R - Highcharter：在堆积柱形图上向下钻取
R - Highcharter: Drilldown on stacked column graph
我已经使用 R 在 Highcharter 中创建了一个堆积柱形图，我正在尝试能够向下钻取它。
即在附图中，我希望能够在 CRDT 列的红色部分向下钻取。到目前为止，我只能得到它，所以 CRDT 的每个颜色部分都钻入相同的信息，或者每个红色部分钻入相同的信息。我需要一个组合过滤器。
以下是我为所有红色部分钻取 "CRDT Red" 信息的代码：
Lvl1Grouping <- aggregate(WIPGate2$Receipt.Qty, by = list(WIPGate$Hold.Code,WIPGate2$Aging),FUN=sum)
Lvl1df <- data_frame(name = Lvl1Grouping$Group.1,
y = Lvl1Grouping$x,
stack = Lvl1Grouping$Group.2,
drilldown = tolower(stack)
)
hc <- highchart() %>%
hc_chart(type = "column") %>%
hc_title(text = "WIP") %>%
hc_xAxis(type = "category") %>%
hc_legend(enabled = FALSE) %>%
hc_plotOptions(column = list(stacking = "normal")) %>%
hc_add_series(name = "Greater than 30 days",data=Lvl1dfLvl1df$stack=="Greater than 30 days",], color = "#D20000") %>%
hc_add_series(name = "Between 20-30 days",data=Lvl1df[Lvl1df$stack=="Between 20-30 days",], color = "#FF7900") %>%
hc_add_series(name = "Between 10-20 days",data=Lvl1df[Lvl1df$stack=="Between 10-20 days",], color = "#F6FC00") %>%
hc_add_series(name = "Less than 10 days",data=Lvl1df[Lvl1df$stack=="Less than 10 days",], color = "#009A00")
hc
Lvl2GroupingCRDT <- WIPGate2[WIPGate2$Hold.Code == "CRDT",]
Lvl2GroupingCRDT4 <- Lvl2GroupingCRDT[Lvl2GroupingCRDT$Aging == "Greater than 30 days",]
Lvl2GroupingCRDT4 <- aggregate(Lvl2GroupingCRDT4$Receipt.Qty, by = list(Lvl2GroupingCRDT4$Customer.Name),FUN=sum)
dfCRDT4 <- data_frame(
name = Lvl2GroupingCRDT4$Group.1,
value = Lvl2GroupingCRDT4$x
)
hc <- hc %>%
hc_drilldown(
allowPointDrilldown = TRUE,
series = list(
list(
id = "greater than 30 days",
name = "CRDT",
data = list_parse2(dfCRDT4)
)
)
)
hc
Current Situation.png
我已经找到了代码，但是它不是 eloquent 解决方案...
诀窍是不是为 1 级信息使用单个数据帧，而是需要为堆栈的每个部分都有一个单独的数据帧。这样你就可以给它一个ID，以便能够引用。
我的代码是数百行，以便按照需要的方式拼接出数据，所以如果有人有更好的解决方案，请post它！ （我的实际代码除了 "CRDT" 还包括其他 7 个组，所以想象下面的 "CRDT" 行 * 7!!!
仅供参考，我更改了一些仪表板和变量，因此它们可能与上面的不一样...
