R/H2R_one_to_many_Cleaning.R
In misizsembes/NGA_H2R_TOOL_v2_June2019: A grammar of hypothesis test driven analysis for the NIgeria 2019 MSNA
#THE FOLDER WHERE UNCLEANED/RAW DATA IS STORED
parent_folder <- "~/Desktop/Nigeria/Hard_to_reach/New_Organization/H2R_August"
#UNLCEANED DATA == "CSV" OR "EXCEL"
uncleaned_data_file_type <- "EXCEL"
#NAME OF EXCEL/CSV FILE WHERE CLEANING LOG IS STORED
cleaning_name <- "REACH_NGA_Tool_H2RQuant_NEW_KII_19_08_2019_final_2019_08_20_07_33_15"
cleaning_log_org_excel_sheet <- "log" #CLEANING LOG EXCEL SHEET NAME (IF EXCEL)
short_name <- 'H2R_August2019'
#HEADER DELIMITER OF COLUMN NAMES
header_delimiter <- "/"
alt_id <- "_index" #IF NOT ALL ID COLUMNS ARE UUID, DEFINE THE ALTERNATIVE (FOR KOBO LOOPS)
#############################LOAD PACKAGES######################################
if (!require(readxl)) install.packages('readxl')
library(readxl)
if (!require(weights)) install.packages('weights')
library(weights)
if (!require(pls)) install.packages('pls')
library(pls)
if (!require(gmodels)) install.packages('gmodels')
library(gmodels)
if (!require(splitstackshape)) install.packages('splitstackshape')
library(splitstackshape)
if (!require(ggplot2)) install.packages('ggplot2')
library(ggplot2)
if (!require(reshape2)) install.packages('reshape2')
library(reshape2)
if (!require(data.table)) install.packages('data.table')
library(data.table)
if (!require(magrittr)) install.packages('magrittr')
library(magrittr)
if (!require(scales)) install.packages('scales')
library(scales)
if (!require(tm)) install.packages('tm')
library(tm)
if (!require(SDMTools)) install.packages('SDMTools')
library(SDMTools)
if (!require(plotly)) install.packages('plotly')
library(plotly)
if (!require(tibble)) install.packages('tibble')
library(tibble)
if (!require(plotly)) install.packages('plotly')
library(plotly)
if (!require(tidyr)) install.packages('tidyr')
library(tidyr)
if (!require(stringr)) install.packages('stringr')
library(stringr)
if (!require(ggrepel)) install.packages('ggrepel')
library(ggrepel)
if (!require(reshape2)) install.packages('reshape2')
library(reshape2)
if (!require(MASS)) install.packages('MASS')
library(MASS)
if (!require(magrittr)) install.packages('magrittr')
library(magrittr)
if (!require(foreign)) install.packages('foreign')
library(foreign)
if (!require(sandwich)) install.packages('sandwich')
library(sandwich)
if (!require(lmtest)) install.packages('lmtest')
library(lmtest)
if (!require(corrplot)) install.packages('corrplot')
library(corrplot)
if (!require(RColorBrewer)) install.packages('RColorBrewer')
library(RColorBrewer)
if (!require(xtable)) install.packages('xtable')
library(xtable)
if (!require(Hmisc)) install.packages('Hmisc')
library(Hmisc)
if (!require(taRifx)) install.packages('taRifx')
library(taRifx)
if (!require(car)) install.packages('car')
library(car)
if (!require(readr)) install.packages('readr')
library(readr)
if (!require(plyr)) install.packages('plyr')
library(plyr)
if (!require(dplyr)) install.packages('dplyr')
library(dplyr)
#if (!require(tidyverse)) install.packages('tidyverse')
#library(tidyverse)
############################################################################################
############################################################################################
cleaning_folder <- "Raw_to_Cleaning_Process"
setwd(paste0(parent_folder,"/",cleaning_folder))
#IMPORT FOLDERS
cleaning_log_import_folder <- "Raw_Data" #FOLDER WHERE THE CLEANING LOG IS STORED
#OUTPUT FOLDERS
cleaning_output_folder <- "updated_cleaning_log" # UPDATED CLEANING LOG OUTPUT FOLDER
updated_data_folder <- "updated_data" #FOLDER WHERE UPDATED DATA GOES
#LOAD CLEANING LOG
cleaning_log_org_excel<- paste0(cleaning_log_import_folder,"/",cleaning_name,".xlsx")
cleaning_log_org <- read_excel(cleaning_log_org_excel, sheet= cleaning_log_org_excel_sheet)
cleaning_log_real_org <-cleaning_log_org
#ENSURE CLEANING LOG NAMES ARE THE SAME AS THE ORIGINAL
names(cleaning_log_org)<- c("folder", "dataset","sheet", "question", "old", "new", "reason", "_uuid", "modified", "cleaner_name")
number_cols_cleaning_log <- ncol(cleaning_log_org)
#CREATE NICE "uuid" COLUMN
cleaning_log_org$uuid <-cleaning_log_org$`_uuid`
#CREATE INDEX COLUMN
cleaning_log_org$index_number <- 1:nrow(cleaning_log_org)
#GRAB NEWEST CORRECTIONS (HIGHEST INDEX NUMBER)
cleaning_log_org <- cleaning_log_org %>% group_by(uuid, question) %>% top_n(n=1) %>% ungroup()
cleaning_log_first_setup <- cleaning_log_org
#FOR QUESTIONS: REPLACE "/" WITH "_"
cleaning_log_org$question <- cleaning_log_org$question %>%
gsub("/", "_", .)
