R/load_data.R
In andyyu6227/MH.datapipe: Preprocessing/filtering mHealth data, imputing NA & check imputation quality
Defines functions
load_raw_pedometer
load_raw_battery
load_imputed_passive
load_filtered_passive
load_active
load_baseline
load_raw_passive
access_api
Documented in
access_api
load_active
load_baseline
load_filtered_passive
load_imputed_passive
load_raw_battery
load_raw_passive
load_raw_pedometer
#' Get access to BOX API
#'
#' @param id the id for box api
#' @param secret the secret for box api
#' @export
access_api = function(id, secret){
boxr::box_auth(client_id = id, client_secret = secret)
}
#' Load raw passive data
#'
#' @return A data frame of raw passive data
#' @export
load_raw_passive = function(){
#Load data
passive_raw_df = boxr::box_read_csv(882499322193) #read raw passive data
#Data format
passive_raw_df$date = as.Date(passive_raw_df$date)
#clean and convert subject names into lower case:
passive_raw_df$subject_id = tolower(passive_raw_df$subject_id)
passive_raw_df$subject_id = gsub("gayerskyreds", "gayevskyreds", passive_raw_df$subject_id)
passive_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", passive_raw_df$subject_id)
passive_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", passive_raw_df$subject_id)
passive_raw_df$subject_id = gsub(" ","", passive_raw_df$subject_id)
passive_raw_df = passive_raw_df %>% arrange(subject_id, date)
#Discard some passive variables
passive_raw_df = passive_raw_df %>%
select(subject_id, date, screen_unlocks, display_events, step_count, time_at_home, conversation_percent, tic_voiced_time, sleep_duration, travel_diameter, device_use_percent) %>%
arrange(subject_id, date)
return(passive_raw_df)
}
#' Load baseline data
#'
#' @return A data frame of baseline data
#' @export
load_baseline = function(){
import_data = function(sheet){data.frame(boxr::box_read_excel(882501310568, sheet = sheet))}
reds = import_data("REDS") %>%
filter(is.na(hr_id) == FALSE) %>%
filter(redcap_event_name == "baseline_arm_1") %>%
select(hr_id, gender, age_yrs, marital_status, ethnicity, race, religion, education, bisbas_DRIVE_TOTAL,
bisbas_funtot, bisbas_reward_tot, bistot, madrstot,
finres_1, finres_2, finres_3, finres_4, finres_5, madrstot)
reds[,2:ncol(reds)] = sapply(reds[,2:ncol(reds)], function(x) as.numeric(x))
relief = import_data("RELIEF") %>%
filter(is.na(hr_id) == FALSE) %>%
filter(redcap_event_name == "baseline_arm_1") %>%
select(hr_id, gender, age_yrs, marital_status, ethnicity, race, religion, education, bisbas_DRIVE_TOTAL,
bisbas_funtot, bisbas_reward_tot, bistot, madrstot,
finres_1, finres_2, finres_3, finres_4, finres_5, madrstot)
relief[,2:ncol(relief)] = sapply(relief[,2:ncol(relief)], function(x) as.numeric(x))
protect = import_data("PROTECT") %>%
filter(is.na(hr_id) == FALSE) %>%
filter(redcap_event_name == "baseline_arm_1") %>%
select(hr_id, gender, age_yrs, marital_status, ethnicity, race, religion, education, bisbas_DRIVE_TOTAL,
bisbas_funtot, bisbas_reward_tot, bistot, madrstot,
finres_1, finres_2, finres_3, finres_4, finres_5, madrstot)
protect[,2:ncol(protect)] = sapply(protect[,2:ncol(protect)], function(x) as.numeric(x))
base_df = bind_rows(reds, relief, protect)
#clean and convert subject names into lower case:
