R-Highcharter：在堆叠柱形图上向下展开
我已经使用Highcharter创建了一个堆叠柱形图，我正在尝试深入研究它 也就是说，在所附图片中，我希望能够向下钻取列CRDT的红色部分。到目前为止，我只能让CRDT的每个颜色部分钻入相同的信息，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 下面是我为所有红色部分钻取“CRDT Red”信息的代码：R-Highcharter：在堆叠柱形图上向下展开,r,highcharts,stackedbarseries,r-highcharter,R,Highcharts,Stackedbarseries,R Highcharter,我已经使用Highcharter创建了一个堆叠柱形图，我正在尝试深入研究它 也就是说，在所附图片中，我希望能够向下钻取列CRDT的红色部分。到目前为止，我只能让CRDT的每个颜色部分钻入相同的信息，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 下面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$Aging)
Lvl1Grouping <- aggregate(WIPGate2$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$x
)
hc <- hc %>%
hc_drilldown(
allowPointDrilldown = TRUE,
series = list(
list(
id = "greater than 30 days",
name = "CRDT",
data = list_parse2(dfCRDT4)
)
)
)
hc
lvl1%
hc_xAxis（type=“category”）%%>%
hc_图例（启用=错误）%>%
hc\U绘图选项（列=列表（堆叠=“正常”））%>%
hc#U添加#U系列（name=“大于30天”，data=Lvl1dfLvl1df$stack==“大于30天”，color=“#D20000”）%%>%
hc#U添加#U系列（name=“20-30天之间”，data=Lvl1df[Lvl1df$stack==“20-30天之间”，]，color=“#FF7900”）%>%
hc#U添加#U系列（name=“10-20天之间”，data=Lvl1df[Lvl1df$stack==“10-20天之间”，]，color=“#F6FC00”）%>%
hc#U添加#U系列（name=“少于10天”，data=Lvl1df[Lvl1df$stack==“少于10天”，color=“#009A00”）
hc
Lvl2GroupingCRDT我已经找到了代码，但是它不是一个雄辩的解决方案
诀窍是不要为级别1信息使用单个数据帧，而是需要为堆栈的每个部分使用单独的数据帧。通过这种方式，您可以为其添加ID，以便能够引用
我的代码有数百行，以便按照需要的方式拼接数据，因此如果有人有更好的解决方案，请发布！！（实际上我的代码除了“CRDT”之外还包括7个其他组，所以想象一下*7下面的“CRDT”行
仅供参考，我已经更改了一些仪表板和变量，因此它们可能与上面的不同
WIPGate2Aging <- WIP_Ops_Filtered()[WIP_Ops_Filtered()$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")))
WIPGate2Aging我已经找到了代码，但是这不是一个有说服力的解决方案
诀窍是不要为级别1信息使用单个数据帧，堆栈的每个部分都需要一个单独的数据帧。通过这种方式，您可以为它添加一个ID，以便能够引用
我的代码有数百行，以便按照需要的方式拼接数据，因此如果有人有更好的解决方案，请发布！！（我的代码实际上包括除“CRDT”之外的7个组，所以想象一下*7下面的“CRDT”行
仅供参考，我已经更改了一些仪表板和变量，因此它们可能与上面的不同
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")))
WIPGate2Aging