#UNIQUE FOLDERS
folders <- unique(cleaning_log_first_setup$folder)
cleaning_folder_list_intofolder <- list()
cleaning_folder_list <- list()
cleaning_sheet_list <- list()
cleaning_dataset_list <- list()
###FIRST SET OF LOOPS: FOR EVERY FOLDER NAME
for(f in 1:length(folders)){ #FOLDER BEGIN
print(f)
folder <- folders[f]
#UNIQUE SURVEYS
surveys_full <- cleaning_log_first_setup %>% dplyr:: filter(folder==folders[f])
surveys <- unique(surveys_full$dataset)
#FOR EVERY EXCEL FILE (SURVEY)
for(j in 1: length(surveys)){ #SURVEYS IN FOLDER
survey_name <- surveys[j]
#SUBSET CLEANING LOG
cleaning_log_org_for_each_survey <- cleaning_log_first_setup %>%
dplyr:: filter(folder == folders[f] )%>% dplyr:: filter(dataset == surveys[j] )
sheets <- unique(cleaning_log_org_for_each_survey$sheet)
for(s in 1: length(sheets)){ #SHEETS IN DATASET
print("sheet")
print(s)
cleaning_log_org_for_each_sheet <- cleaning_log_org_for_each_survey %>%
dplyr:: filter(sheet == sheets[s] )
#IF "UUID" LETTER IS TRUE
any_alpha <- grepl("[[:alpha:]]", cleaning_log_org_for_each_sheet$uuid) #NO ALPHABET NUMBERS IF FALSE
any_alpha <- any(any_alpha)
#ALL QUESTIONS TO BE CLEANED
allquestions <- unique(cleaning_log_org_for_each_sheet$question)
if (uncleaned_data_file_type == "EXCEL"){
#UNCLEANED EXCEL FILE NAME
uncleaned_excel <- paste0(folder,"/", survey_name ,".xlsx")
#UNCLEANED EXCEL SHEET NAME
uncleaned <- read_excel(uncleaned_excel, sheet= sheets[s])
} else if (uncleaned_data_file_type == "CSV"){
uncleaned <- read_csv(paste0(folder,"/",survey_name, ".csv"))
} else {
print("UNCLEANED FILE TYPE ERROR")
}
###ADJUST INDEX TO BE UUID COLUMN
if( length(grep("^_uuid$",colnames(uncleaned)))>0 ){
uuid_index <- grep("^_uuid$",colnames(uncleaned))
} else {
uuid_index <- grep("uuid",colnames(uncleaned))
}
if( nrow(unique(uncleaned[uuid_index]))==1 ){
grep("uuid",colnames(uncleaned))
uncleaned$`_uuid` <- NULL
colnames(uncleaned)[grep("^_index$",colnames(uncleaned))] <- "index"
uncleaned <- uncleaned %>% dplyr:: rename(uuid = index)
print("INDEX NOT UUID")
} else {
colnames(uncleaned)[uuid_index] <- "uuid" #ADD UUID COLUMN
#uncleaned <- uncleaned
print("UUID GOOD")
}
##############BEGIN CHANGE HEADERS##############
colnames(uncleaned) <- gsub(header_delimiter, "_", colnames(uncleaned))
#REMOVE DUPLICATE COLUMNS
uncleaned <- uncleaned[, !duplicated(colnames(uncleaned))]
##############END CHANGE HEADERS##############
##CHANGE FROM UUID TO "_index"
if(any_alpha == FALSE){
print("INDEX NOT UUID")
uuid_columns <- grep("uuid",colnames(uncleaned))
uncleaned <- uncleaned[, -c(uuid_columns)]
index_column <- grep("^",alt_id,"$",colnames(uncleaned))
colnames(uncleaned)[index_column] <- "uuid"
} else{
uncleaned <- uncleaned
}
#FILTER OUT ON THIS MONTH'S CORRECTIONS
cleaning_log <- cleaning_log_org_for_each_sheet
cleaning_log <- data.frame(lapply(cleaning_log, function(x) {gsub(header_delimiter, "_", x)}))
#NOTE--FIX "_uuid" to "uuid"
cleaning_log$question <- str_replace( cleaning_log$question, "_uuid", "uuid")
#LIST OF QUESTIONS IN THE CLEANING LOG SUBSET
# detach("package:plyr")
# library(dplyr)
cleaning_log_nulls <- cleaning_log %>% dplyr::filter(new == "NULL" )
null_entries <- as.character(cleaning_log_nulls$uuid)
cleaning_log_no_null <- cleaning_log %>% dplyr::filter(!uuid %in% c(null_entries))
colquestion <- as.character(unique(cleaning_log_no_null$question))
#REMOVE IF NOT A HEADER IN THE DATA
colquestion <- colquestion[(colquestion %in% colnames(uncleaned))]
#WARNING: CLEANING QUESTION NAME DOES NOT EXIST IN THE UNCLEANED DATASET
###LOOP BEGIN
#EMPTY LIST FOR UPDATED QUESTIONS
keep_q<-list()
#CREATE COPIES OF DATA AND CLEANING LOG
uncleaned_added_correction <- uncleaned
cleaning_log_all_updated <- cleaning_log
###UPDATE DATA SHEET LOOP