base_df$hr_id = tolower(base_df$hr_id)
base_df$hr_id = gsub("gayerskyreds", "gayevskyreds", base_df$hr_id)
base_df$hr_id = gsub("rodriguezreds", "rodriquezreds", base_df$hr_id)
base_df$hr_id = gsub("rodriguezreds", "rodriquezreds", base_df$hr_id)
base_df$hr_id = gsub(" ","",base_df$hr_id)
names(base_df)[1] = "subject_id"
return(base_df)
}
#' Load active data
#'
#' @return A data frame of active data
#' @export
load_active = function(){
#Load Active Data:
active_long = boxr::box_read_csv(882501545763) %>% select(subject_id, timestamp, q_id, val)
#date format
active_long$timestamp <- as.Date(active_long$timestamp)
#clean and convert subject names into lower case:
active_long = active_long %>%
arrange(subject_id, timestamp)
active_long$subject_id = tolower(active_long$subject_id)
active_long$subject_id = gsub("gayerskyreds", "gayevskyreds", active_long$subject_id)
active_long$subject_id = gsub("rodriguezreds", "rodriquezreds", active_long$subject_id)
active_long$subject_id = gsub("rodriguezreds", "rodriquezreds", active_long$subject_id)
active_long$subject_id = gsub(" ","", active_long$subject_id)
#delect duplicat records
active_long = active_long %>% distinct(subject_id, timestamp, q_id, .keep_all = TRUE)
#convert data from long format to wide format
active_df = spread(active_long, q_id, val, fill = -999) %>% select(-invalid_format_no_response)
active_df = active_df %>%
arrange(subject_id, timestamp)
#convert PAM related data from strings to numerics
active_df = active_df %>%
mutate(PAM_row = as.numeric(substr(PAM, 2, 2)) - 1) %>%
mutate(PAM_col = as.numeric(substr(PAM, 4, 4))) %>%
mutate(PAMstep_row = as.numeric(substr(pam_step, 2, 2))) %>%
mutate(PAMstep_col = as.numeric(substr(pam_step, 4, 4)))
active_df$PAM_row[which(active_df$PAM_row == 8)] = 0
active_df$PAM_col[which(active_df$PAM_col == 9)] = 0
active_df$PAMstep_row[which(active_df$PAMstep_row == 9)] = 0
active_df$PAMstep_col[which(active_df$PAMstep_col == 9)] = 0
#Convert picture selection data into correlated scores(the formula is based on explainations of app's website)
active_df = active_df %>%
mutate(row = PAM_row+PAMstep_row) %>%
mutate(col = PAM_col+PAMstep_col) %>%
mutate(arousal = 5 - row) %>%
mutate(valence = col) %>%
select(subject_id, timestamp, homework, pain, phq8_q1_alacrity, phq8_q2_alacrity, stress, arousal, valence)
#NA values
active_df$arousal[which(active_df$arousal == 0)] = NA
active_df$valence[which(active_df$valence == 0)] = NA
active_df$pain[which(active_df$pain == '-999')] = NA
active_df$phq8_q1_alacrity[which(active_df$phq8_q1_alacrity == '-999')] = NA
active_df$phq8_q2_alacrity[which(active_df$phq8_q2_alacrity == '-999')] = NA
active_df$stress[which(active_df$stress == '-999')] = NA
active_df$homework[which(active_df$homework == '-999')] = NA
names(active_df)[2] = "date"
active_df[,3:ncol(active_df)] = sapply(active_df[,3:ncol(active_df)], function(x) as.numeric(x))
return(active_df)
}
#' Load filtered passive data
#'
#' @return A data frame of filtered passive data
#' @export
load_filtered_passive = function(){
filtered_passive = boxr::box_read_csv(884263835242)
filtered_passive$date = as.Date(filtered_passive$date)
filtered_passive$subject_id = tolower(filtered_passive$subject_id)
