R/water.R
In validmeasures/wsup: An Implementation of the WSUP Urban Water and Sanitation Survey in R
Defines functions
get_water_vars
Documented in
get_water_vars
################################################################################
#
#' Calculate indicators: Water
#'
#' @param surveyData A data frame containing survey data with information for
#' caluclating water indicators.
#' @return A data frame containing calculated water indicators
#' @examples
#' # Apply get_water_vars() to surveyDataBGD dataset
#' waterDF <- get_water_vars(washdata::surveyDataBGD)
#'
#' @export
#'
#
################################################################################
get_water_vars <- function(surveyData) {
## waterSource: source of drinking water
waterSource <- ifelse(surveyData$water1 == "Other (please specify)",
surveyData$water2,
surveyData$water1)
waterSource <- ifelse(waterSource == "Deep tube well ",
"Deep tube well",
waterSource)
waterSource <- ifelse(waterSource == "Shallow tubwell",
"Shallow tube well",
waterSource)
## water1: improved source of drinking water
water1 <- ifelse(waterSource %in% c("Bottled water",
"Deep tube well",
"Piped water into dwelling",
"Piped water to yard/plot",
"Public tap/standpipe/kiosk",
"Water lifted by motor",
"Cart with small tank/drum or tanker-truck",
"Rainwater collection"), 1, 0)
## water2: formal/informal source of drinking water for Pareto chart
water2 <- ifelse(surveyData$water3 == "", "Don't know", surveyData$water3)
## water2a: formal/informal source of drinking water for estimation
water2a <- ifelse(surveyData$water3 == "", NA,
ifelse(surveyData$water3 == "Formal", 1, 0))
## water3: source of water a WSUP-supported facility
water3 <- ifelse(surveyData$water5 == "", "Don't know", surveyData$water5)
## water3a: source of water a WSUP-supported facility estimation
water3a <- ifelse(surveyData$water5 == "", NA,
ifelse(surveyData$water5 == "Yes", 1, 0))
## water4: mean number of hours per day water is available
water4 <- surveyData$water7
## water4a: water available at least 12 hours (half a day)
water4a <- ifelse(surveyData$water7 >= 12, 1, 0)
## water4b: water available for full day
water4b <- ifelse(is.na(surveyData$water7), 0,
ifelse(surveyData$water7 == 24, 1, 0))
## water5: mean number of days per week water available
water5 <- ifelse(surveyData$water9 == "", NA,
ifelse(surveyData$water9 == "7 day per week", 7,
ifelse(surveyData$water9 == "6 day per week", 6,
ifelse(surveyData$water9 == "5 day per week", 5,
ifelse(surveyData$water9 == "4 day per week", 4,
ifelse(surveyData$water9 == "3 day per week", 3,
ifelse(surveyData$water9 == "2 day per week", 2,
ifelse(surveyData$water9 == "1 day per week", 1, 0))))))))
## water5a: water available more than 3 days a week
water5a <- ifelse(water5 > 3, 1, 0)
## water5b: water available the whole week
water5b <- ifelse(is.na(water5), 0,
ifelse(water5 == 7, 1, 0))
## water6: water available for the whole year
water6 <- ifelse(surveyData$water11 == "", "Don't know",
ifelse(surveyData$water11 == "Yes", "Yes", "No"))
## water6a: water available for the whole year (estimation)
water6a <- ifelse(surveyData$water11 == "", 0,
ifelse(surveyData$water11 == "Yes", 1, 0))
## water7: mean number of minutes to collect water
water7 <- ifelse(is.na(surveyData$water14), 0, surveyData$water14)
## water7a: distance to water source is within 30 minutes or less
water7a <- ifelse(water7 <= 30, 1, 0)
## water7b: satisfied with distance between home and water source
water7b <- ifelse(surveyData$water16 == "", 1,
ifelse(surveyData$water16 == "Yes", 1, 0))
## water7c: satisfied with distance between home and water source (estimate)
water7c <- ifelse(water7b == 2, NA, water7b)
## water8: satisfied with queuing time
water8 <- vector(mode = "numeric", length = nrow(surveyData))
water8[surveyData$water18 == "No"] <- 0
water8[surveyData$water18 == "Yes"] <- 1
water8[surveyData$water18 == "" & surveyData$water19 == TRUE] <- 2
water8[surveyData$water18 == "" & surveyData$water20 == TRUE] <- 3
water8[is.na(surveyData$water18) &
is.na(surveyData$water19) &
is.na(surveyData$water20)] <- 4
## water8a: satisfied with queuing time
water8a <- ifelse(water8 %in% 2:4, NA, water8)
## water9: person who usually collects water
## waterCollect: person who usually collects water
waterCollect <- ifelse(surveyData$water21 == "Other (please specify)",
surveyData$water22,
surveyData$water21)
waterCollect <- ifelse(waterCollect == "",