WIPGate2Aging <- WIP_Ops_Filtered()[WIP_Ops_Filtered()$Hold.Code!="",]
WIPGate2G30 <- WIPGate2Aging[WIPGate2Aging$Aging == "Greater than 30 days",]
WIPGate22030 <- WIPGate2Aging[WIPGate2Aging$Aging == "Between 20-30 days",]
WIPGate21020 <- WIPGate2Aging[WIPGate2Aging$Aging == "Between 10-20 days",]
WIPGate2L10 <- WIPGate2Aging[WIPGate2Aging$Aging == "Less than 10 days",]
try(Lvl1GroupingG30 <- aggregate(WIPGate2G30$Receipt.Qty, by = list(WIPGate2G30$Hold.Code),FUN=sum),silent = TRUE)
if (exists("Lvl1GroupingG30")) {} else {Lvl1GroupingG30=data.table(Group.1=numeric(), x=numeric())}
try(Lvl1Grouping2030 <- aggregate(WIPGate22030$Receipt.Qty, by = list(WIPGate22030$Hold.Code),FUN=sum),silent = TRUE)
if (exists("Lvl1Grouping2030")) {} else {Lvl1Grouping2030=data.table(Group.1=numeric(), x=numeric())}
try(Lvl1Grouping1020 <- aggregate(WIPGate21020$Receipt.Qty, by = list(WIPGate21020$Hold.Code),FUN=sum),silent = TRUE)
if (exists("Lvl1Grouping1020")) {} else {Lvl1Grouping1020=data.table(Group.1=numeric(), x=numeric())}
try(Lvl1GroupingL10 <- aggregate(WIPGate2L10$Receipt.Qty, by = list(WIPGate2L10$Hold.Code),FUN=sum),silent = TRUE)
if (exists("Lvl1GroupingL10")) {} else {Lvl1GroupingL10=data.table(Group.1=numeric(), x=numeric())}
Lvl1dfG30 <- data_frame(name = Lvl1GroupingG30$Group.1, y = Lvl1GroupingG30$x, drilldown = tolower((paste(name,"4"))))
Lvl1df2030 <- data_frame(name = Lvl1Grouping2030$Group.1, y = Lvl1Grouping2030$x, drilldown = tolower((paste(name,"3"))))
Lvl1df1020 <- data_frame(name = Lvl1Grouping1020$Group.1, y = Lvl1Grouping1020$x, drilldown = tolower((paste(name,"2"))))
Lvl1dfL10 <- data_frame(name = Lvl1GroupingL10$Group.1, y = Lvl1GroupingL10$x, drilldown = tolower((paste(name,"1"))))
Lvl2GroupingCRDTG30 <- WIPGate2Aging[WIPGate2Aging$Hold.Code == "CRDT" & WIPGate2Aging$Aging == "Greater than 30 days",]
try(Lvl2GroupingCRDTG30b <- aggregate(Lvl2GroupingCRDTG30$Receipt.Qty, by = list(Lvl2GroupingCRDTG30$Customer.Name),FUN=sum),silent = TRUE)
if (exists("Lvl2GroupingCRDTG30b")) {} else {Lvl2GroupingCRDTG30b=data.table(Group.1=numeric(), x=numeric())}
Lvl2GroupingCRDT2030 <- WIPGate2Aging[WIPGate2Aging$Hold.Code == "CRDT" & WIPGate2Aging$Aging == "Between 20-30 days",]
try(Lvl2GroupingCRDT2030b <- aggregate(Lvl2GroupingCRDT2030$Receipt.Qty, by = list(Lvl2GroupingCRDT2030$Customer.Name),FUN=sum),silent = TRUE)
if (exists("Lvl2GroupingCRDT2030b")) {} else {Lvl2GroupingCRDT2030b=data.table(Group.1=numeric(), x=numeric())}
Lvl2GroupingCRDT1020 <- WIPGate2Aging[WIPGate2Aging$Hold.Code == "CRDT" & WIPGate2Aging$Aging == "Between 10-20 days",]
try(Lvl2GroupingCRDT1020b <- aggregate(Lvl2GroupingCRDT1020$Receipt.Qty, by = list(Lvl2GroupingCRDT1020$Customer.Name),FUN=sum),silent = TRUE)
if (exists("Lvl2GroupingCRDT1020b")) {} else {Lvl2GroupingCRDT1020b=data.table(Group.1=numeric(), x=numeric())}
Lvl2GroupingCRDTL10 <- WIPGate2Aging[WIPGate2Aging$Hold.Code == "CRDT" & WIPGate2Aging$Aging == "Less than 10 days",]
try(Lvl2GroupingCRDTL10b <- aggregate(Lvl2GroupingCRDTL10$Receipt.Qty, by = list(Lvl2GroupingCRDTL10$Customer.Name),FUN=sum),silent = TRUE)