filtered_passive$subject_id = gsub("gayerskyreds", "gayevskyreds", filtered_passive$subject_id)
filtered_passive$subject_id = gsub("rodriguezreds", "rodriquezreds", filtered_passive$subject_id)
filtered_passive$subject_id = gsub("rodriguezreds", "rodriquezreds", filtered_passive$subject_id)
filtered_passive$subject_id = gsub(" ", "", filtered_passive$subject_id)
filtered_passive = filtered_passive %>% arrange(subject_id, date)
filtered_passive = filtered_passive %>% select(subject_id, date, screen_unlocks, display_events, step_count, time_at_home, conversation_percent, tic_voiced_time, sleep_duration, travel_diameter, device_use_percent)
return(filtered_passive)
}
#' Load imputed data
#'
#' @return A data frame of imputed passive data
#' @export
load_imputed_passive = function(){
impute_p = boxr::box_read_csv(885059869455)[-1] %>% arrange(subject_id, date)
return(impute_p)
}
#' Load raw battery data
#'
#' @return A data frame of raw battery data
#' @export
load_raw_battery = function(){
#Load data
battery_raw_df = boxr::box_read_csv(717718293729) #read raw battery data
battery_raw_df = battery_raw_df %>% select(subject_id, timestamp, level)
#clean and convert subject names into lower case:
battery_raw_df$subject_id = tolower(battery_raw_df$subject_id)
battery_raw_df$subject_id = gsub("gayerskyreds", "gayevskyreds", battery_raw_df$subject_id)
battery_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", battery_raw_df$subject_id)
battery_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", battery_raw_df$subject_id)
battery_raw_df$subject_id = gsub(" ","", battery_raw_df$subject_id)
battery_raw_df = battery_raw_df %>% arrange(subject_id, timestamp)
clean_subs = c(
"gayevskyreds10", "gayevskyreds11" , "gayevskyreds12" ,"gayevskyreds13" ,"gayevskyreds16" ,"gayevskyreds17" ,"gayevskyreds18" ,
"gayevskyreds2" , "gayevskyreds3" , "gayevskyreds4" ,"gayevskyreds6" ,"gayevskyreds7" ,"gayevskyreds8" ,"gayevskyreds9" ,
"rodriquezreds1", "rodriquezreds2" , "rodriquezreds3" ,"rodriquezreds4" ,"sternrelief1" ,"sternrelief12" ,"sternrelief14" ,
"sternrelief17" , "sternrelief18" , "sternrelief20" ,"sternrelief21" ,"sternrelief22" ,"sternrelief23" ,"sternrelief24" ,
"sternrelief26" , "sternrelief27" , "sternrelief28" ,"sternrelief3" ,"sternrelief30" ,"sternrelief31" ,"sternrelief32" ,
"sternrelief35" , "sternrelief4" , "sternrelief5" ,"sternrelief6" ,"sternrelief7" ,"sternrelief8" ,"sternrelief9" ,
"wynneprotect10", "wynneprotect11" , "wynneprotect12" ,"wynneprotect144" ,"wynneprotect146" ,"wynneprotect21" ,"wynneprotect23" ,
"wynneprotect24", "wynneprotect25" , "wynneprotect56" ,"wynneprotect58" ,"wynnereds11" ,"wynnereds12" ,"wynnereds2" ,
"wynnereds3" , "wynnereds4" , "wynnereds6" ,"wynnereds7" ,"wynnereds8" )
battery_raw_df = battery_raw_df %>% filter(subject_id %in% clean_subs)
return(battery_raw_df)
}
#' Load raw pedometer data
#'
#' @return A data frame of raw pedometer data
#' @export
load_raw_pedometer = function(){
#Load data
pedometer_raw_df = boxr::box_read_csv(717719539241) #read raw pedometer data
pedometer_raw_df = pedometer_raw_df %>% select(-user_id, -bacth_id, -id)
#clean and convert subject names into lower case:
pedometer_raw_df$subject_id = tolower(pedometer_raw_df$subject_id)