NA,
waterCollect)
waterCollect <- ifelse(waterCollect == "Source inside house",
NA,
waterCollect)
waterCollect <- stringr::str_split(string = waterCollect, pattern = ", ", simplify = TRUE)
## Create temporary container for vector outputs
temp <- NULL
## Cycle through columns of waterCollect
for(i in 1:ncol(waterCollect)) {
## Concatenate waterCollect columns into a single vector
temp <- c(temp, waterCollect[ , i])
}
## Re-assign NA value to "" answers
temp <- ifelse(temp == "", NA, temp)
## Get responses
tempNames <- names(table(temp))
## Create empty vector container
water9 <- NULL
## Cycle through responses
for(i in 1:length(tempNames)) {
## Create empty vector with length of surveyData
assign(paste("water9", letters[i], sep = ""),
vector(mode = "numeric", length = nrow(surveyData)))
## Cycle through data columns in waterCollect
for(j in 1:ncol(waterCollect)) {
## Assign values
x <- ifelse(waterCollect[ , j] == tempNames[i], i, 0)
## Concatenate responses
assign(paste("water9", letters[i], sep = ""),
get(paste("water9", letters[i], sep = "")) + x)
}
## Rename responses to character strings
assign(paste("water9", letters[i], sep = ""),
ifelse(get(paste("water9", letters[i], sep = "")) == i, tempNames[i], NA))
##
water9 <- data.frame(cbind(water9,
get(paste("water9", letters[i], sep = ""))))
}
## Rename the data.frame
names(water9) <- paste("water9", letters[1:length(tempNames)], sep = "")
## water10: amount of water (litres) used by household per day
water10 <- ifelse(surveyData$water23 == "", "Don't know", surveyData$water23)
## water10a: amount of water sufficient
water10a <- ifelse(surveyData$water25 == "", "Don't know", surveyData$water25)
## water10b: amount of water sufficient (estimate)
water10b <- ifelse(water10a == "Don't know", NA,
ifelse(water10a == "Yes", 1, 0))
## water11: water from other sources
## Re-code "Don't know"
water11 <- ifelse(surveyData$water27 == "", "Don't know", surveyData$water27)
## Re-code NAs
water11a <- ifelse(water11 == "Don't know", NA,
ifelse(water11 == "Yes", 1, 0))
## Re-code factors
water11b <- ifelse(surveyData$water29 == "", NA,
ifelse(surveyData$water29 == "Other (please specify)",
surveyData$water30, surveyData$water29))
## Re-code
water11b <- ifelse(water11b == "", NA, water11b)
water11b[water11b == "Mosque"] <- "Mosque, school, etc."
water11b[water11b %in% c("Neighbour's house",
"Pump point of water")] <- "Other's water point"
water11b[water11b == "Deep tube well"] <- "Tube well"
water11b[water11b == "Cann't arranged"] <- "Can't arrange"
## Re-code
water11c <- ifelse(water11b %in% c("Bottled water",
"Piped water into dwelling",
"Piped water to yard/plot",
"Protected well or spring in yard",
"Public tap/standpipe/kiosk",
"Tube well",
"Water lifted by motor"), 1,
ifelse(is.na(water11b), 0, 0))
## Re-code
water11d <- ifelse(water1 == 1 & water7a == 1 &
water4b == 1 & water5b == 1 & water6a == 1, 1,
ifelse(water1 == 1 & water7a == 1 &
((water4b == 0 | water5b == 0 | water6a == 0) &
water11c == 1), 1, 0))
## water12: spend on water
## mean spend on water
water12 <- ifelse(surveyData$water32 == "", NA, surveyData$water32)
## satisfied with price of water
water12a <- ifelse(surveyData$water35 == "", "Don't know", surveyData$water35)
## satisfied with price of water - estimate
water12b <- ifelse(water12a == "Don't know", NA,
ifelse(water12a == "Yes", 1, 0))
## water13: investment in improving water source
## Recode
water13 <- ifelse(surveyData$water37 == "", "Don't know", surveyData$water37)
## Recode
water13a <- ifelse(water13 == "Don't know", NA,
ifelse(water13 == "Yes", 1, 0))
## water14: water quality
## Recode
water14 <- ifelse(surveyData$water40 == "", "Don't know", surveyData$water40)
## Recode
water14a <- ifelse(water14 == "Don't know", NA,
ifelse(water14 == "Yes", 1, 0))
## water15: water quality improvement
## waterImprovement: water quality improvement
waterImprovement <- ifelse(surveyData$water42 == "Other improvement (please specify)",
surveyData$water43,
surveyData$water42)
waterImprovement <- ifelse(waterImprovement == "",
"Don't know/no answer/not applicable",
waterImprovement)
waterImprovement <- str_split(string = waterImprovement, pattern = ", ", simplify = TRUE)
## Create temporary container for vector outputs
temp <- NULL
## Cycle through columns of waterImprovement
for(i in 1:ncol(waterImprovement)) {
waterImprovement[ , i] <- ifelse(waterImprovement[ , i] == "Other improvement (please specify)",