for(i in seq_along(colquestion)){ #START QUESTION
print("questions")
print(i)
corrected_question_in_df <- data.frame()
#SUBSET EACH CLEANING QUESTION FROM CLEANING LOG
clean_log_one_question<- cleaning_log %>%
dplyr:: filter(question == colquestion[i])
clean_log_one_question <- remove.factors(clean_log_one_question)
if (i >= 2){
colnames(uncleaned_added_correction)[grep("uuid.x" , colnames(uncleaned_added_correction))] <- "idd"
uncleaned_added_correction <- uncleaned_added_correction %>% dplyr:: mutate() %>% dplyr:: select (-contains("uuid")) %>% dplyr:: rename(uuid = idd)
} else {
print("FIRST LOOP -- NO DUPLICATE DEALINGS")
}
#DATA UNIQUE ID
uncleaned_added_correction$unique_idx <- paste0(unlist(uncleaned_added_correction$uuid) , "_", as.vector(unlist(uncleaned_added_correction[grep(paste0("^",colquestion[i],"$"),colnames(uncleaned_added_correction))])) )
uncleaned_added_correction$unique_idx <- paste0(uncleaned_added_correction$unique_idx, "_", ave(uncleaned_added_correction$unique_idx ,uncleaned_added_correction$unique_idx , FUN=seq_along) )
#CLEANING LOG UNIQUE ID
clean_log_one_question$unique_idx <- paste0(clean_log_one_question$uuid , "_" ,clean_log_one_question$old)
clean_log_one_question$unique_idx <- paste0(clean_log_one_question$unique_idx , "_" , ave(clean_log_one_question$unique_idx ,clean_log_one_question$unique_idx , FUN=seq_along))
#ADD CLEANING QUESTION TO DATASET
newgo <- merge(uncleaned_added_correction, clean_log_one_question ,by="unique_idx",all.x=TRUE)
unique_idx <- newgo$unique_idx
#FIND INDEX OF QUESTION TO REPLACE IN THE DATASET
org_index_question <-grep( paste0("^",colquestion[i],"$"),colnames(newgo))
#FIND INDEX OF CLEANING QUESTION COLUMN
question_to_replace_index <- grep( "^question$",colnames(newgo))
#FIND INDEX OF REPLACEMENT INFO (CLEANING) COLUMN
new_answer_index <- grep( "^new$",colnames(newgo))
#COPY ORIGINAL UNCLEANED RESPONSE COLUMN
newgo$question_clone <- newgo[,org_index_question]
question_clone_index <- grep( "^question_clone$",colnames(newgo))
#SUBSET RELEVANT COLUMNS
trim_newgo <- newgo[,c(org_index_question,question_to_replace_index,new_answer_index,question_clone_index)]
#UPDATE ONE QUESTION AT A TIME
trim_newgo[,5] <- ifelse(!is.na(trim_newgo[,2]), as.vector(trim_newgo[,3]),trim_newgo[,4])
keep_q[[i]] <- trim_newgo[,5]
#SAVE "uuid" FROM "newgo" TO JOIN TO "uncleaned"
#REMOVE MULTIPLE UUID COLUMNS
newgo$idd <- as.vector(newgo[,min(grep("uuid",colnames(newgo)))])
newgo <- newgo %>% dplyr:: select(-contains("uuid")) %>% dplyr:: rename(uuid=idd)
newgo <- newgo[, !duplicated(colnames(newgo))]
corrected_question_uuid<- newgo[,grep("^uuid$", colnames(newgo))]
#ADD CORRECTED QUESTION WITH "uuid"
corrected_question_with_uuid_df <- as.data.frame(cbind(corrected_question_uuid,keep_q[[i]],unique_idx))
#RENAME CORRECTED QUESTION SUBSET
colnames(corrected_question_with_uuid_df)[1] <- "uuid"
colnames(corrected_question_with_uuid_df)[2] <- "new_question"
#UPDATE "uncleaned"
uncleaned_added_correction <- merge(uncleaned_added_correction, corrected_question_with_uuid_df,by="unique_idx", all.x=TRUE)
question_needed <- grep(paste0("^",colquestion[i],"$"),colnames(uncleaned_added_correction))
uncleaned_added_correction[,question_needed] <- uncleaned_added_correction$new_question
uncleaned_added_correction$new_question <- NULL
trim_newgo<-NULL
clean_log_one_question$unique_idx<-NULL
#UPDATE CLEANING LOG
clean_log_one_question$modified<-"yes"
clean_log_update <- subset(cleaning_log_all_updated, !(index_number %in% clean_log_one_question$index_number))
cleaning_log_all_updated <-rbind(clean_log_update,clean_log_one_question)
} #END QUESTION
cleaning_sheet_list[[s]] <- cleaning_log_all_updated
#RENAME ADJUSTED DATA
cleaned_up <- uncleaned_added_correction