if (exists("Lvl2GroupingCRDTL10b")) {} else {Lvl2GroupingCRDTL10b=data.table(Group.1=numeric(), x=numeric())}
dfCRDTG30 <- arrange(data_frame(name = Lvl2GroupingCRDTG30b$Group.1,value = Lvl2GroupingCRDTG30b$x),desc(value))
dfCRDT2030 <- arrange(data_frame(name = Lvl2GroupingCRDT2030b$Group.1,value = Lvl2GroupingCRDT2030b$x),desc(value))
dfCRDT1020 <- arrange(data_frame(name = Lvl2GroupingCRDT1020b$Group.1,value = Lvl2GroupingCRDT1020b$x),desc(value))
dfCRDTL10 <- arrange(data_frame(name = Lvl2GroupingCRDTL10b$Group.1,value = Lvl2GroupingCRDTL10b$x),desc(value))
highchart() %>%
hc_chart(type = "column") %>%
hc_xAxis(type = "category") %>%
hc_yAxis(gridLineWidth = 0) %>%
hc_legend(enabled = TRUE) %>%
hc_plotOptions(column = list(stacking = "normal")) %>%
hc_add_series(name = "Greater than 30 days",data=Lvl1dfG30, color = "#D20000") %>%
hc_add_series(name = "Between 20-30 days",data=Lvl1df2030, color = "#FF7900") %>%
hc_add_series(name = "Between 10-20 days",data=Lvl1df1020, color = "#F6FC00") %>%
hc_add_series(name = "Less than 10 days",data=Lvl1dfL10, color = "#009A00") %>%
hc_drilldown(
allowPointDrilldown = TRUE,
series = list(
list(id = "crdt 4", data = list_parse2(dfCRDTG30), name="Customer"),
list(id = "crdt 3", data = list_parse2(dfCRDT2030), name="Customer"),
list(id = "crdt 2", data = list_parse2(dfCRDT1020), name="Customer"),
list(id = "crdt 1", data = list_parse2(dfCRDTL10), name="Customer")))
我已经使用 R 在 Highcharter 中创建了一个堆积柱形图，我正在尝试能够向下钻取它。
即在附图中，我希望能够在 CRDT 列的红色部分向下钻取。到目前为止，我只能得到它，所以 CRDT 的每个颜色部分都钻入相同的信息，或者每个红色部分钻入相同的信息。我需要一个组合过滤器。
以下是我为所有红色部分钻取 "CRDT Red" 信息的代码：
Lvl1Grouping <- aggregate(WIPGate2$Receipt.Qty, by = list(WIPGate$Hold.Code,WIPGate2$Aging),FUN=sum)
Lvl1df <- data_frame(name = Lvl1Grouping$Group.1,
y = Lvl1Grouping$x,
stack = Lvl1Grouping$Group.2,
drilldown = tolower(stack)
)
hc <- highchart() %>%
hc_chart(type = "column") %>%
hc_title(text = "WIP") %>%
hc_xAxis(type = "category") %>%
hc_legend(enabled = FALSE) %>%
hc_plotOptions(column = list(stacking = "normal")) %>%
hc_add_series(name = "Greater than 30 days",data=Lvl1dfLvl1df$stack=="Greater than 30 days",], color = "#D20000") %>%
hc_add_series(name = "Between 20-30 days",data=Lvl1df[Lvl1df$stack=="Between 20-30 days",], color = "#FF7900") %>%
hc_add_series(name = "Between 10-20 days",data=Lvl1df[Lvl1df$stack=="Between 10-20 days",], color = "#F6FC00") %>%
hc_add_series(name = "Less than 10 days",data=Lvl1df[Lvl1df$stack=="Less than 10 days",], color = "#009A00")
hc
Lvl2GroupingCRDT <- WIPGate2[WIPGate2$Hold.Code == "CRDT",]
Lvl2GroupingCRDT4 <- Lvl2GroupingCRDT[Lvl2GroupingCRDT$Aging == "Greater than 30 days",]
Lvl2GroupingCRDT4 <- aggregate(Lvl2GroupingCRDT4$Receipt.Qty, by = list(Lvl2GroupingCRDT4$Customer.Name),FUN=sum)
dfCRDT4 <- data_frame(
name = Lvl2GroupingCRDT4$Group.1,
value = Lvl2GroupingCRDT4$x
)
hc <- hc %>%
hc_drilldown(
allowPointDrilldown = TRUE,
series = list(
list(
id = "greater than 30 days",
name = "CRDT",
data = list_parse2(dfCRDT4)
)
)
)
hc
Current Situation.png
我已经找到了代码，但是它不是 eloquent 解决方案...
