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Added logic to deal with if SanKey chart has no data. #65

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merged 1 commit into from
May 10, 2022
Merged

Added logic to deal with if SanKey chart has no data. #65

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221 changes: 112 additions & 109 deletions R/industry_flow.R
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Original file line number Diff line number Diff line change
Expand Up @@ -12,156 +12,159 @@ sankey_chart <- function(subjectinput, sexinput, qualinput) {

cohort_sankey1 <- na.omit(cohort_sankey1)
cohort_sankey2 <- na.omit(cohort_sankey2)
if (all(cohort_sankey1$count == 0) | all(is.na(cohort_sankey1$count))) {
return(NULL)
} else {

# Choose top 9 SIC section names and label all others as 'OTHER' based on counts for 1 YAG
# Choose top 9 SIC section names and label all others as 'OTHER' based on counts for 1 YAG

section_names1 <- cohort_sankey1 %>%
group_by(SECTIONNAME.x) %>%
dplyr::summarise(count = sum(count)) %>%
arrange(., -count)
section_names1 <- cohort_sankey1 %>%
group_by(SECTIONNAME.x) %>%
dplyr::summarise(count = sum(count)) %>%
arrange(., -count)

section_names2 <- cohort_sankey1 %>%
group_by(SECTIONNAME.y) %>%
dplyr::summarise(count = sum(count)) %>%
arrange(., -count)
section_names2 <- cohort_sankey1 %>%
group_by(SECTIONNAME.y) %>%
dplyr::summarise(count = sum(count)) %>%
arrange(., -count)

section_names <- section_names1 %>%
full_join(section_names2, by = c("SECTIONNAME.x" = "SECTIONNAME.y"))
section_names$count.x[is.na(section_names$count.x) == TRUE] <- 0
section_names$count.y[is.na(section_names$count.y) == TRUE] <- 0
section_names$count <- section_names$count.x + section_names$count.y
section_names <- section_names1 %>%
full_join(section_names2, by = c("SECTIONNAME.x" = "SECTIONNAME.y"))
section_names$count.x[is.na(section_names$count.x) == TRUE] <- 0
section_names$count.y[is.na(section_names$count.y) == TRUE] <- 0
section_names$count <- section_names$count.x + section_names$count.y

section_names <- section_names[, -c(2, 3)] %>%
arrange(., -count)
section_names <- section_names[, -c(2, 3)] %>%
arrange(., -count)

section_names$ID <- 1:nrow(section_names)
section_names$SECTIONNAME_NEW <- section_names$SECTIONNAME.x
section_names$SECTIONNAME_NEW[section_names$ID > 9] <- "Other"
section_names$ID <- 1:nrow(section_names)
section_names$SECTIONNAME_NEW <- section_names$SECTIONNAME.x
section_names$SECTIONNAME_NEW[section_names$ID > 9] <- "Other"

names(section_names) <- c("old", "count", "ID", "new")
names(section_names) <- c("old", "count", "ID", "new")

# re-calculate counts using new section names variable
# re-calculate counts using new section names variable

cohort_sankey1 <- cohort_sankey1 %>%
left_join(section_names, by = c("SECTIONNAME.x" = "old"))
cohort_sankey1$SECTIONNAME.x <- cohort_sankey1$new
cohort_sankey1 <- cohort_sankey1[, -c(10, 11, 12)]
cohort_sankey1 <- cohort_sankey1 %>%
left_join(section_names, by = c("SECTIONNAME.x" = "old"))
cohort_sankey1$SECTIONNAME.x <- cohort_sankey1$new
cohort_sankey1 <- cohort_sankey1[, -c(10, 11, 12)]

cohort_sankey1 <- cohort_sankey1 %>%
left_join(section_names, by = c("SECTIONNAME.y" = "old"))
cohort_sankey1$SECTIONNAME.y <- cohort_sankey1$new
cohort_sankey1 <- cohort_sankey1[, -c(10, 11, 12)]
cohort_sankey1 <- cohort_sankey1 %>%
left_join(section_names, by = c("SECTIONNAME.y" = "old"))
cohort_sankey1$SECTIONNAME.y <- cohort_sankey1$new
cohort_sankey1 <- cohort_sankey1[, -c(10, 11, 12)]

# The following line had disappeared from my branch compared to main branch.
# I didn't mean to delete it and assuming no-one else has been on the branch,
# so assuming it was an accidental deletion.
cohort_sankey1$SECTIONNAME.y[is.na(cohort_sankey1$SECTIONNAME.y) == TRUE] <- "Other"
# The following line had disappeared from my branch compared to main branch.
# I didn't mean to delete it and assuming no-one else has been on the branch,
# so assuming it was an accidental deletion.
cohort_sankey1$SECTIONNAME.y[is.na(cohort_sankey1$SECTIONNAME.y) == TRUE] <- "Other"

cohort_sankey1 <- cohort_sankey1 %>%
group_by(sex.x, subject_name.x, YAG.x, SECTIONNAME.x, YAG.y, SECTIONNAME.y) %>%
dplyr::summarise(count = sum(count.x)) %>%
arrange(., -count)
cohort_sankey1 <- cohort_sankey1 %>%
group_by(sex.x, subject_name.x, YAG.x, SECTIONNAME.x, YAG.y, SECTIONNAME.y) %>%
dplyr::summarise(count = sum(count.x)) %>%
arrange(., -count)