surveyData$water43,
waterImprovement[ , i])
}
## Cycle through columns of waterImprovement
for(i in 1:ncol(waterImprovement)) {
## Concatenate waterImprovement columns into a single vector
temp <- c(temp, waterImprovement[ , i])
}
## Re-assign NA value to "" answers
temp <- ifelse(temp == "", NA, temp)
## Get responses
tempNames <- names(table(temp))
## Create vector accumulator
water15 <- NULL
## Cycle through responses
for(i in 1:length(tempNames))
{
## Create empty vector with length of surveyData
assign(paste("water15", letters[i], sep = ""),
vector(mode = "numeric", length = nrow(surveyData)))
## Cycle through data columns in waterCollect
for(j in 1:ncol(waterImprovement))
{
## Assign values
x <- ifelse(waterImprovement[ , j] == tempNames[i], i, 0)
## Concatenate responses
assign(paste("water15", letters[i], sep = ""),
get(paste("water15", letters[i], sep = "")) + x)
}
## Rename responses to character strings
assign(paste("water15", letters[i], sep = ""),
ifelse(get(paste("water15", letters[i], sep = "")) == i, tempNames[i], NA))
## Create water quality data.frame
water15 <- data.frame(cbind(water15, get(paste("water15", letters[i], sep = ""))))
}
## Rename the data.frame
names(water15) <- paste("water15", letters[1:length(tempNames)], sep = "")
## water16: water pressure
## Re-code
water16 <- ifelse(surveyData$water45 == "", "Don't know", surveyData$water45)
## Re-code
water16a <- ifelse(water16 == "Don't know", NA,
ifelse(water16 == "Yes", 1, 0))
## water17: support provider
## Re-code
water17 <- ifelse(surveyData$water47 == "", "Don't know/not applicable",
ifelse(surveyData$water47 == "Other (please specify)",
surveyData$water48, surveyData$water47))
## Re-code
water17 <- ifelse(water17 == "", "Don't know/not applicable", water17)
## Re-code: these lines of code [473-495] are Dhaka, Bangladesh 2017 specific.
water17 <- ifelse(water17 == "Landlord/House owner ", "Landlord/House owner",
ifelse(water17 == "Caretaker ", "Caretaker",
ifelse(water17 %in% c("Gaurd", "Gaurd "), "Guard",
ifelse(water17 %in% c("No complain arise",
"No complain arise",
"Till lemdon't face any problem"), "No complaints",
ifelse(water17 == "Water office ", "Water office",
ifelse(water17 == "Do no't cpmlain", "Do not complain",
ifelse(water17 == "Parlament Member (MP)", "Parliament Member (MP)",
ifelse(water17 == "Relavent office", "Relevant office",
ifelse(water17 == "Messengaer ", "Messenger",
ifelse(water17 == "Local Gverenment Engineering office", "Local Government Engineering office",
water17))))))))))
## Re-code: these lines of code [499-506] are Dhaka, Bangladesh 2017 specific
water17 <- ifelse(water17 %in% c("Facility operator",
"Local Government Engineering office",
"Power and Water Development office",
"Relevant office",
"Water office",
"Water supplier",
"Water utility",
"Women Affair Directory"), 1, 0)
################################################################################
#
# water18: water storage
#
################################################################################
## waterStorage
waterStorage <- ifelse(as.character(surveyData$wash60) == "",
"Don't know/not applicable",
as.character(surveyData$wash60))
waterStorage <- stringr::str_split(string = waterStorage, pattern = ", ", simplify = TRUE)
## water18a: Clean container (with lid)
water18a <- vector(mode = "numeric", length = nrow(surveyData))
water18a[waterStorage[,1] == "Clean container (with lid)" |
waterStorage[,2] == "Clean container (with lid)" |
waterStorage[,3] == "Clean container (with lid)"] <- 1
## water18b: Clean container (without lid)
water18b <- vector(mode = "numeric", length = nrow(surveyData))
water18b[waterStorage[,1] == "Clean container (without lid)" |
waterStorage[,2] == "Clean container (without lid)" |
waterStorage[,3] == "Clean container (without lid)"] <- 2
## water18c: Dirty container
water18c <- vector(mode = "numeric", length = nrow(surveyData))
water18c[waterStorage[,1] == "Dirty container" |
waterStorage[,2] == "Dirty container" |
waterStorage[,3] == "Dirty container"] <- 3
## water18d: Don't know/not applicable
water18d <- vector(mode = "numeric", length = nrow(surveyData))
water18d[waterStorage[,1] == "Don't know/not applicable" |
waterStorage[,2] == "Don't know/not applicable" |
waterStorage[,3] == "Don't know/not applicable"] <- 4
## water18
water18 <- ifelse(water18d == 4, NA,
ifelse(water18a == 1 & water18b != 2 & water18c != 3, 1, 0))