#EXPORT TO CSV
if( length(grep("^uuid.x$",colnames(cleaned_up)))>0 ) {
cleaned_up <- cleaned_up %>% dplyr:: mutate(idx = uuid.x) %>% dplyr:: select(-c(unique_idx, uuid.x, uuid.y))%>% dplyr:: rename(uuid = idx)
} else {
cleaned_up <- cleaned_up
}
#REMOVE NULL QUESTIONS
cleaning_log_null <- cleaning_log_org %>% dplyr:: filter(new=="NULL") %>% dplyr:: filter(sheet == sheets[s]) %>% dplyr:: select(uuid) %>% dplyr:: distinct(uuid)
if(nrow(cleaning_log_null)>0){
cleaned_up <- cleaned_up[ ! as.character(cleaned_up$uuid) %in% unique(cleaning_log_null$uuid), ]
} else{
cleaned_up <- cleaned_up
}
write.csv(cleaned_up,paste0(folders[f],"/",updated_data_folder,"/","cleanedh2r_", short_name,"_", sheets[s], ".csv") ,na = "")
} #SHEET END
cleaning_dataset_list[[j]] <- cleaning_sheet_list
} #SURVEY END
cleaning_folder_list_intofolder[[f]] <- cleaning_dataset_list
} #END FOLDER
cleaning_folder_list_intofolder[sapply(cleaning_folder_list_intofolder, is.null)] <- NULL
#ALT CONVERT LIST OF LISTS TO DF
flat = unlist(cleaning_folder_list_intofolder, recursive = FALSE)
flat = unlist(flat, recursive = FALSE)
cleaning_log_all_updated <-ldply(flat, data.frame)
#Confirm/Deny NULL removals in the cleaning log
if(nrow(cleaning_log_null)>0){
print("NULLS REMOVED")
cleaning_log_null$onesz <- 1
cleaning_log_all_updated <- merge(cleaning_log_all_updated, cleaning_log_null, by="uuid", all.x=TRUE)
cleaning_log_all_updated$modified <- ifelse(as.character.factor(cleaning_log_all_updated$modified) =="no" & cleaning_log_all_updated$onesz==1, "yes",as.character.factor(cleaning_log_all_updated$modified))
cleaning_log_all_updated$onesz <- NULL
} else{
print("NO NULLS REMOVED")
cleaning_log_all_updated <- cleaning_log_all_updated
}
####SECOND SET OF LOOPS: JOIN WITH ORGINAL CLEANING SHEET
clean_log_update <- subset(cleaning_log_org, !(index_number %in% cleaning_log_all_updated$index_number))
names(clean_log_update) <- names(cleaning_log_all_updated)
#ROWBIND UPDATED WITH NON-UPDATED
cleaning_log_all_updated <- rbind(clean_log_update,cleaning_log_all_updated)
#DELETE REPEATED CLEANS PER-QUESTION
recent_cleans_quest <- list()
recent_cleans_survey <- list()
recent_cleans_folder <- list()
for(j in seq_along(folders)){
folder_sub <- subset(cleaning_log_all_updated, folder == folders[j])
all_surveys <- as.character(unique(folder_sub$dataset))
for(k in seq_along(all_surveys)){
survey_sub <- subset(folder_sub, dataset == all_surveys[k])
questions_per_survey <- as.character(unique(survey_sub$question))
for(i in seq_along(questions_per_survey)){
one_question <- subset(survey_sub, question == questions_per_survey[i])
one_question$index_number <- as.numeric(as.character( one_question$index_number))
latest_clean_perquestion <- one_question %>%
group_by(uuid) %>%
filter(index_number == max(index_number))
latest_clean_perquestion <- data.frame(lapply(latest_clean_perquestion, as.character), stringsAsFactors=FALSE)
recent_cleans_quest[[i]] <- latest_clean_perquestion
}
recent_cleans_survey[[k]] <- recent_cleans_quest
}
recent_cleans_folder[[j]] <- recent_cleans_survey
}
#UNLIST LIST OF LISTS
flat = unlist(recent_cleans_folder, recursive = FALSE)
flat2 = unlist(flat, recursive = FALSE)
cleaning_log_all_updated <- do.call(rbind.data.frame, flat2)
cleaning_log_all_updated <- cleaning_log_all_updated[!duplicated(cleaning_log_all_updated$index_number),]
#CLEAN FILE
cleaning_log_all_updated$index_number <- NULL
cleaning_log_all_updated$uuid <- NULL
names(cleaning_log_all_updated) <- names(cleaning_log_real_org)
write.csv(cleaning_log_all_updated,paste0(cleaning_log_import_folder,"/",cleaning_output_folder,"/","UPDATED_CLEANING_LOG_",short_name,".csv"), na = "")
misizsembes/NGA_H2R_TOOL_v2_June2019 documentation built on Nov. 4, 2019, 6:56 p.m.