# re-calculate counts using new section names variable
# re-calculate counts using new section names variable

cohort_sankey2 <- cohort_sankey2 %>%
left_join(section_names, by = c("SECTIONNAME.x" = "old"))
cohort_sankey2$SECTIONNAME.x <- cohort_sankey2$new
cohort_sankey2 <- cohort_sankey2[, -c(10, 11, 12)]
cohort_sankey2 <- cohort_sankey2 %>%
left_join(section_names, by = c("SECTIONNAME.x" = "old"))
cohort_sankey2$SECTIONNAME.x <- cohort_sankey2$new
cohort_sankey2 <- cohort_sankey2[, -c(10, 11, 12)]

cohort_sankey2 <- cohort_sankey2 %>%
left_join(section_names, by = c("SECTIONNAME.y" = "old"))
cohort_sankey2$SECTIONNAME.y <- cohort_sankey2$new
cohort_sankey2 <- cohort_sankey2[, -c(10, 11, 12)]
cohort_sankey2 <- cohort_sankey2 %>%
left_join(section_names, by = c("SECTIONNAME.y" = "old"))
cohort_sankey2$SECTIONNAME.y <- cohort_sankey2$new
cohort_sankey2 <- cohort_sankey2[, -c(10, 11, 12)]

cohort_sankey2$SECTIONNAME.y[is.na(cohort_sankey2$SECTIONNAME.y) == TRUE] <- "Other"
cohort_sankey2$SECTIONNAME.x[is.na(cohort_sankey2$SECTIONNAME.x) == TRUE] <- "Other"
cohort_sankey2$SECTIONNAME.y[is.na(cohort_sankey2$SECTIONNAME.y) == TRUE] <- "Other"
cohort_sankey2$SECTIONNAME.x[is.na(cohort_sankey2$SECTIONNAME.x) == TRUE] <- "Other"

cohort_sankey2 <- cohort_sankey2 %>%
group_by(sex.x, subject_name.x, YAG.x, SECTIONNAME.x, YAG.y, SECTIONNAME.y) %>%
dplyr::summarise(count = sum(count.x)) %>%
arrange(., -count)
cohort_sankey2 <- cohort_sankey2 %>%
group_by(sex.x, subject_name.x, YAG.x, SECTIONNAME.x, YAG.y, SECTIONNAME.y) %>%
dplyr::summarise(count = sum(count.x)) %>%
arrange(., -count)

# Now name nodes
# Now name nodes

nodes <- data.frame("name" = c(
unique(cohort_sankey1$SECTIONNAME.x),
unique(c(cohort_sankey1$SECTIONNAME.y, cohort_sankey2$SECTIONNAME.x)),
unique(cohort_sankey2$SECTIONNAME.y)
))
nodes <- data.frame("name" = c(
unique(cohort_sankey1$SECTIONNAME.x),
unique(c(cohort_sankey1$SECTIONNAME.y, cohort_sankey2$SECTIONNAME.x)),
unique(cohort_sankey2$SECTIONNAME.y)
))

nodes$ID <- 0:(nrow(nodes) - 1)
nodes$ID <- 0:(nrow(nodes) - 1)

# View nodes and separate into 3 sections to join the ID numbers into links.
# View nodes and separate into 3 sections to join the ID numbers into links.

nodes1 <- nodes[1:length(unique(cohort_sankey1$SECTIONNAME.x)), ]
nodes2 <- nodes[(length(unique(cohort_sankey1$SECTIONNAME.x)) + 1):((length(unique(cohort_sankey1$SECTIONNAME.x))) + length(unique(c(cohort_sankey1$SECTIONNAME.y, cohort_sankey2$SECTIONNAME.x)))), ]
nodes3 <- nodes[((length(unique(cohort_sankey1$SECTIONNAME.x))) + length(unique(c(cohort_sankey1$SECTIONNAME.y, cohort_sankey2$SECTIONNAME.x))) + 1):nrow(nodes), ]
nodes1 <- nodes[1:length(unique(cohort_sankey1$SECTIONNAME.x)), ]
nodes2 <- nodes[(length(unique(cohort_sankey1$SECTIONNAME.x)) + 1):((length(unique(cohort_sankey1$SECTIONNAME.x))) + length(unique(c(cohort_sankey1$SECTIONNAME.y, cohort_sankey2$SECTIONNAME.x)))), ]
nodes3 <- nodes[((length(unique(cohort_sankey1$SECTIONNAME.x))) + length(unique(c(cohort_sankey1$SECTIONNAME.y, cohort_sankey2$SECTIONNAME.x))) + 1):nrow(nodes), ]