pedometer_raw_df$subject_id = gsub("gayerskyreds", "gayevskyreds", pedometer_raw_df$subject_id)
pedometer_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", pedometer_raw_df$subject_id)
pedometer_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", pedometer_raw_df$subject_id)
pedometer_raw_df$subject_id = gsub(" ","", pedometer_raw_df$subject_id)
pedometer_raw_df = pedometer_raw_df %>% arrange(subject_id, timestamp)
clean_subs = c(
"gayevskyreds10", "gayevskyreds11" , "gayevskyreds12" ,"gayevskyreds13" ,"gayevskyreds16" ,"gayevskyreds17" ,"gayevskyreds18" ,
"gayevskyreds2" , "gayevskyreds3" , "gayevskyreds4" ,"gayevskyreds6" ,"gayevskyreds7" ,"gayevskyreds8" ,"gayevskyreds9" ,
"rodriquezreds1", "rodriquezreds2" , "rodriquezreds3" ,"rodriquezreds4" ,"sternrelief1" ,"sternrelief12" ,"sternrelief14" ,
"sternrelief17" , "sternrelief18" , "sternrelief20" ,"sternrelief21" ,"sternrelief22" ,"sternrelief23" ,"sternrelief24" ,
"sternrelief26" , "sternrelief27" , "sternrelief28" ,"sternrelief3" ,"sternrelief30" ,"sternrelief31" ,"sternrelief32" ,
"sternrelief35" , "sternrelief4" , "sternrelief5" ,"sternrelief6" ,"sternrelief7" ,"sternrelief8" ,"sternrelief9" ,
"wynneprotect10", "wynneprotect11" , "wynneprotect12" ,"wynneprotect144" ,"wynneprotect146" ,"wynneprotect21" ,"wynneprotect23" ,
"wynneprotect24", "wynneprotect25" , "wynneprotect56" ,"wynneprotect58" ,"wynnereds11" ,"wynnereds12" ,"wynnereds2" ,
"wynnereds3" , "wynnereds4" , "wynnereds6" ,"wynnereds7" ,"wynnereds8" )
pedometer_raw_df = pedometer_raw_df %>% filter(subject_id %in% clean_subs)
return(pedometer_raw_df)
}
andyyu6227/MH.datapipe documentation built on Jan. 1, 2022, 10:18 p.m.
R Package Documentation
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Defines functions load_raw_pedometer load_raw_battery load_imputed_passive load_filtered_passive load_active load_baseline load_raw_passive access_api
Documented in access_api load_active load_baseline load_filtered_passive load_imputed_passive load_raw_battery load_raw_passive load_raw_pedometer
#' Get access to BOX API
#'
#' @param id the id for box api
#' @param secret the secret for box api
#' @export
access_api = function(id, secret){
boxr::box_auth(client_id = id, client_secret = secret)
}
#' Load raw passive data
#'
#' @return A data frame of raw passive data
#' @export
load_raw_passive = function(){
#Load data
passive_raw_df = boxr::box_read_csv(882499322193) #read raw passive data
#Data format
passive_raw_df$date = as.Date(passive_raw_df$date)
#clean and convert subject names into lower case:
passive_raw_df$subject_id = tolower(passive_raw_df$subject_id)
passive_raw_df$subject_id = gsub("gayerskyreds", "gayevskyreds", passive_raw_df$subject_id)
passive_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", passive_raw_df$subject_id)
passive_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", passive_raw_df$subject_id)
passive_raw_df$subject_id = gsub(" ","", passive_raw_df$subject_id)
passive_raw_df = passive_raw_df %>% arrange(subject_id, date)
#Discard some passive variables
passive_raw_df = passive_raw_df %>%
select(subject_id, date, screen_unlocks, display_events, step_count, time_at_home, conversation_percent, tic_voiced_time, sleep_duration, travel_diameter, device_use_percent) %>%