## waterQuality: this indicator was not collected in survey. For future
# surveys, if water quality tests are performed, this indicator
# will be calculated based on that data.
# Check whether waterQualityDF has been loaded
if(exists("waterQualityDF")) {
## Add logic here to process water quality data with waterQuality variable as
## the result to be used for calculating indicators
} else
## Assign NULL value to waterQuality variable if waterQualityDF is not available
waterQuality <- NULL
## JMP indicators for drinking water - post-2015
## Surface water: river, dam, lake, pond, stream, canal or irrigation channel
jmpWater1 <- ifelse(waterSource == "Surface water", 1, 0)
## Unimproved: unprotected dug wells, unprotected springs
jmpWater2 <- vector(mode = "numeric", length = nrow(surveyData))
jmpWater2[water1 != 1 & waterSource != "Surface water"] <- 1
## Limited: Improved but more than 30 minutes collection time
jmpWater3 <- vector(mode = "numeric", length = nrow(surveyData))
jmpWater3[water1 == 1 & water7a == 0] <- 1
## Determine if water quality data is available
if(is.null(waterQuality)) {
## At least basic: improved and no more than 30 minutes collection time
jmpWater4 <- vector(mode = "numeric", length = nrow(surveyData))
jmpWater4[water1 == 1 & water7a == 1] <- 1
## no safely managed: create jmpWater5 empty vector
jmpWater5 <- vector(mode = "numeric", length = nrow(surveyData))
jmpWater5[jmpWater5 == 0] <- NA
} else {
## Basic: Improved and no more than 30 minutes collection time
jmpWater4 <- vector(mode = "numeric", length = nrow(surveyData))
##
jmpWater4[water1 == 1 &
!waterSource %in% c("Piped water into dwelling",
"Piped water to yard/plot",
"Protected dug well or spring in yard") &
water7a == 1] <- 1
##
jmpWater4[water1 == 1 &
waterSource %in% c("Piped water into dwelling",
"Piped water to yard/plot",
"Protected dug well or spring in yard") &
(water4a == 0 | water5b == 0 | water6a == 0) &
water7a == 1] <- 1
## Self-managed: improved and no more than 30 minutes collection time and available
# when needed and free from priority contamination
jmpWater5 <- vector(mode = "numeric", length = nrow(surveyData))
##
jmpWater5[water1 == 1 &
waterSource %in% c("Piped water into dwelling",
"Piped water to yard/plot",
"Protected dug well or spring in yard") &
water4a == 1 &
water5b == 1 &
water6a == 1 &
waterQuality == 1] <- 1
}
## accessWater: Access to sufficient and sustained drinking water
## Re-code
accessWater <- ifelse(water10 %in% c("61-100 litres per day",
"101-150 litres per day",
"150-200 litres per day",
"201-300 literes per day",
">301 litres per day") &
water4b == 1 & water5b == 1 & water6a == 1, 1, 0)
## Create waterDF
## Concatenate water indicators
waterDF <- data.frame("uniqueID" = surveyData[ , "uniqueID"],
waterSource, water1, water2, water2a, water3, water3a,
water4, water4a, water4b, water5, water5a, water5b,
water6, water6a, water7, water7a, water7b, water7c, water8, water8a,
water9, water10, water10a, water10b,
water11, water11a, water11b, water11c, water11d,
water12, water12a, water12b,
water13, water13a,
water14, water14a,
water16, water16a,
water17, water18,
jmpWater1, jmpWater2, jmpWater3, jmpWater4, jmpWater5,
accessWater)
## Return results
return(waterDF)
}
validmeasures/wsup documentation built on Dec. 16, 2019, 4:50 a.m.