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#THE FOLDER WHERE UNCLEANED/RAW DATA IS STORED
parent_folder <- "~/Desktop/Nigeria/Hard_to_reach/New_Organization/H2R_August"
#UNLCEANED DATA == "CSV" OR "EXCEL"
uncleaned_data_file_type <- "EXCEL"
#NAME OF EXCEL/CSV FILE WHERE CLEANING LOG IS STORED
cleaning_name <- "REACH_NGA_Tool_H2RQuant_NEW_KII_19_08_2019_final_2019_08_20_07_33_15"
cleaning_log_org_excel_sheet <- "log" #CLEANING LOG EXCEL SHEET NAME (IF EXCEL)
short_name <- 'H2R_August2019'
#HEADER DELIMITER OF COLUMN NAMES
header_delimiter <- "/"
alt_id <- "_index" #IF NOT ALL ID COLUMNS ARE UUID, DEFINE THE ALTERNATIVE (FOR KOBO LOOPS)
#############################LOAD PACKAGES######################################
if (!require(readxl)) install.packages('readxl')
library(readxl)
if (!require(weights)) install.packages('weights')
library(weights)
if (!require(pls)) install.packages('pls')
library(pls)
if (!require(gmodels)) install.packages('gmodels')
library(gmodels)
if (!require(splitstackshape)) install.packages('splitstackshape')
library(splitstackshape)
if (!require(ggplot2)) install.packages('ggplot2')
library(ggplot2)
if (!require(reshape2)) install.packages('reshape2')
library(reshape2)
if (!require(data.table)) install.packages('data.table')
library(data.table)
if (!require(magrittr)) install.packages('magrittr')
library(magrittr)
if (!require(scales)) install.packages('scales')
library(scales)
if (!require(tm)) install.packages('tm')
library(tm)
if (!require(SDMTools)) install.packages('SDMTools')
library(SDMTools)
if (!require(plotly)) install.packages('plotly')
library(plotly)
if (!require(tibble)) install.packages('tibble')
library(tibble)
if (!require(plotly)) install.packages('plotly')
library(plotly)
if (!require(tidyr)) install.packages('tidyr')
library(tidyr)
if (!require(stringr)) install.packages('stringr')
library(stringr)
if (!require(ggrepel)) install.packages('ggrepel')
library(ggrepel)
if (!require(reshape2)) install.packages('reshape2')
library(reshape2)
if (!require(MASS)) install.packages('MASS')
library(MASS)
if (!require(magrittr)) install.packages('magrittr')
library(magrittr)
if (!require(foreign)) install.packages('foreign')
library(foreign)
if (!require(sandwich)) install.packages('sandwich')
library(sandwich)
if (!require(lmtest)) install.packages('lmtest')
library(lmtest)
if (!require(corrplot)) install.packages('corrplot')
library(corrplot)
if (!require(RColorBrewer)) install.packages('RColorBrewer')
library(RColorBrewer)
if (!require(xtable)) install.packages('xtable')
library(xtable)
if (!require(Hmisc)) install.packages('Hmisc')
library(Hmisc)
if (!require(taRifx)) install.packages('taRifx')
library(taRifx)
if (!require(car)) install.packages('car')
library(car)
if (!require(readr)) install.packages('readr')
library(readr)
if (!require(plyr)) install.packages('plyr')
library(plyr)
if (!require(dplyr)) install.packages('dplyr')
library(dplyr)
#if (!require(tidyverse)) install.packages('tidyverse')
#library(tidyverse)
############################################################################################
############################################################################################
cleaning_folder <- "Raw_to_Cleaning_Process"
setwd(paste0(parent_folder,"/",cleaning_folder))
#IMPORT FOLDERS
cleaning_log_import_folder <- "Raw_Data" #FOLDER WHERE THE CLEANING LOG IS STORED
#OUTPUT FOLDERS
cleaning_output_folder <- "updated_cleaning_log" # UPDATED CLEANING LOG OUTPUT FOLDER
updated_data_folder <- "updated_data" #FOLDER WHERE UPDATED DATA GOES
#LOAD CLEANING LOG
cleaning_log_org_excel<- paste0(cleaning_log_import_folder,"/",cleaning_name,".xlsx")
cleaning_log_org <- read_excel(cleaning_log_org_excel, sheet= cleaning_log_org_excel_sheet)
cleaning_log_real_org <-cleaning_log_org
#ENSURE CLEANING LOG NAMES ARE THE SAME AS THE ORIGINAL
names(cleaning_log_org)<- c("folder", "dataset","sheet", "question", "old", "new", "reason", "_uuid", "modified", "cleaner_name")
number_cols_cleaning_log <- ncol(cleaning_log_org)
#CREATE NICE "uuid" COLUMN
cleaning_log_org$uuid <-cleaning_log_org$`_uuid`
#CREATE INDEX COLUMN
cleaning_log_org$index_number <- 1:nrow(cleaning_log_org)
#GRAB NEWEST CORRECTIONS (HIGHEST INDEX NUMBER)
cleaning_log_org <- cleaning_log_org %>% group_by(uuid, question) %>% top_n(n=1) %>% ungroup()
cleaning_log_first_setup <- cleaning_log_org
#FOR QUESTIONS: REPLACE "/" WITH "_"
cleaning_log_org$question <- cleaning_log_org$question %>%
gsub("/", "_", .)