arrange(subject_id, date)
return(passive_raw_df)
}
#' Load baseline data
#'
#' @return A data frame of baseline data
#' @export
load_baseline = function(){
import_data = function(sheet){data.frame(boxr::box_read_excel(882501310568, sheet = sheet))}
reds = import_data("REDS") %>%
filter(is.na(hr_id) == FALSE) %>%
filter(redcap_event_name == "baseline_arm_1") %>%
select(hr_id, gender, age_yrs, marital_status, ethnicity, race, religion, education, bisbas_DRIVE_TOTAL,
bisbas_funtot, bisbas_reward_tot, bistot, madrstot,
finres_1, finres_2, finres_3, finres_4, finres_5, madrstot)
reds[,2:ncol(reds)] = sapply(reds[,2:ncol(reds)], function(x) as.numeric(x))
relief = import_data("RELIEF") %>%
filter(is.na(hr_id) == FALSE) %>%
filter(redcap_event_name == "baseline_arm_1") %>%
select(hr_id, gender, age_yrs, marital_status, ethnicity, race, religion, education, bisbas_DRIVE_TOTAL,
bisbas_funtot, bisbas_reward_tot, bistot, madrstot,
finres_1, finres_2, finres_3, finres_4, finres_5, madrstot)
relief[,2:ncol(relief)] = sapply(relief[,2:ncol(relief)], function(x) as.numeric(x))
protect = import_data("PROTECT") %>%
filter(is.na(hr_id) == FALSE) %>%
filter(redcap_event_name == "baseline_arm_1") %>%
select(hr_id, gender, age_yrs, marital_status, ethnicity, race, religion, education, bisbas_DRIVE_TOTAL,
bisbas_funtot, bisbas_reward_tot, bistot, madrstot,
finres_1, finres_2, finres_3, finres_4, finres_5, madrstot)
protect[,2:ncol(protect)] = sapply(protect[,2:ncol(protect)], function(x) as.numeric(x))
base_df = bind_rows(reds, relief, protect)
#clean and convert subject names into lower case:
base_df$hr_id = tolower(base_df$hr_id)
base_df$hr_id = gsub("gayerskyreds", "gayevskyreds", base_df$hr_id)
base_df$hr_id = gsub("rodriguezreds", "rodriquezreds", base_df$hr_id)
base_df$hr_id = gsub("rodriguezreds", "rodriquezreds", base_df$hr_id)
base_df$hr_id = gsub(" ","",base_df$hr_id)
names(base_df)[1] = "subject_id"
return(base_df)
}
#' Load active data
#'
#' @return A data frame of active data
#' @export
load_active = function(){
#Load Active Data:
active_long = boxr::box_read_csv(882501545763) %>% select(subject_id, timestamp, q_id, val)
#date format
active_long$timestamp <- as.Date(active_long$timestamp)
#clean and convert subject names into lower case:
active_long = active_long %>%
arrange(subject_id, timestamp)
active_long$subject_id = tolower(active_long$subject_id)
active_long$subject_id = gsub("gayerskyreds", "gayevskyreds", active_long$subject_id)
active_long$subject_id = gsub("rodriguezreds", "rodriquezreds", active_long$subject_id)
active_long$subject_id = gsub("rodriguezreds", "rodriquezreds", active_long$subject_id)
active_long$subject_id = gsub(" ","", active_long$subject_id)
#delect duplicat records
active_long = active_long %>% distinct(subject_id, timestamp, q_id, .keep_all = TRUE)
#convert data from long format to wide format
active_df = spread(active_long, q_id, val, fill = -999) %>% select(-invalid_format_no_response)
active_df = active_df %>%
arrange(subject_id, timestamp)
#convert PAM related data from strings to numerics
active_df = active_df %>%
mutate(PAM_row = as.numeric(substr(PAM, 2, 2)) - 1) %>%
mutate(PAM_col = as.numeric(substr(PAM, 4, 4))) %>%