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Defines functions get_water_vars
Documented in get_water_vars
################################################################################
#
#' Calculate indicators: Water
#'
#' @param surveyData A data frame containing survey data with information for
#' caluclating water indicators.
#' @return A data frame containing calculated water indicators
#' @examples
#' # Apply get_water_vars() to surveyDataBGD dataset
#' waterDF <- get_water_vars(washdata::surveyDataBGD)
#'
#' @export
#'
#
################################################################################
get_water_vars <- function(surveyData) {
## waterSource: source of drinking water
waterSource <- ifelse(surveyData$water1 == "Other (please specify)",
surveyData$water2,
surveyData$water1)
waterSource <- ifelse(waterSource == "Deep tube well ",
"Deep tube well",
waterSource)
waterSource <- ifelse(waterSource == "Shallow tubwell",
"Shallow tube well",
waterSource)
## water1: improved source of drinking water
water1 <- ifelse(waterSource %in% c("Bottled water",
"Deep tube well",
"Piped water into dwelling",
"Piped water to yard/plot",
"Public tap/standpipe/kiosk",
"Water lifted by motor",
"Cart with small tank/drum or tanker-truck",
"Rainwater collection"), 1, 0)
## water2: formal/informal source of drinking water for Pareto chart
water2 <- ifelse(surveyData$water3 == "", "Don't know", surveyData$water3)
## water2a: formal/informal source of drinking water for estimation
water2a <- ifelse(surveyData$water3 == "", NA,
ifelse(surveyData$water3 == "Formal", 1, 0))
## water3: source of water a WSUP-supported facility
water3 <- ifelse(surveyData$water5 == "", "Don't know", surveyData$water5)
## water3a: source of water a WSUP-supported facility estimation
water3a <- ifelse(surveyData$water5 == "", NA,
ifelse(surveyData$water5 == "Yes", 1, 0))
## water4: mean number of hours per day water is available
water4 <- surveyData$water7
## water4a: water available at least 12 hours (half a day)
water4a <- ifelse(surveyData$water7 >= 12, 1, 0)
## water4b: water available for full day
water4b <- ifelse(is.na(surveyData$water7), 0,
ifelse(surveyData$water7 == 24, 1, 0))
## water5: mean number of days per week water available
water5 <- ifelse(surveyData$water9 == "", NA,
ifelse(surveyData$water9 == "7 day per week", 7,
ifelse(surveyData$water9 == "6 day per week", 6,
ifelse(surveyData$water9 == "5 day per week", 5,
ifelse(surveyData$water9 == "4 day per week", 4,
ifelse(surveyData$water9 == "3 day per week", 3,
ifelse(surveyData$water9 == "2 day per week", 2,
ifelse(surveyData$water9 == "1 day per week", 1, 0))))))))
## water5a: water available more than 3 days a week
water5a <- ifelse(water5 > 3, 1, 0)
## water5b: water available the whole week
water5b <- ifelse(is.na(water5), 0,
ifelse(water5 == 7, 1, 0))
## water6: water available for the whole year
water6 <- ifelse(surveyData$water11 == "", "Don't know",
ifelse(surveyData$water11 == "Yes", "Yes", "No"))
## water6a: water available for the whole year (estimation)
water6a <- ifelse(surveyData$water11 == "", 0,
ifelse(surveyData$water11 == "Yes", 1, 0))
## water7: mean number of minutes to collect water
water7 <- ifelse(is.na(surveyData$water14), 0, surveyData$water14)
## water7a: distance to water source is within 30 minutes or less
water7a <- ifelse(water7 <= 30, 1, 0)
## water7b: satisfied with distance between home and water source
water7b <- ifelse(surveyData$water16 == "", 1,
ifelse(surveyData$water16 == "Yes", 1, 0))
## water7c: satisfied with distance between home and water source (estimate)
water7c <- ifelse(water7b == 2, NA, water7b)
## water8: satisfied with queuing time
water8 <- vector(mode = "numeric", length = nrow(surveyData))
water8[surveyData$water18 == "No"] <- 0
water8[surveyData$water18 == "Yes"] <- 1
water8[surveyData$water18 == "" & surveyData$water19 == TRUE] <- 2
water8[surveyData$water18 == "" & surveyData$water20 == TRUE] <- 3
water8[is.na(surveyData$water18) &
is.na(surveyData$water19) &
is.na(surveyData$water20)] <- 4
## water8a: satisfied with queuing time
water8a <- ifelse(water8 %in% 2:4, NA, water8)
## water9: person who usually collects water
## waterCollect: person who usually collects water
waterCollect <- ifelse(surveyData$water21 == "Other (please specify)",
surveyData$water22,
surveyData$water21)
waterCollect <- ifelse(waterCollect == "",
NA,
waterCollect)