#UNIQUE FOLDERS
folders <- unique(cleaning_log_first_setup$folder)
cleaning_folder_list_intofolder <- list()
cleaning_folder_list <- list()
cleaning_sheet_list <- list()
cleaning_dataset_list <- list()
###FIRST SET OF LOOPS: FOR EVERY FOLDER NAME
for(f in 1:length(folders)){ #FOLDER BEGIN
print(f)
folder <- folders[f]
#UNIQUE SURVEYS
surveys_full <- cleaning_log_first_setup %>% dplyr:: filter(folder==folders[f])
surveys <- unique(surveys_full$dataset)
#FOR EVERY EXCEL FILE (SURVEY)
for(j in 1: length(surveys)){ #SURVEYS IN FOLDER
survey_name <- surveys[j]
#SUBSET CLEANING LOG
cleaning_log_org_for_each_survey <- cleaning_log_first_setup %>%
dplyr:: filter(folder == folders[f] )%>% dplyr:: filter(dataset == surveys[j] )
sheets <- unique(cleaning_log_org_for_each_survey$sheet)
for(s in 1: length(sheets)){ #SHEETS IN DATASET
print("sheet")
print(s)
cleaning_log_org_for_each_sheet <- cleaning_log_org_for_each_survey %>%
dplyr:: filter(sheet == sheets[s] )
#IF "UUID" LETTER IS TRUE
any_alpha <- grepl("[[:alpha:]]", cleaning_log_org_for_each_sheet$uuid) #NO ALPHABET NUMBERS IF FALSE
any_alpha <- any(any_alpha)
#ALL QUESTIONS TO BE CLEANED
allquestions <- unique(cleaning_log_org_for_each_sheet$question)
if (uncleaned_data_file_type == "EXCEL"){
#UNCLEANED EXCEL FILE NAME
uncleaned_excel <- paste0(folder,"/", survey_name ,".xlsx")
#UNCLEANED EXCEL SHEET NAME
uncleaned <- read_excel(uncleaned_excel, sheet= sheets[s])
} else if (uncleaned_data_file_type == "CSV"){
uncleaned <- read_csv(paste0(folder,"/",survey_name, ".csv"))
} else {
print("UNCLEANED FILE TYPE ERROR")
}
###ADJUST INDEX TO BE UUID COLUMN
if( length(grep("^_uuid$",colnames(uncleaned)))>0 ){
uuid_index <- grep("^_uuid$",colnames(uncleaned))
} else {
uuid_index <- grep("uuid",colnames(uncleaned))
}
if( nrow(unique(uncleaned[uuid_index]))==1 ){
grep("uuid",colnames(uncleaned))
uncleaned$`_uuid` <- NULL
colnames(uncleaned)[grep("^_index$",colnames(uncleaned))] <- "index"
uncleaned <- uncleaned %>% dplyr:: rename(uuid = index)
print("INDEX NOT UUID")
} else {
colnames(uncleaned)[uuid_index] <- "uuid" #ADD UUID COLUMN
#uncleaned <- uncleaned
print("UUID GOOD")
}
##############BEGIN CHANGE HEADERS##############
colnames(uncleaned) <- gsub(header_delimiter, "_", colnames(uncleaned))
#REMOVE DUPLICATE COLUMNS
uncleaned <- uncleaned[, !duplicated(colnames(uncleaned))]
##############END CHANGE HEADERS##############
##CHANGE FROM UUID TO "_index"
if(any_alpha == FALSE){
print("INDEX NOT UUID")
uuid_columns <- grep("uuid",colnames(uncleaned))
uncleaned <- uncleaned[, -c(uuid_columns)]
index_column <- grep("^",alt_id,"$",colnames(uncleaned))
colnames(uncleaned)[index_column] <- "uuid"
} else{
uncleaned <- uncleaned
}
#FILTER OUT ON THIS MONTH'S CORRECTIONS
cleaning_log <- cleaning_log_org_for_each_sheet
cleaning_log <- data.frame(lapply(cleaning_log, function(x) {gsub(header_delimiter, "_", x)}))
#NOTE--FIX "_uuid" to "uuid"
cleaning_log$question <- str_replace( cleaning_log$question, "_uuid", "uuid")
#LIST OF QUESTIONS IN THE CLEANING LOG SUBSET
# detach("package:plyr")
# library(dplyr)
cleaning_log_nulls <- cleaning_log %>% dplyr::filter(new == "NULL" )
null_entries <- as.character(cleaning_log_nulls$uuid)
cleaning_log_no_null <- cleaning_log %>% dplyr::filter(!uuid %in% c(null_entries))
colquestion <- as.character(unique(cleaning_log_no_null$question))
#REMOVE IF NOT A HEADER IN THE DATA
colquestion <- colquestion[(colquestion %in% colnames(uncleaned))]
#WARNING: CLEANING QUESTION NAME DOES NOT EXIST IN THE UNCLEANED DATASET
###LOOP BEGIN
#EMPTY LIST FOR UPDATED QUESTIONS
keep_q<-list()
#CREATE COPIES OF DATA AND CLEANING LOG
uncleaned_added_correction <- uncleaned
cleaning_log_all_updated <- cleaning_log
###UPDATE DATA SHEET LOOP
