#################################################################################################### # For: Norway # Paper: Mental Health Prevalences # Programmer: Renate Houts # File: # Date: 26-Sept-2023 # # Purpose: # RMH -- Redact cells based on < 10 people from files created in SAS # # ################################################################################################## # Load necessary libraries library(plyr) # Needed for mapvalues; plyr needs to be loaded before tidyverse library(tidyverse) # Needed for data wrangling # Read in data files person <- read.csv("M:/p1074-renateh/2023_DayInLifeGP/Work/Results/PersonLevel_Sept2023.csv") encounter <- read.csv("M:/p1074-renateh/2023_DayInLifeGP/Work/Results/EncounterLevel_Sept2023.csv") pers_enc <- full_join(person, encounter, by = "code", suffix = c(".p", ".e")) %>% filter(row_number() %in% c(1:48, 92:95)) %>% mutate(all_p.p = ifelse(all_n.p <= 10, NA, all_p.p), all_p.e = ifelse(all_n.p <= 10, NA, all_p.e), female_p.p = ifelse(female_n.p <= 10, NA, female_p.p), female_p.e = ifelse(female_n.p <= 10, NA, female_p.e), male_p.p = ifelse(male_n.p <= 10, NA, male_p.p), male_p.e = ifelse(male_n.p <= 10, NA, male_p.e)) %>% mutate(all_n.p = ifelse(all_n.p <= 10, NA, all_n.p), all_n.e = ifelse(all_n.e <= 10, NA, all_n.e), female_n.p = ifelse(female_n.p <= 10, NA, female_n.p), female_n.e = ifelse(female_n.e <= 10, NA, female_n.e), male_n.p = ifelse(male_n.p <= 10, NA, male_n.p), male_n.e = ifelse(male_n.e <= 10, NA, male_n.e)) min(pers_enc$all_n.p, na.rm = TRUE) min(pers_enc$female_n.p, na.rm = TRUE) min(pers_enc$male_n.p, na.rm = TRUE) person_age <- read.csv("M:/p1074-renateh/2023_DayInLifeGP/Work/Results/PersonLevel_age_Sept2023.csv") %>% select(age, tot_n, A_n, B_n, D_n, F_n, H_n, K_n, L_n, N_n, P_n, R_n, S_n, T_n, U_n, W_n, X_n, A_p, B_p, D_p, F_p, H_p, K_p, L_p, N_p, P_p, R_p, S_p, T_p, U_p, W_p, X_p, circ_n, endo_n, pulm_n, gast_n, urog_n, musc_n, hema_n, canc_n, neur_n, circ_p, endo_p, pulm_p, gast_p, urog_p, musc_p, hema_p, canc_p, neur_p, str_n, adhd_n, anx_n, dem_n, dep_n, dev_n, eat_n, phb_n, psy_n, ptsd_n, sex_n, slp_n, som_n, sub_n, sui_n, cha_n, con_n, per_n, chf_n, adl_n, stu_n, fea_n, irr_n, oth_n, str_p, adhd_p, anx_p, dem_p, dep_p, dev_p, eat_p, phb_p, psy_p, ptsd_p, sex_p, slp_p, som_p, sub_p, sui_p, cha_p, con_p, per_p, chf_p, adl_p, stu_p, fea_p, irr_p, oth_p, Pdx_n, infect_n, pain_n, injury_n, Pdx_p, infect_p, pain_p, injury_p) encounter_age <- read.csv("M:/p1074-renateh/2023_DayInLifeGP/Work/Results/EncounterLevel_age_Sept2023.csv") %>% select(age, enc_n, A_n, B_n, D_n, F_n, H_n, K_n, L_n, N_n, P_n, R_n, S_n, T_n, U_n, W_n, X_n, A_p, B_p, D_p, F_p, H_p, K_p, L_p, N_p, P_p, R_p, S_p, T_p, U_p, W_p, X_p, circ_n, endo_n, pulm_n, gast_n, urog_n, musc_n, hema_n, canc_n, neur_n, circ_p, endo_p, pulm_p, gast_p, urog_p, musc_p, hema_p, canc_p, neur_p, str_n, adhd_n, anx_n, dem_n, dep_n, dev_n, eat_n, phb_n, psy_n, ptsd_n, sex_n, slp_n, som_n, sub_n, sui_n, cha_n, con_n, per_n, chf_n, adl_n, stu_n, fea_n, irr_n, oth_n, str_p, adhd_p, anx_p, dem_p, dep_p, dev_p, eat_p, phb_p, psy_p, ptsd_p, sex_p, slp_p, som_p, sub_p, sui_p, cha_p, con_p, per_p, chf_p, adl_p, stu_p, fea_p, irr_p, oth_p, Pdx_n, infect_n, pain_n, injury_n, Pdx_p, infect_p, pain_p, injury_p) pers_enc_age <- full_join(person_age, encounter_age, by = "age", suffix = c(".p", ".e")) %>% mutate(A_p.p = ifelse(A_n.p <= 10, NA, A_p.p), B_p.p = ifelse(B_n.p <= 10, NA, B_p.p), D_p.p = ifelse(D_n.p <= 10, NA, D_p.p), F_p.p = ifelse(F_n.p <= 10, NA, F_p.p), H_p.p = ifelse(H_n.p <= 10, NA, H_p.p), K_p.p = ifelse(K_n.p <= 10, NA, K_p.p), L_p.p = ifelse(L_n.p <= 10, NA, L_p.p), N_p.p = ifelse(N_n.p <= 10, NA, N_p.p), P_p.p = ifelse(P_n.p <= 10, NA, P_p.p), R_p.p = ifelse(R_n.p <= 10, NA, R_p.p), S_p.p = ifelse(S_n.p <= 10, NA, S_p.p), T_p.p = ifelse(T_n.p <= 10, NA, T_p.p), U_p.p = ifelse(U_n.p <= 10, NA, U_p.p), W_p.p = ifelse(W_n.p <= 10, NA, W_p.p), X_p.p = ifelse(X_n.p <= 10, NA, X_p.p), A_p.e = ifelse(A_n.p <= 10, NA, A_p.e), B_p.e = ifelse(B_n.p <= 10, NA, B_p.e), D_p.e = ifelse(D_n.p <= 10, NA, D_p.e), F_p.e = ifelse(F_n.p <= 10, NA, F_p.e), H_p.e = ifelse(H_n.p <= 10, NA, H_p.e), K_p.e = ifelse(K_n.p <= 10, NA, K_p.e), L_p.e = ifelse(L_n.p <= 10, NA, L_p.e), N_p.e = ifelse(N_n.p <= 10, NA, N_p.e), P_p.e = ifelse(P_n.p <= 10, NA, P_p.e), R_p.e = ifelse(R_n.p <= 10, NA, R_p.e), S_p.e = ifelse(S_n.p <= 10, NA, S_p.e), T_p.e = ifelse(T_n.p <= 10, NA, T_p.e), U_p.e = ifelse(U_n.p <= 10, NA, U_p.e), W_p.e = ifelse(W_n.p <= 10, NA, W_p.e), X_p.e = ifelse(X_n.p <= 10, NA, X_p.e), circ_p.p = ifelse(circ_n.p <= 10, NA, circ_p.p), endo_p.p = ifelse(endo_n.p <= 10, NA, endo_p.p), pulm_p.p = ifelse(pulm_n.p <= 10, NA, pulm_p.p), gast_p.p = ifelse(gast_n.p <= 10, NA, gast_p.p), urog_p.p = ifelse(urog_n.p <= 10, NA, urog_p.p), musc_p.p = ifelse(musc_n.p <= 10, NA, musc_p.p), hema_p.p = ifelse(hema_n.p <= 10, NA, hema_p.p), canc_p.p = ifelse(canc_n.p <= 10, NA, canc_p.p), neur_p.p = ifelse(neur_n.p <= 10, NA, neur_p.p), circ_p.e = ifelse(circ_n.p <= 10, NA, circ_p.e), endo_p.e = ifelse(endo_n.p <= 10, NA, endo_p.e), pulm_p.e = ifelse(pulm_n.p <= 10, NA, pulm_p.e), gast_p.e = ifelse(gast_n.p <= 10, NA, gast_p.e), urog_p.e = ifelse(urog_n.p <= 10, NA, urog_p.e), musc_p.e = ifelse(musc_n.p <= 10, NA, musc_p.e), hema_p.e = ifelse(hema_n.p <= 10, NA, hema_p.e), canc_p.e = ifelse(canc_n.p <= 10, NA, canc_p.e), neur_p.e = ifelse(neur_n.p <= 10, NA, neur_p.e), Pdx_p.p = ifelse(Pdx_n.p <= 10, NA, Pdx_p.p), infect_p.p = ifelse(infect_n.p <= 10, NA, infect_p.p), pain_p.p = ifelse(pain_n.p <= 10, NA, pain_p.p), injury_p.p = ifelse(injury_n.p <= 10, NA, injury_p.p), Pdx_p.e = ifelse(Pdx_n.p <= 10, NA, Pdx_p.e), infect_p.e = ifelse(infect_n.p <= 10, NA, infect_p.e), pain_p.e = ifelse(pain_n.p <= 10, NA, pain_p.e), injury_p.e = ifelse(injury_n.p <= 10, NA, injury_p.e), str_p.p = ifelse(str_n.p <= 10, NA, str_p.p), adhd_p.p = ifelse(adhd_n.p <= 10, NA, adhd_p.p), anx_p.p = ifelse(anx_n.p <= 10, NA, anx_p.p), dem_p.p = ifelse(dem_n.p <= 10, NA, dem_p.p), dep_p.p = ifelse(dep_n.p <= 10, NA, dep_p.p), dev_p.p = ifelse(dev_n.p <= 10, NA, dev_p.p), eat_p.p = ifelse(eat_n.p <= 10, NA, eat_p.p), phb_p.p = ifelse(phb_n.p <= 10, NA, phb_p.p), psy_p.p = ifelse(psy_n.p <= 10, NA, psy_p.p), ptsd_p.p = ifelse(ptsd_n.p <= 10, NA, ptsd_p.p), sex_p.p = ifelse(sex_n.p <= 10, NA, sex_p.p), slp_p.p = ifelse(slp_n.p <= 10, NA, slp_p.p), som_p.p = ifelse(som_n.p <= 10, NA, som_p.p), sub_p.p = ifelse(sub_n.p <= 10, NA, sub_p.p), sui_p.p = ifelse(sui_n.p <= 10, NA, sui_p.p), cha_p.p = ifelse(cha_n.p <= 10, NA, cha_p.p), con_p.p = ifelse(con_n.p <= 10, NA, con_p.p), per_p.p = ifelse(per_n.p <= 10, NA, per_p.p), chf_p.p = ifelse(chf_n.p <= 10, NA, chf_p.p), adl_p.p = ifelse(adl_n.p <= 10, NA, adl_p.p), stu_p.p = ifelse(stu_n.p <= 10, NA, stu_p.p), fea_p.p = ifelse(fea_n.p <= 10, NA, fea_p.p), irr_p.p = ifelse(irr_n.p <= 10, NA, irr_p.p), oth_p.p = ifelse(oth_n.p <= 10, NA, oth_p.p), str_p.e = ifelse(str_n.p <= 10, NA, str_p.e), adhd_p.e = ifelse(adhd_n.p <= 10, NA, adhd_p.e), anx_p.e = ifelse(anx_n.p <= 10, NA, anx_p.e), dem_p.e = ifelse(dem_n.p <= 10, NA, dem_p.e), dep_p.e = ifelse(dep_n.p <= 10, NA, dep_p.e), dev_p.e = ifelse(dev_n.p <= 10, NA, dev_p.e), eat_p.e = ifelse(eat_n.p <= 10, NA, eat_p.e), phb_p.e = ifelse(phb_n.p <= 10, NA, phb_p.e), psy_p.e = ifelse(psy_n.p <= 10, NA, psy_p.e), ptsd_p.e = ifelse(ptsd_n.p <= 10, NA, ptsd_p.e), sex_p.e = ifelse(sex_n.p <= 10, NA, sex_p.e), slp_p.e = ifelse(slp_n.p <= 10, NA, slp_p.e), som_p.e = ifelse(som_n.p <= 10, NA, som_p.e), sub_p.e = ifelse(sub_n.p <= 10, NA, sub_p.e), sui_p.e = ifelse(sui_n.p <= 10, NA, sui_p.e), cha_p.e = ifelse(cha_n.p <= 10, NA, cha_p.e), con_p.e = ifelse(con_n.p <= 10, NA, con_p.e), per_p.e = ifelse(per_n.p <= 10, NA, per_p.e), chf_p.e = ifelse(chf_n.p <= 10, NA, chf_p.e), adl_p.e = ifelse(adl_n.p <= 10, NA, adl_p.e), stu_p.e = ifelse(stu_n.p <= 10, NA, stu_p.e), fea_p.e = ifelse(fea_n.p <= 10, NA, fea_p.e), irr_p.e = ifelse(irr_n.p <= 10, NA, irr_p.e), oth_p.e = ifelse(oth_n.p <= 10, NA, oth_p.e)) %>% mutate(A_n.p = ifelse(A_n.p <= 10, NA, A_n.p), B_n.p = ifelse(B_n.p <= 10, NA, B_n.p), D_n.p = ifelse(D_n.p <= 10, NA, D_n.p), F_n.p = ifelse(F_n.p <= 10, NA, F_n.p), H_n.p = ifelse(H_n.p <= 10, NA, H_n.p), K_n.p = ifelse(K_n.p <= 10, NA, K_n.p), L_n.p = ifelse(L_n.p <= 10, NA, L_n.p), N_n.p = ifelse(N_n.p <= 10, NA, N_n.p), P_n.p = ifelse(P_n.p <= 10, NA, P_n.p), R_n.p = ifelse(R_n.p <= 10, NA, R_n.p), S_n.p = ifelse(S_n.p <= 10, NA, S_n.p), T_n.p = ifelse(T_n.p <= 10, NA, T_n.p), U_n.p = ifelse(U_n.p <= 10, NA, U_n.p), W_n.p = ifelse(W_n.p <= 10, NA, W_n.p), X_n.p = ifelse(X_n.p <= 10, NA, X_n.p), A_n.e = ifelse(A_n.p <= 10, NA, A_n.e), B_n.e = ifelse(B_n.p <= 10, NA, B_n.e), D_n.e = ifelse(D_n.p <= 10, NA, D_n.e), F_n.e = ifelse(F_n.p <= 10, NA, F_n.e), H_n.e = ifelse(H_n.p <= 10, NA, H_n.e), K_n.e = ifelse(K_n.p <= 10, NA, K_n.e), L_n.e = ifelse(L_n.p <= 10, NA, L_n.e), N_n.e = ifelse(N_n.p <= 10, NA, N_n.e), P_n.e = ifelse(P_n.p <= 10, NA, P_n.e), R_n.e = ifelse(R_n.p <= 10, NA, R_n.e), S_n.e = ifelse(S_n.p <= 10, NA, S_n.e), T_n.e = ifelse(T_n.p <= 10, NA, T_n.e), U_n.e = ifelse(U_n.p <= 10, NA, U_n.e), W_n.e = ifelse(W_n.p <= 10, NA, W_n.e), X_n.e = ifelse(X_n.p <= 10, NA, X_n.e), circ_n.p = ifelse(circ_n.p <= 10, NA, circ_n.p), endo_n.p = ifelse(endo_n.p <= 10, NA, endo_n.p), pulm_n.p = ifelse(pulm_n.p <= 10, NA, pulm_n.p), gast_n.p = ifelse(gast_n.p <= 10, NA, gast_n.p), urog_n.p = ifelse(urog_n.p <= 10, NA, urog_n.p), musc_n.p = ifelse(musc_n.p <= 10, NA, musc_n.p), hema_n.p = ifelse(hema_n.p <= 10, NA, hema_n.p), canc_n.p = ifelse(canc_n.p <= 10, NA, canc_n.p), neur_n.p = ifelse(neur_n.p <= 10, NA, neur_n.p), circ_n.e = ifelse(circ_n.p <= 10, NA, circ_n.e), endo_n.e = ifelse(endo_n.p <= 10, NA, endo_n.e), pulm_n.e = ifelse(pulm_n.p <= 10, NA, pulm_n.e), gast_n.e = ifelse(gast_n.p <= 10, NA, gast_n.e), urog_n.e = ifelse(urog_n.p <= 10, NA, urog_n.e), musc_n.e = ifelse(musc_n.p <= 10, NA, musc_n.e), hema_n.e = ifelse(hema_n.p <= 10, NA, hema_n.e), canc_n.e = ifelse(canc_n.p <= 10, NA, canc_n.e), neur_n.e = ifelse(neur_n.p <= 10, NA, neur_n.e), Pdx_n.p = ifelse(Pdx_n.p <= 10, NA, Pdx_n.p), infect_n.p = ifelse(infect_n.p <= 