mutate(PAMstep_row = as.numeric(substr(pam_step, 2, 2))) %>%
mutate(PAMstep_col = as.numeric(substr(pam_step, 4, 4)))
active_df$PAM_row[which(active_df$PAM_row == 8)] = 0
active_df$PAM_col[which(active_df$PAM_col == 9)] = 0
active_df$PAMstep_row[which(active_df$PAMstep_row == 9)] = 0
active_df$PAMstep_col[which(active_df$PAMstep_col == 9)] = 0
#Convert picture selection data into correlated scores(the formula is based on explainations of app's website)
active_df = active_df %>%
mutate(row = PAM_row+PAMstep_row) %>%
mutate(col = PAM_col+PAMstep_col) %>%
mutate(arousal = 5 - row) %>%
mutate(valence = col) %>%
select(subject_id, timestamp, homework, pain, phq8_q1_alacrity, phq8_q2_alacrity, stress, arousal, valence)
#NA values
active_df$arousal[which(active_df$arousal == 0)] = NA
active_df$valence[which(active_df$valence == 0)] = NA
active_df$pain[which(active_df$pain == '-999')] = NA
active_df$phq8_q1_alacrity[which(active_df$phq8_q1_alacrity == '-999')] = NA
active_df$phq8_q2_alacrity[which(active_df$phq8_q2_alacrity == '-999')] = NA
active_df$stress[which(active_df$stress == '-999')] = NA
active_df$homework[which(active_df$homework == '-999')] = NA
names(active_df)[2] = "date"
active_df[,3:ncol(active_df)] = sapply(active_df[,3:ncol(active_df)], function(x) as.numeric(x))
return(active_df)
}
#' Load filtered passive data
#'
#' @return A data frame of filtered passive data
#' @export
load_filtered_passive = function(){
filtered_passive = boxr::box_read_csv(884263835242)
filtered_passive$date = as.Date(filtered_passive$date)
filtered_passive$subject_id = tolower(filtered_passive$subject_id)
filtered_passive$subject_id = gsub("gayerskyreds", "gayevskyreds", filtered_passive$subject_id)
filtered_passive$subject_id = gsub("rodriguezreds", "rodriquezreds", filtered_passive$subject_id)
filtered_passive$subject_id = gsub("rodriguezreds", "rodriquezreds", filtered_passive$subject_id)
filtered_passive$subject_id = gsub(" ", "", filtered_passive$subject_id)
filtered_passive = filtered_passive %>% arrange(subject_id, date)
filtered_passive = filtered_passive %>% select(subject_id, date, screen_unlocks, display_events, step_count, time_at_home, conversation_percent, tic_voiced_time, sleep_duration, travel_diameter, device_use_percent)
return(filtered_passive)
}
#' Load imputed data
#'
#' @return A data frame of imputed passive data
#' @export
load_imputed_passive = function(){
impute_p = boxr::box_read_csv(885059869455)[-1] %>% arrange(subject_id, date)
return(impute_p)
}
#' Load raw battery data
#'
#' @return A data frame of raw battery data
#' @export
load_raw_battery = function(){
#Load data
battery_raw_df = boxr::box_read_csv(717718293729) #read raw battery data
battery_raw_df = battery_raw_df %>% select(subject_id, timestamp, level)
#clean and convert subject names into lower case:
battery_raw_df$subject_id = tolower(battery_raw_df$subject_id)
battery_raw_df$subject_id = gsub("gayerskyreds", "gayevskyreds", battery_raw_df$subject_id)
battery_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", battery_raw_df$subject_id)
battery_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", battery_raw_df$subject_id)
battery_raw_df$subject_id = gsub(" ","", battery_raw_df$subject_id)
battery_raw_df = battery_raw_df %>% arrange(subject_id, timestamp)