for(i in seq_along(colquestion)){ #START QUESTION
print("questions")
print(i)
corrected_question_in_df <- data.frame()
#SUBSET EACH CLEANING QUESTION FROM CLEANING LOG
clean_log_one_question<- cleaning_log %>%
dplyr:: filter(question == colquestion[i])
clean_log_one_question <- remove.factors(clean_log_one_question)
if (i >= 2){
colnames(uncleaned_added_correction)[grep("uuid.x" , colnames(uncleaned_added_correction))] <- "idd"
uncleaned_added_correction <- uncleaned_added_correction %>% dplyr:: mutate() %>% dplyr:: select (-contains("uuid")) %>% dplyr:: rename(uuid = idd)
} else {
print("FIRST LOOP -- NO DUPLICATE DEALINGS")
}
#DATA UNIQUE ID
uncleaned_added_correction$unique_idx <- paste0(unlist(uncleaned_added_correction$uuid) , "_", as.vector(unlist(uncleaned_added_correction[grep(paste0("^",colquestion[i],"$"),colnames(uncleaned_added_correction))])) )
uncleaned_added_correction$unique_idx <- paste0(uncleaned_added_correction$unique_idx, "_", ave(uncleaned_added_correction$unique_idx ,uncleaned_added_correction$unique_idx , FUN=seq_along) )
#CLEANING LOG UNIQUE ID
clean_log_one_question$unique_idx <- paste0(clean_log_one_question$uuid , "_" ,clean_log_one_question$old)
clean_log_one_question$unique_idx <- paste0(clean_log_one_question$unique_idx , "_" , ave(clean_log_one_question$unique_idx ,clean_log_one_question$unique_idx , FUN=seq_along))
#ADD CLEANING QUESTION TO DATASET
newgo <- merge(uncleaned_added_correction, clean_log_one_question ,by="unique_idx",all.x=TRUE)
unique_idx <- newgo$unique_idx
#FIND INDEX OF QUESTION TO REPLACE IN THE DATASET
org_index_question <-grep( paste0("^",colquestion[i],"$"),colnames(newgo))
#FIND INDEX OF CLEANING QUESTION COLUMN
question_to_replace_index <- grep( "^question$",colnames(newgo))
#FIND INDEX OF REPLACEMENT INFO (CLEANING) COLUMN
new_answer_index <- grep( "^new$",colnames(newgo))
#COPY ORIGINAL UNCLEANED RESPONSE COLUMN
newgo$question_clone <- newgo[,org_index_question]
question_clone_index <- grep( "^question_clone$",colnames(newgo))
#SUBSET RELEVANT COLUMNS
trim_newgo <- newgo[,c(org_index_question,question_to_replace_index,new_answer_index,question_clone_index)]
#UPDATE ONE QUESTION AT A TIME
trim_newgo[,5] <- ifelse(!is.na(trim_newgo[,2]), as.vector(trim_newgo[,3]),trim_newgo[,4])
keep_q[[i]] <- trim_newgo[,5]
#SAVE "uuid" FROM "newgo" TO JOIN TO "uncleaned"
#REMOVE MULTIPLE UUID COLUMNS
newgo$idd <- as.vector(newgo[,min(grep("uuid",colnames(newgo)))])
newgo <- newgo %>% dplyr:: select(-contains("uuid")) %>% dplyr:: rename(uuid=idd)
newgo <- newgo[, !duplicated(colnames(newgo))]
corrected_question_uuid<- newgo[,grep("^uuid$", colnames(newgo))]
#ADD CORRECTED QUESTION WITH "uuid"
corrected_question_with_uuid_df <- as.data.frame(cbind(corrected_question_uuid,keep_q[[i]],unique_idx))
#RENAME CORRECTED QUESTION SUBSET
colnames(corrected_question_with_uuid_df)[1] <- "uuid"
colnames(corrected_question_with_uuid_df)[2] <- "new_question"
#UPDATE "uncleaned"
uncleaned_added_correction <- merge(uncleaned_added_correction, corrected_question_with_uuid_df,by="unique_idx", all.x=TRUE)
question_needed <- grep(paste0("^",colquestion[i],"$"),colnames(uncleaned_added_correction))
uncleaned_added_correction[,question_needed] <- uncleaned_added_correction$new_question
uncleaned_added_correction$new_question <- NULL
trim_newgo<-NULL
clean_log_one_question$unique_idx<-NULL
#UPDATE CLEANING LOG
clean_log_one_question$modified<-"yes"
clean_log_update <- subset(cleaning_log_all_updated, !(index_number %in% clean_log_one_question$index_number))
cleaning_log_all_updated <-rbind(clean_log_update,clean_log_one_question)
} #END QUESTION
cleaning_sheet_list[[s]] <- cleaning_log_all_updated
#RENAME ADJUSTED DATA
cleaned_up <- uncleaned_added_correction