waterCollect <- ifelse(waterCollect == "Source inside house",
NA,
waterCollect)
waterCollect <- stringr::str_split(string = waterCollect, pattern = ", ", simplify = TRUE)
## Create temporary container for vector outputs
temp <- NULL
## Cycle through columns of waterCollect
for(i in 1:ncol(waterCollect)) {
## Concatenate waterCollect columns into a single vector
temp <- c(temp, waterCollect[ , i])
}
## Re-assign NA value to "" answers
temp <- ifelse(temp == "", NA, temp)
## Get responses
tempNames <- names(table(temp))
## Create empty vector container
water9 <- NULL
## Cycle through responses
for(i in 1:length(tempNames)) {
## Create empty vector with length of surveyData
assign(paste("water9", letters[i], sep = ""),
vector(mode = "numeric", length = nrow(surveyData)))
## Cycle through data columns in waterCollect
for(j in 1:ncol(waterCollect)) {
## Assign values
x <- ifelse(waterCollect[ , j] == tempNames[i], i, 0)
## Concatenate responses
assign(paste("water9", letters[i], sep = ""),
get(paste("water9", letters[i], sep = "")) + x)
}
## Rename responses to character strings
assign(paste("water9", letters[i], sep = ""),
ifelse(get(paste("water9", letters[i], sep = "")) == i, tempNames[i], NA))
##
water9 <- data.frame(cbind(water9,
get(paste("water9", letters[i], sep = ""))))
}
## Rename the data.frame
names(water9) <- paste("water9", letters[1:length(tempNames)], sep = "")
## water10: amount of water (litres) used by household per day
water10 <- ifelse(surveyData$water23 == "", "Don't know", surveyData$water23)
## water10a: amount of water sufficient
water10a <- ifelse(surveyData$water25 == "", "Don't know", surveyData$water25)
## water10b: amount of water sufficient (estimate)
water10b <- ifelse(water10a == "Don't know", NA,
ifelse(water10a == "Yes", 1, 0))
## water11: water from other sources
## Re-code "Don't know"
water11 <- ifelse(surveyData$water27 == "", "Don't know", surveyData$water27)
## Re-code NAs
water11a <- ifelse(water11 == "Don't know", NA,
ifelse(water11 == "Yes", 1, 0))
## Re-code factors
water11b <- ifelse(surveyData$water29 == "", NA,
ifelse(surveyData$water29 == "Other (please specify)",
surveyData$water30, surveyData$water29))
## Re-code
water11b <- ifelse(water11b == "", NA, water11b)
water11b[water11b == "Mosque"] <- "Mosque, school, etc."
water11b[water11b %in% c("Neighbour's house",
"Pump point of water")] <- "Other's water point"
water11b[water11b == "Deep tube well"] <- "Tube well"
water11b[water11b == "Cann't arranged"] <- "Can't arrange"
## Re-code
water11c <- ifelse(water11b %in% c("Bottled water",
"Piped water into dwelling",
"Piped water to yard/plot",
"Protected well or spring in yard",
"Public tap/standpipe/kiosk",
"Tube well",
"Water lifted by motor"), 1,
ifelse(is.na(water11b), 0, 0))
## Re-code
water11d <- ifelse(water1 == 1 & water7a == 1 &
water4b == 1 & water5b == 1 & water6a == 1, 1,
ifelse(water1 == 1 & water7a == 1 &
((water4b == 0 | water5b == 0 | water6a == 0) &
water11c == 1), 1, 0))
## water12: spend on water
## mean spend on water
water12 <- ifelse(surveyData$water32 == "", NA, surveyData$water32)
## satisfied with price of water
water12a <- ifelse(surveyData$water35 == "", "Don't know", surveyData$water35)
## satisfied with price of water - estimate
water12b <- ifelse(water12a == "Don't know", NA,
ifelse(water12a == "Yes", 1, 0))
## water13: investment in improving water source
## Recode
water13 <- ifelse(surveyData$water37 == "", "Don't know", surveyData$water37)
## Recode
water13a <- ifelse(water13 == "Don't know", NA,
ifelse(water13 == "Yes", 1, 0))
## water14: water quality
## Recode
water14 <- ifelse(surveyData$water40 == "", "Don't know", surveyData$water40)
## Recode
water14a <- ifelse(water14 == "Don't know", NA,
ifelse(water14 == "Yes", 1, 0))
## water15: water quality improvement
## waterImprovement: water quality improvement
waterImprovement <- ifelse(surveyData$water42 == "Other improvement (please specify)",
surveyData$water43,
surveyData$water42)
waterImprovement <- ifelse(waterImprovement == "",
"Don't know/no answer/not applicable",
waterImprovement)
waterImprovement <- str_split(string = waterImprovement, pattern = ", ", simplify = TRUE)
## Create temporary container for vector outputs
temp <- NULL
## Cycle through columns of waterImprovement
for(i in 1:ncol(waterImprovement)) {
waterImprovement[ , i] <- ifelse(waterImprovement[ , i] == "Other improvement (please specify)",