# Create links for 1-3 YAG ------------------------------------------------

links1 <- as.data.frame(
cohort_sankey1[, c(4, 6, 7)],
byrow = TRUE, ncol = 3
)
# Create links for 1-3 YAG ------------------------------------------------

names(links1) <- c("source", "target", "value")
links1 <- as.data.frame(
cohort_sankey1[, c(4, 6, 7)],
byrow = TRUE, ncol = 3
)

# Change names in links to numbers
names(links1) <- c("source", "target", "value")

links1 <- links1 %>%
left_join(nodes1, by = c("source" = "name"))
links1$source <- links1$ID
links1 <- links1[, -4]
# Change names in links to numbers

links1 <- links1 %>%
left_join(nodes2, by = c("target" = "name"))
links1$target <- links1$ID
links1 <- links1[, -4]
links1 <- links1 %>%
left_join(nodes1, by = c("source" = "name"))
links1$source <- links1$ID
links1 <- links1[, -4]

links1 <- links1 %>%
left_join(nodes2, by = c("target" = "name"))
links1$target <- links1$ID
links1 <- links1[, -4]

# Create links for 3-5 YAG ------------------------------------------------

links2 <- as.data.frame(
cohort_sankey2[, c(4, 6, 7)],
byrow = TRUE, ncol = 3
)
# Create links for 3-5 YAG ------------------------------------------------

names(links2) <- c("source", "target", "value")
links2 <- as.data.frame(
cohort_sankey2[, c(4, 6, 7)],
byrow = TRUE, ncol = 3
)

# Change names in links to numbers
names(links2) <- c("source", "target", "value")

links2 <- links2 %>%
left_join(nodes2, by = c("source" = "name"))
links2$source <- links2$ID
links2 <- links2[, -4]
# Change names in links to numbers

links2 <- links2 %>%
left_join(nodes3, by = c("target" = "name"))
links2$target <- links2$ID
links2 <- links2[, -4]
links2 <- links2 %>%
left_join(nodes2, by = c("source" = "name"))
links2$source <- links2$ID
links2 <- links2[, -4]

links2 <- links2 %>%
left_join(nodes3, by = c("target" = "name"))
links2$target <- links2$ID
links2 <- links2[, -4]

# join the 2 links together

links <- links1 %>%
full_join(links2)
# join the 2 links together

links <- links %>%
mutate_at(
"value",
funs(ifelse(!is.na(as.numeric(.)), round_any(as.numeric(.), 5), .))
)
links <- links1 %>%
full_join(links2)

# Force a space between node names and values
nodes$name <- paste(nodes$name, " ")
links <- links %>%
mutate_at(
"value",
funs(ifelse(!is.na(as.numeric(.)), round_any(as.numeric(.), 5), .))
)

plot <- sankeyNetwork(
Links = links, Nodes = nodes,
Source = "source", Target = "target",
Value = "value", NodeID = "name", fontSize = 10, nodePadding = 20
)
# Force a space between node names and values
nodes$name <- paste(nodes$name, " ")

plot <- sankeyNetwork(
Links = links, Nodes = nodes,
Source = "source", Target = "target",
Value = "value", NodeID = "name", fontSize = 10, nodePadding = 20
)
}
return(plot)
}

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10 changes: 10 additions & 0 deletions server.R
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Original file line number Diff line number Diff line change
Expand Up @@ -49,10 +49,20 @@ server <- function(input, output, session) {
input$qualinput
)
)

output$sankey <- renderSankeyNetwork({
reactiveSankey()
})

output$sankey_flag <- renderUI({
if (!type_sum(reactiveSankey()) == "snkyNtwr") {
tagList(br(), h3("No data found for the selected filters."))
} else {
NULL
}
})


output$sankey_title <- renderText({
sankey_title(input$indflow.subjectinput, input$sexinput, input$qualinput)
})
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13 changes: 11 additions & 2 deletions ui.R
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Original file line number Diff line number Diff line change
Expand Up @@ -218,8 +218,17 @@ fluidPage(
4,
div("5 years after graduation", style = "text-align: right")
),
withSpinner(
sankeyNetworkOutput(outputId = "sankey", height = 800)
conditionalPanel(
condition = "!is.null(output$sankey_flag)",
withSpinner(
uiOutput("sankey_flag")
)
),
conditionalPanel(
condition = "is.null(output$sankey_flag)",
withSpinner(
sankeyNetworkOutput(outputId = "sankey", height = 800)
)
)
),

Expand Down