLE SFAT S040 S060 S080 S100 S120
## 1 18.4420 0.000 1.092205 0.000000 0.000000 0.000000 0.000000 0.002080
## 2 0.0000 0.000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
## 3 363.2695 340.770 6.033577 0.000000 0.000000 0.002220 0.002220 0.002887
## 4 234.5353 9.072 1.338515 0.039312 0.027216 0.021168 0.032600 0.037984
## 5 58.4045 26.125 10.231760 0.271590 0.083435 0.094215 0.195525 0.143110
## 6 3.8620 18.300 3.928790 0.137250 0.137250 0.137250 0.137250 0.149775
## S140 S160 S180 MFAT M161 M181 M201 M221
## 1 0.0020800 0.834455 0.216755 6.1216350 0.005090 6.0750550 0.037440 0.00104
## 2 0.0000000 0.000000 0.000000 0.0000000 0.000000 0.0000000 0.000000 0.00000
## 3 0.0595570 4.189893 1.573217 8.7545500 0.308750 8.3356900 0.084170 0.00777
## 4 0.1298365 0.834111 0.190963 0.4705195 0.050816 0.4136555 0.000000 0.00000
## 5 1.0552850 5.589870 2.149125 12.7942100 0.374660 12.1712800 0.113355 0.00000
## 6 0.5504950 1.958100 0.698240 1.8666400 0.004975 1.8318600 0.000000 0.00000
## PFAT P182 P183 P184 P204 P205 P225 P226 VITD
## 1 3.498815 3.2158550 0.2829600 0 0.000000 0.00000 0 0.00000 1.9760
## 2 0.000000 0.0000000 0.0000000 0 0.000000 0.00000 0 0.00000 0.0000
## 3 12.797260 11.2482050 1.3573275 0 0.143857 0.00444 0 0.03441 1.9980
## 4 0.526016 0.3288785 0.1971375 0 0.000000 0.00000 0 0.00000 0.9072
## 5 12.136520 10.4085300 1.6884450 0 0.014080 0.00000 0 0.00000 0.0000
## 6 0.846860 0.6657100 0.1811500 0 0.000000 0.00000 0 0.00000 2.3790
## CHOLN VITE_ADD B12_ADD F_TOTAL F_CITMLB F_OTHER F_JUICE V_TOTAL V_DRKGR
## 1 36.0993 0 3.016 0.659950 0.65995 0.000000 0.0000 0.000000 0.00000
## 2 0.0000 0 0.000 0.000000 0.00000 0.000000 0.0000 0.000000 0.00000
## 3 293.9523 0 0.000 0.000000 0.00000 0.000000 0.0000 1.732125 0.99120
## 4 113.8396 0 0.000 3.337895 0.00000 3.035495 0.3024 0.635040 0.63504
## 5 128.6725 0 0.000 0.039600 0.00000 0.000000 0.0396 1.289200 0.03960
## 6 47.7865 0 1.410 0.630000 0.30625 0.323750 0.0000 0.000000 0.00000
## V_REDOR_TOTAL V_REDOR_TOMATO V_REDOR_OTHER V_STARCHY_TOTAL V_STARCHY_POTATO
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## 6 0 0 0 0 0
## V_STARCHY_OTHER V_OTHER V_LEGUMES G_TOTAL G_WHOLE G_REFINED PF_TOTAL
## 1 0 0.000000 0.00000 2.7456 2.6520 0.0936 0.7384
## 2 0 0.000000 0.00000 0.0000 0.0000 0.0000 0.0000
## 3 0 0.740925 0.00000 0.0000 0.0000 0.0000 2.3733
## 4 0 0.000000 0.00000 0.0000 0.0000 0.0000 0.0000
## 5 0 1.249600 1.25675 2.6928 0.0000 2.6928 0.0000
## 6 0 0.000000 0.00000 1.1797 0.5969 0.5828 0.0000
## PF_MPS_TOTAL PF_MEAT PF_CUREDMEAT PF_ORGAN PF_POULT PF_SEAFD_HI PF_SEAFD_LOW
## 1 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0
## PF_EGGS PF_SOY PF_NUTSDS PF_LEGUMES D_TOTAL D_MILK D_YOGURT D_CHEESE OILS
## 1 0.0000 0 0.7384 0.00000 0.00000 0.00000 0 0.0000 6.0736
## 2 0.0000 0 0.0000 0.00000 0.00000 0.00000 0 0.0000 0.0000
## 3 1.8093 0 0.5640 0.00000 0.00000 0.00000 0 0.0000 18.2068
## 4 0.0000 0 0.0000 0.00000 0.78624 0.21168 0 0.0000 0.0000
## 5 0.0000 0 0.0000 4.93515 0.55440 0.00000 0 0.5544 22.4840
## 6 0.0000 0 0.0000 0.00000 0.75030 0.75030 0 0.0000 0.0000
## SOLID_FATS ADD_SUGARS A_DRINKS Occ_Name Occ_In_Words
## 1 0.00000 12.53787 0 1 Breakfast
## 2 0.00000 0.00000 0 7 Just a drink
## 3 4.85070 0.00000 0 3 Lunch
## 4 0.78624 0.00000 0 6 Snack
## 5 8.94520 0.00000 0 4 Dinner
## 6 4.83120 2.27480 0 1 BreakfastSave Sum_by_User_Day_Occ as a txt file.
write.table(Sum_by_User_Day_Occ, 'VVKAJ_Sum_by_User_Day_Occ.txt', sep="\t", row.names=F, quote=F)Come back to the main directory before you start running another script.
setwd(main_wd)