surveyData$water43,
waterImprovement[ , i])
}
## Cycle through columns of waterImprovement
for(i in 1:ncol(waterImprovement)) {
## Concatenate waterImprovement columns into a single vector
temp <- c(temp, waterImprovement[ , i])
}
## Re-assign NA value to "" answers
temp <- ifelse(temp == "", NA, temp)
## Get responses
tempNames <- names(table(temp))
## Create vector accumulator
water15 <- NULL
## Cycle through responses
for(i in 1:length(tempNames))
{
## Create empty vector with length of surveyData
assign(paste("water15", letters[i], sep = ""),
vector(mode = "numeric", length = nrow(surveyData)))
## Cycle through data columns in waterCollect
for(j in 1:ncol(waterImprovement))
{
## Assign values
x <- ifelse(waterImprovement[ , j] == tempNames[i], i, 0)
## Concatenate responses
assign(paste("water15", letters[i], sep = ""),
get(paste("water15", letters[i], sep = "")) + x)
}
## Rename responses to character strings
assign(paste("water15", letters[i], sep = ""),
ifelse(get(paste("water15", letters[i], sep = "")) == i, tempNames[i], NA))
## Create water quality data.frame
water15 <- data.frame(cbind(water15, get(paste("water15", letters[i], sep = ""))))
}
## Rename the data.frame
names(water15) <- paste("water15", letters[1:length(tempNames)], sep = "")
## water16: water pressure
## Re-code
water16 <- ifelse(surveyData$water45 == "", "Don't know", surveyData$water45)
## Re-code
water16a <- ifelse(water16 == "Don't know", NA,
ifelse(water16 == "Yes", 1, 0))
## water17: support provider
## Re-code
water17 <- ifelse(surveyData$water47 == "", "Don't know/not applicable",
ifelse(surveyData$water47 == "Other (please specify)",
surveyData$water48, surveyData$water47))
## Re-code
water17 <- ifelse(water17 == "", "Don't know/not applicable", water17)
## Re-code: these lines of code [473-495] are Dhaka, Bangladesh 2017 specific.
water17 <- ifelse(water17 == "Landlord/House owner ", "Landlord/House owner",
ifelse(water17 == "Caretaker ", "Caretaker",
ifelse(water17 %in% c("Gaurd", "Gaurd "), "Guard",
ifelse(water17 %in% c("No complain arise",
"No complain arise",
"Till lemdon't face any problem"), "No complaints",
ifelse(water17 == "Water office ", "Water office",
ifelse(water17 == "Do no't cpmlain", "Do not complain",
ifelse(water17 == "Parlament Member (MP)", "Parliament Member (MP)",
ifelse(water17 == "Relavent office", "Relevant office",
ifelse(water17 == "Messengaer ", "Messenger",
ifelse(water17 == "Local Gverenment Engineering office", "Local Government Engineering office",
water17))))))))))
## Re-code: these lines of code [499-506] are Dhaka, Bangladesh 2017 specific
water17 <- ifelse(water17 %in% c("Facility operator",
"Local Government Engineering office",
"Power and Water Development office",
"Relevant office",
"Water office",
"Water supplier",
"Water utility",
"Women Affair Directory"), 1, 0)
################################################################################
#
# water18: water storage
#
################################################################################
## waterStorage
waterStorage <- ifelse(as.character(surveyData$wash60) == "",
"Don't know/not applicable",
as.character(surveyData$wash60))
waterStorage <- stringr::str_split(string = waterStorage, pattern = ", ", simplify = TRUE)
## water18a: Clean container (with lid)
water18a <- vector(mode = "numeric", length = nrow(surveyData))
water18a[waterStorage[,1] == "Clean container (with lid)" |
waterStorage[,2] == "Clean container (with lid)" |
waterStorage[,3] == "Clean container (with lid)"] <- 1
## water18b: Clean container (without lid)
water18b <- vector(mode = "numeric", length = nrow(surveyData))
water18b[waterStorage[,1] == "Clean container (without lid)" |
waterStorage[,2] == "Clean container (without lid)" |
waterStorage[,3] == "Clean container (without lid)"] <- 2
## water18c: Dirty container
water18c <- vector(mode = "numeric", length = nrow(surveyData))
water18c[waterStorage[,1] == "Dirty container" |
waterStorage[,2] == "Dirty container" |
waterStorage[,3] == "Dirty container"] <- 3
## water18d: Don't know/not applicable
water18d <- vector(mode = "numeric", length = nrow(surveyData))
water18d[waterStorage[,1] == "Don't know/not applicable" |
waterStorage[,2] == "Don't know/not applicable" |
waterStorage[,3] == "Don't know/not applicable"] <- 4
## water18
water18 <- ifelse(water18d == 4, NA,
ifelse(water18a == 1 & water18b != 2 & water18c != 3, 1, 0))