clean_subs = c(
"gayevskyreds10", "gayevskyreds11" , "gayevskyreds12" ,"gayevskyreds13" ,"gayevskyreds16" ,"gayevskyreds17" ,"gayevskyreds18" ,
"gayevskyreds2" , "gayevskyreds3" , "gayevskyreds4" ,"gayevskyreds6" ,"gayevskyreds7" ,"gayevskyreds8" ,"gayevskyreds9" ,
"rodriquezreds1", "rodriquezreds2" , "rodriquezreds3" ,"rodriquezreds4" ,"sternrelief1" ,"sternrelief12" ,"sternrelief14" ,
"sternrelief17" , "sternrelief18" , "sternrelief20" ,"sternrelief21" ,"sternrelief22" ,"sternrelief23" ,"sternrelief24" ,
"sternrelief26" , "sternrelief27" , "sternrelief28" ,"sternrelief3" ,"sternrelief30" ,"sternrelief31" ,"sternrelief32" ,
"sternrelief35" , "sternrelief4" , "sternrelief5" ,"sternrelief6" ,"sternrelief7" ,"sternrelief8" ,"sternrelief9" ,
"wynneprotect10", "wynneprotect11" , "wynneprotect12" ,"wynneprotect144" ,"wynneprotect146" ,"wynneprotect21" ,"wynneprotect23" ,
"wynneprotect24", "wynneprotect25" , "wynneprotect56" ,"wynneprotect58" ,"wynnereds11" ,"wynnereds12" ,"wynnereds2" ,
"wynnereds3" , "wynnereds4" , "wynnereds6" ,"wynnereds7" ,"wynnereds8" )
battery_raw_df = battery_raw_df %>% filter(subject_id %in% clean_subs)
return(battery_raw_df)
}
#' Load raw pedometer data
#'
#' @return A data frame of raw pedometer data
#' @export
load_raw_pedometer = function(){
#Load data
pedometer_raw_df = boxr::box_read_csv(717719539241) #read raw pedometer data
pedometer_raw_df = pedometer_raw_df %>% select(-user_id, -bacth_id, -id)
#clean and convert subject names into lower case:
pedometer_raw_df$subject_id = tolower(pedometer_raw_df$subject_id)
pedometer_raw_df$subject_id = gsub("gayerskyreds", "gayevskyreds", pedometer_raw_df$subject_id)
pedometer_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", pedometer_raw_df$subject_id)
pedometer_raw_df$subject_id = gsub("rodriguezreds", "rodriquezreds", pedometer_raw_df$subject_id)
pedometer_raw_df$subject_id = gsub(" ","", pedometer_raw_df$subject_id)
pedometer_raw_df = pedometer_raw_df %>% arrange(subject_id, timestamp)
clean_subs = c(
"gayevskyreds10", "gayevskyreds11" , "gayevskyreds12" ,"gayevskyreds13" ,"gayevskyreds16" ,"gayevskyreds17" ,"gayevskyreds18" ,
"gayevskyreds2" , "gayevskyreds3" , "gayevskyreds4" ,"gayevskyreds6" ,"gayevskyreds7" ,"gayevskyreds8" ,"gayevskyreds9" ,
"rodriquezreds1", "rodriquezreds2" , "rodriquezreds3" ,"rodriquezreds4" ,"sternrelief1" ,"sternrelief12" ,"sternrelief14" ,
"sternrelief17" , "sternrelief18" , "sternrelief20" ,"sternrelief21" ,"sternrelief22" ,"sternrelief23" ,"sternrelief24" ,
"sternrelief26" , "sternrelief27" , "sternrelief28" ,"sternrelief3" ,"sternrelief30" ,"sternrelief31" ,"sternrelief32" ,
"sternrelief35" , "sternrelief4" , "sternrelief5" ,"sternrelief6" ,"sternrelief7" ,"sternrelief8" ,"sternrelief9" ,
"wynneprotect10", "wynneprotect11" , "wynneprotect12" ,"wynneprotect144" ,"wynneprotect146" ,"wynneprotect21" ,"wynneprotect23" ,
"wynneprotect24", "wynneprotect25" , "wynneprotect56" ,"wynneprotect58" ,"wynnereds11" ,"wynnereds12" ,"wynnereds2" ,
"wynnereds3" , "wynnereds4" , "wynnereds6" ,"wynnereds7" ,"wynnereds8" )
pedometer_raw_df = pedometer_raw_df %>% filter(subject_id %in% clean_subs)
return(pedometer_raw_df)
}
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