#EXPORT TO CSV
if( length(grep("^uuid.x$",colnames(cleaned_up)))>0 ) {
cleaned_up <- cleaned_up %>% dplyr:: mutate(idx = uuid.x) %>% dplyr:: select(-c(unique_idx, uuid.x, uuid.y))%>% dplyr:: rename(uuid = idx)
} else {
cleaned_up <- cleaned_up
}
#REMOVE NULL QUESTIONS
cleaning_log_null <- cleaning_log_org %>% dplyr:: filter(new=="NULL") %>% dplyr:: filter(sheet == sheets[s]) %>% dplyr:: select(uuid) %>% dplyr:: distinct(uuid)
if(nrow(cleaning_log_null)>0){
cleaned_up <- cleaned_up[ ! as.character(cleaned_up$uuid) %in% unique(cleaning_log_null$uuid), ]
} else{
cleaned_up <- cleaned_up
}
write.csv(cleaned_up,paste0(folders[f],"/",updated_data_folder,"/","cleanedh2r_", short_name,"_", sheets[s], ".csv") ,na = "")
} #SHEET END
cleaning_dataset_list[[j]] <- cleaning_sheet_list
} #SURVEY END
cleaning_folder_list_intofolder[[f]] <- cleaning_dataset_list
} #END FOLDER
cleaning_folder_list_intofolder[sapply(cleaning_folder_list_intofolder, is.null)] <- NULL
#ALT CONVERT LIST OF LISTS TO DF
flat = unlist(cleaning_folder_list_intofolder, recursive = FALSE)
flat = unlist(flat, recursive = FALSE)
cleaning_log_all_updated <-ldply(flat, data.frame)
#Confirm/Deny NULL removals in the cleaning log
if(nrow(cleaning_log_null)>0){
print("NULLS REMOVED")
cleaning_log_null$onesz <- 1
cleaning_log_all_updated <- merge(cleaning_log_all_updated, cleaning_log_null, by="uuid", all.x=TRUE)
cleaning_log_all_updated$modified <- ifelse(as.character.factor(cleaning_log_all_updated$modified) =="no" & cleaning_log_all_updated$onesz==1, "yes",as.character.factor(cleaning_log_all_updated$modified))
cleaning_log_all_updated$onesz <- NULL
} else{
print("NO NULLS REMOVED")
cleaning_log_all_updated <- cleaning_log_all_updated
}
####SECOND SET OF LOOPS: JOIN WITH ORGINAL CLEANING SHEET
clean_log_update <- subset(cleaning_log_org, !(index_number %in% cleaning_log_all_updated$index_number))
names(clean_log_update) <- names(cleaning_log_all_updated)
#ROWBIND UPDATED WITH NON-UPDATED
cleaning_log_all_updated <- rbind(clean_log_update,cleaning_log_all_updated)
#DELETE REPEATED CLEANS PER-QUESTION
recent_cleans_quest <- list()
recent_cleans_survey <- list()
recent_cleans_folder <- list()
for(j in seq_along(folders)){
folder_sub <- subset(cleaning_log_all_updated, folder == folders[j])
all_surveys <- as.character(unique(folder_sub$dataset))
for(k in seq_along(all_surveys)){
survey_sub <- subset(folder_sub, dataset == all_surveys[k])
questions_per_survey <- as.character(unique(survey_sub$question))
for(i in seq_along(questions_per_survey)){
one_question <- subset(survey_sub, question == questions_per_survey[i])
one_question$index_number <- as.numeric(as.character( one_question$index_number))
latest_clean_perquestion <- one_question %>%
group_by(uuid) %>%
filter(index_number == max(index_number))
latest_clean_perquestion <- data.frame(lapply(latest_clean_perquestion, as.character), stringsAsFactors=FALSE)
recent_cleans_quest[[i]] <- latest_clean_perquestion
}
recent_cleans_survey[[k]] <- recent_cleans_quest
}
recent_cleans_folder[[j]] <- recent_cleans_survey
}
#UNLIST LIST OF LISTS
flat = unlist(recent_cleans_folder, recursive = FALSE)
flat2 = unlist(flat, recursive = FALSE)
cleaning_log_all_updated <- do.call(rbind.data.frame, flat2)
cleaning_log_all_updated <- cleaning_log_all_updated[!duplicated(cleaning_log_all_updated$index_number),]
#CLEAN FILE
cleaning_log_all_updated$index_number <- NULL
cleaning_log_all_updated$uuid <- NULL
names(cleaning_log_all_updated) <- names(cleaning_log_real_org)
write.csv(cleaning_log_all_updated,paste0(cleaning_log_import_folder,"/",cleaning_output_folder,"/","UPDATED_CLEANING_LOG_",short_name,".csv"), na = "")
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