诀窍是不是为 1 级信息使用单个数据帧，而是需要为堆栈的每个部分都有一个单独的数据帧。这样你就可以给它一个ID，以便能够引用。
我的代码是数百行，以便按照需要的方式拼接出数据，所以如果有人有更好的解决方案，请post它！ （我的实际代码除了 "CRDT" 还包括其他 7 个组，所以想象下面的 "CRDT" 行 * 7!!!
仅供参考，我更改了一些仪表板和变量，因此它们可能与上面的不一样...
WIPGate2Aging <- WIP_Ops_Filtered()[WIP_Ops_Filtered()$Hold.Code!="",]
WIPGate2G30 <- WIPGate2Aging[WIPGate2Aging$Aging == "Greater than 30 days",]
WIPGate22030 <- WIPGate2Aging[WIPGate2Aging$Aging == "Between 20-30 days",]
WIPGate21020 <- WIPGate2Aging[WIPGate2Aging$Aging == "Between 10-20 days",]
WIPGate2L10 <- WIPGate2Aging[WIPGate2Aging$Aging == "Less than 10 days",]
try(Lvl1GroupingG30 <- aggregate(WIPGate2G30$Receipt.Qty, by = list(WIPGate2G30$Hold.Code),FUN=sum),silent = TRUE)
if (exists("Lvl1GroupingG30")) {} else {Lvl1GroupingG30=data.table(Group.1=numeric(), x=numeric())}
try(Lvl1Grouping2030 <- aggregate(WIPGate22030$Receipt.Qty, by = list(WIPGate22030$Hold.Code),FUN=sum),silent = TRUE)
if (exists("Lvl1Grouping2030")) {} else {Lvl1Grouping2030=data.table(Group.1=numeric(), x=numeric())}
try(Lvl1Grouping1020 <- aggregate(WIPGate21020$Receipt.Qty, by = list(WIPGate21020$Hold.Code),FUN=sum),silent = TRUE)
if (exists("Lvl1Grouping1020")) {} else {Lvl1Grouping1020=data.table(Group.1=numeric(), x=numeric())}
try(Lvl1GroupingL10 <- aggregate(WIPGate2L10$Receipt.Qty, by = list(WIPGate2L10$Hold.Code),FUN=sum),silent = TRUE)
if (exists("Lvl1GroupingL10")) {} else {Lvl1GroupingL10=data.table(Group.1=numeric(), x=numeric())}
Lvl1dfG30 <- data_frame(name = Lvl1GroupingG30$Group.1, y = Lvl1GroupingG30$x, drilldown = tolower((paste(name,"4"))))
Lvl1df2030 <- data_frame(name = Lvl1Grouping2030$Group.1, y = Lvl1Grouping2030$x, drilldown = tolower((paste(name,"3"))))
Lvl1df1020 <- data_frame(name = Lvl1Grouping1020$Group.1, y = Lvl1Grouping1020$x, drilldown = tolower((paste(name,"2"))))
Lvl1dfL10 <- data_frame(name = Lvl1GroupingL10$Group.1, y = Lvl1GroupingL10$x, drilldown = tolower((paste(name,"1"))))
Lvl2GroupingCRDTG30 <- WIPGate2Aging[WIPGate2Aging$Hold.Code == "CRDT" & WIPGate2Aging$Aging == "Greater than 30 days",]
try(Lvl2GroupingCRDTG30b <- aggregate(Lvl2GroupingCRDTG30$Receipt.Qty, by = list(Lvl2GroupingCRDTG30$Customer.Name),FUN=sum),silent = TRUE)
if (exists("Lvl2GroupingCRDTG30b")) {} else {Lvl2GroupingCRDTG30b=data.table(Group.1=numeric(), x=numeric())}
Lvl2GroupingCRDT2030 <- WIPGate2Aging[WIPGate2Aging$Hold.Code == "CRDT" & WIPGate2Aging$Aging == "Between 20-30 days",]