10, NA, infect_n.p), pain_n.p = ifelse(pain_n.p <= 10, NA, pain_n.p), injury_n.p = ifelse(injury_n.p <= 10, NA, injury_n.p), Pdx_n.e = ifelse(Pdx_n.p <= 10, NA, Pdx_n.e), infect_n.e = ifelse(infect_n.p <= 10, NA, infect_n.e), pain_n.e = ifelse(pain_n.p <= 10, NA, pain_n.e), injury_n.e = ifelse(injury_n.p <= 10, NA, injury_n.e), str_n.p = ifelse(str_n.p <= 10, NA, str_n.p), adhd_n.p = ifelse(adhd_n.p <= 10, NA, adhd_n.p), anx_n.p = ifelse(anx_n.p <= 10, NA, anx_n.p), dem_n.p = ifelse(dem_n.p <= 10, NA, dem_n.p), dep_n.p = ifelse(dep_n.p <= 10, NA, dep_n.p), dev_n.p = ifelse(dev_n.p <= 10, NA, dev_n.p), eat_n.p = ifelse(eat_n.p <= 10, NA, eat_n.p), phb_n.p = ifelse(phb_n.p <= 10, NA, phb_n.p), psy_n.p = ifelse(psy_n.p <= 10, NA, psy_n.p), ptsd_n.p = ifelse(ptsd_n.p <= 10, NA, ptsd_n.p), sex_n.p = ifelse(sex_n.p <= 10, NA, sex_n.p), slp_n.p = ifelse(slp_n.p <= 10, NA, slp_n.p), som_n.p = ifelse(som_n.p <= 10, NA, som_n.p), sub_n.p = ifelse(sub_n.p <= 10, NA, sub_n.p), sui_n.p = ifelse(sui_n.p <= 10, NA, sui_n.p), cha_n.p = ifelse(cha_n.p <= 10, NA, cha_n.p), con_n.p = ifelse(con_n.p <= 10, NA, con_n.p), per_n.p = ifelse(per_n.p <= 10, NA, per_n.p), chf_n.p = ifelse(chf_n.p <= 10, NA, chf_n.p), adl_n.p = ifelse(adl_n.p <= 10, NA, adl_n.p), stu_n.p = ifelse(stu_n.p <= 10, NA, stu_n.p), fea_n.p = ifelse(fea_n.p <= 10, NA, fea_n.p), irr_n.p = ifelse(irr_n.p <= 10, NA, irr_n.p), oth_n.p = ifelse(oth_n.p <= 10, NA, oth_n.p), str_n.e = ifelse(str_n.p <= 10, NA, str_n.e), adhd_n.e = ifelse(adhd_n.p <= 10, NA, adhd_n.e), anx_n.e = ifelse(anx_n.p <= 10, NA, anx_n.e), dem_n.e = ifelse(dem_n.p <= 10, NA, dem_n.e), dep_n.e = ifelse(dep_n.p <= 10, NA, dep_n.e), dev_n.e = ifelse(dev_n.p <= 10, NA, dev_n.e), eat_n.e = ifelse(eat_n.p <= 10, NA, eat_n.e), phb_n.e = ifelse(phb_n.p <= 10, NA, phb_n.e), psy_n.e = ifelse(psy_n.p <= 10, NA, psy_n.e), ptsd_n.e = ifelse(ptsd_n.p <= 10, NA, ptsd_n.e), sex_n.e = ifelse(sex_n.p <= 10, NA, sex_n.e), slp_n.e = ifelse(slp_n.p <= 10, NA, slp_n.e), som_n.e = ifelse(som_n.p <= 10, NA, som_n.e), sub_n.e = ifelse(sub_n.p <= 10, NA, sub_n.e), sui_n.e = ifelse(sui_n.p <= 10, NA, sui_n.e), cha_n.e = ifelse(cha_n.p <= 10, NA, cha_n.e), con_n.e = ifelse(con_n.p <= 10, NA, con_n.e), per_n.e = ifelse(per_n.p <= 10, NA, per_n.e), chf_n.e = ifelse(chf_n.p <= 10, NA, chf_n.e), adl_n.e = ifelse(adl_n.p <= 10, NA, adl_n.e), stu_n.e = ifelse(stu_n.p <= 10, NA, stu_n.e), fea_n.e = ifelse(fea_n.p <= 10, NA, fea_n.e), irr_n.e = ifelse(irr_n.p <= 10, NA, irr_n.e), oth_n.e = ifelse(oth_n.p <= 10, NA, oth_n.e)) min(pers_enc_age$A_n.p, na.rm = TRUE) min(pers_enc_age$B_n.p, na.rm = TRUE) min(pers_enc_age$D_n.p, na.rm = TRUE) min(pers_enc_age$F_n.p, na.rm = TRUE) min(pers_enc_age$H_n.p, na.rm = TRUE) min(pers_enc_age$K_n.p, na.rm = TRUE) min(pers_enc_age$L_n.p, na.rm = TRUE) min(pers_enc_age$N_n.p, na.rm = TRUE) min(pers_enc_age$P_n.p, na.rm = TRUE) min(pers_enc_age$R_n.p, na.rm = TRUE) min(pers_enc_age$S_n.p, na.rm = TRUE) min(pers_enc_age$T_n.p, na.rm = TRUE) min(pers_enc_age$U_n.p, na.rm = TRUE) min(pers_enc_age$W_n.p, na.rm = TRUE) min(pers_enc_age$X_n.p, na.rm = TRUE) min(pers_enc_age$circ_n.p, na.rm = TRUE) min(pers_enc_age$endo_n.p, na.rm = TRUE) min(pers_enc_age$pulm_n.p, na.rm = TRUE) min(pers_enc_age$gast_n.p, na.rm = TRUE) min(pers_enc_age$urog_n.p, na.rm = TRUE) min(pers_enc_age$musc_n.p, na.rm = TRUE) min(pers_enc_age$hema_n.p, na.rm = TRUE) min(pers_enc_age$canc_n.p, na.rm = TRUE) min(pers_enc_age$neur_n.p, na.rm = TRUE) min(pers_enc_age$Pdx_n.p, na.rm = TRUE) min(pers_enc_age$infect_n.p, na.rm = TRUE) min(pers_enc_age$pain_n.p, na.rm = TRUE) min(pers_enc_age$injury_n.p, na.rm = TRUE) min(pers_enc_age$str_n.p, na.rm = TRUE) min(pers_enc_age$adhd_n.p, na.rm = TRUE) min(pers_enc_age$anx_n.p, na.rm = TRUE) min(pers_enc_age$dem_n.p, na.rm = TRUE) min(pers_enc_age$dep_n.p, na.rm = TRUE) min(pers_enc_age$dev_n.p, na.rm = TRUE) min(pers_enc_age$eat_n.p, na.rm = TRUE) min(pers_enc_age$phb_n.p, na.rm = TRUE) min(pers_enc_age$psy_n.p, na.rm = TRUE) min(pers_enc_age$ptsd_n.p, na.rm = TRUE) min(pers_enc_age$sex_n.p, na.rm = TRUE) min(pers_enc_age$slp_n.p, na.rm = TRUE) min(pers_enc_age$som_n.p, na.rm = TRUE) min(pers_enc_age$sub_n.p, na.rm = TRUE) min(pers_enc_age$sui_n.p, na.rm = TRUE) min(pers_enc_age$cha_n.p, na.rm = TRUE) min(pers_enc_age$con_n.p, na.rm = TRUE) min(pers_enc_age$per_n.p, na.rm = TRUE) min(pers_enc_age$chf_n.p, na.rm = TRUE) min(pers_enc_age$adl_n.p, na.rm = TRUE) min(pers_enc_age$stu_n.p, na.rm = TRUE) min(pers_enc_age$fea_n.p, na.rm = TRUE) min(pers_enc_age$irr_n.p, na.rm = TRUE) min(pers_enc_age$oth_n.p, na.rm = TRUE) space <- tibble(code = "", all_n.p = 0, all_p.p = 0, female_n.p = 0, female_p.p = 0, male_n.p = 0, male_p.p = 0, all_n.e = 0, all_p.e = 0, female_n.e = 0, female_p.e = 0, male_n.e = 0, male_p.e = 0) pers_enc <- bind_rows(pers_enc, space) %>% mutate(code = ifelse(code == "P", "Psychological", code)) write.csv(pers_enc, "M:/p1074-renateh/2023_DayInLifeGP/Work/Results/PersonEncounter_GT10_Sept2023.csv") write.csv(pers_enc_age, "M:/p1074-renateh/2023_DayInLifeGP/Work/Results/PersonEncounterAge_GT10_Sept2023.csv")