## waterQuality: this indicator was not collected in survey. For future
# surveys, if water quality tests are performed, this indicator
# will be calculated based on that data.
# Check whether waterQualityDF has been loaded
if(exists("waterQualityDF")) {
## Add logic here to process water quality data with waterQuality variable as
## the result to be used for calculating indicators
} else
## Assign NULL value to waterQuality variable if waterQualityDF is not available
waterQuality <- NULL
## JMP indicators for drinking water - post-2015
## Surface water: river, dam, lake, pond, stream, canal or irrigation channel
jmpWater1 <- ifelse(waterSource == "Surface water", 1, 0)
## Unimproved: unprotected dug wells, unprotected springs
jmpWater2 <- vector(mode = "numeric", length = nrow(surveyData))
jmpWater2[water1 != 1 & waterSource != "Surface water"] <- 1
## Limited: Improved but more than 30 minutes collection time
jmpWater3 <- vector(mode = "numeric", length = nrow(surveyData))
jmpWater3[water1 == 1 & water7a == 0] <- 1
## Determine if water quality data is available
if(is.null(waterQuality)) {
## At least basic: improved and no more than 30 minutes collection time
jmpWater4 <- vector(mode = "numeric", length = nrow(surveyData))
jmpWater4[water1 == 1 & water7a == 1] <- 1
## no safely managed: create jmpWater5 empty vector
jmpWater5 <- vector(mode = "numeric", length = nrow(surveyData))
jmpWater5[jmpWater5 == 0] <- NA
} else {
## Basic: Improved and no more than 30 minutes collection time
jmpWater4 <- vector(mode = "numeric", length = nrow(surveyData))
##
jmpWater4[water1 == 1 &
!waterSource %in% c("Piped water into dwelling",
"Piped water to yard/plot",
"Protected dug well or spring in yard") &
water7a == 1] <- 1
##
jmpWater4[water1 == 1 &
waterSource %in% c("Piped water into dwelling",
"Piped water to yard/plot",
"Protected dug well or spring in yard") &
(water4a == 0 | water5b == 0 | water6a == 0) &
water7a == 1] <- 1
## Self-managed: improved and no more than 30 minutes collection time and available
# when needed and free from priority contamination
jmpWater5 <- vector(mode = "numeric", length = nrow(surveyData))
##
jmpWater5[water1 == 1 &
waterSource %in% c("Piped water into dwelling",
"Piped water to yard/plot",
"Protected dug well or spring in yard") &
water4a == 1 &
water5b == 1 &
water6a == 1 &
waterQuality == 1] <- 1
}
## accessWater: Access to sufficient and sustained drinking water
## Re-code
accessWater <- ifelse(water10 %in% c("61-100 litres per day",
"101-150 litres per day",
"150-200 litres per day",
"201-300 literes per day",
">301 litres per day") &
water4b == 1 & water5b == 1 & water6a == 1, 1, 0)
## Create waterDF
## Concatenate water indicators
waterDF <- data.frame("uniqueID" = surveyData[ , "uniqueID"],
waterSource, water1, water2, water2a, water3, water3a,
water4, water4a, water4b, water5, water5a, water5b,
water6, water6a, water7, water7a, water7b, water7c, water8, water8a,
water9, water10, water10a, water10b,
water11, water11a, water11b, water11c, water11d,
water12, water12a, water12b,
water13, water13a,
water14, water14a,
water16, water16a,
water17, water18,
jmpWater1, jmpWater2, jmpWater3, jmpWater4, jmpWater5,
accessWater)
## Return results
return(waterDF)
}
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