try(Lvl2GroupingCRDT2030b <- aggregate(Lvl2GroupingCRDT2030$Receipt.Qty, by = list(Lvl2GroupingCRDT2030$Customer.Name),FUN=sum),silent = TRUE)
if (exists("Lvl2GroupingCRDT2030b")) {} else {Lvl2GroupingCRDT2030b=data.table(Group.1=numeric(), x=numeric())}
Lvl2GroupingCRDT1020 <- WIPGate2Aging[WIPGate2Aging$Hold.Code == "CRDT" & WIPGate2Aging$Aging == "Between 10-20 days",]
try(Lvl2GroupingCRDT1020b <- aggregate(Lvl2GroupingCRDT1020$Receipt.Qty, by = list(Lvl2GroupingCRDT1020$Customer.Name),FUN=sum),silent = TRUE)
if (exists("Lvl2GroupingCRDT1020b")) {} else {Lvl2GroupingCRDT1020b=data.table(Group.1=numeric(), x=numeric())}
Lvl2GroupingCRDTL10 <- WIPGate2Aging[WIPGate2Aging$Hold.Code == "CRDT" & WIPGate2Aging$Aging == "Less than 10 days",]
try(Lvl2GroupingCRDTL10b <- aggregate(Lvl2GroupingCRDTL10$Receipt.Qty, by = list(Lvl2GroupingCRDTL10$Customer.Name),FUN=sum),silent = TRUE)
if (exists("Lvl2GroupingCRDTL10b")) {} else {Lvl2GroupingCRDTL10b=data.table(Group.1=numeric(), x=numeric())}
dfCRDTG30 <- arrange(data_frame(name = Lvl2GroupingCRDTG30b$Group.1,value = Lvl2GroupingCRDTG30b$x),desc(value))
dfCRDT2030 <- arrange(data_frame(name = Lvl2GroupingCRDT2030b$Group.1,value = Lvl2GroupingCRDT2030b$x),desc(value))
dfCRDT1020 <- arrange(data_frame(name = Lvl2GroupingCRDT1020b$Group.1,value = Lvl2GroupingCRDT1020b$x),desc(value))
dfCRDTL10 <- arrange(data_frame(name = Lvl2GroupingCRDTL10b$Group.1,value = Lvl2GroupingCRDTL10b$x),desc(value))
highchart() %>%
hc_chart(type = "column") %>%
hc_xAxis(type = "category") %>%
hc_yAxis(gridLineWidth = 0) %>%
hc_legend(enabled = TRUE) %>%
hc_plotOptions(column = list(stacking = "normal")) %>%
hc_add_series(name = "Greater than 30 days",data=Lvl1dfG30, color = "#D20000") %>%
hc_add_series(name = "Between 20-30 days",data=Lvl1df2030, color = "#FF7900") %>%
hc_add_series(name = "Between 10-20 days",data=Lvl1df1020, color = "#F6FC00") %>%
hc_add_series(name = "Less than 10 days",data=Lvl1dfL10, color = "#009A00") %>%
hc_drilldown(
allowPointDrilldown = TRUE,
series = list(
list(id = "crdt 4", data = list_parse2(dfCRDTG30), name="Customer"),
list(id = "crdt 3", data = list_parse2(dfCRDT2030), name="Customer"),
list(id = "crdt 2", data = list_parse2(dfCRDT1020), name="Customer"),
list(id = "crdt 1", data = list_parse2(dfCRDTL10), name="Customer")))