Amanda

Column

通过率

坏账率

Column

数据

分类 时间 总量 通过量 坏账量
销售 2016-08-16 10 4 1
销售 2016-09-16 32 20 6
销售 2016-10-16 47 27 0
销售 2016-11-16 27 11 0
销售 2016-12-01 1 0 0
门店 2016-08-01 226 144 16
门店 2016-09-01 316 187 16
门店 2016-10-01 403 226 0
门店 2016-11-01 328 156 0
门店 2016-12-01 6 2 0

销售区域1

Angela

Column

通过率

坏账率

Column

数据

分类 时间 总量 通过量 坏账量
销售 2016-07-01 7 4 2
销售 2016-08-01 58 28 9
销售 2016-09-01 26 16 8
销售 2016-10-01 31 18 0
销售 2016-11-01 4 0 0
门店 2016-07-01 457 288 38
门店 2016-08-01 656 413 61
门店 2016-09-01 535 332 43
门店 2016-10-01 589 355 1
门店 2016-11-01 395 188 0

销售区域2

Justin

Column

通过率

坏账率

Column

数据

分类 时间 总量 通过量 坏账量
销售 2016-08-01 18 9 4
销售 2016-09-01 25 16 3
销售 2016-10-01 23 12 0
销售 2016-11-01 11 4 0
门店 2016-08-01 656 413 61
门店 2016-09-01 535 332 43
门店 2016-10-01 589 355 1
门店 2016-11-01 395 188 0

销售区域3

Taylor

Column

通过率

坏账率

Column

数据

分类 时间 总量 通过量 坏账量
销售 2016-08-01 16 8 4
销售 2016-09-01 43 28 6
销售 2016-10-01 74 41 0
销售 2016-11-01 46 17 0
门店 2016-08-01 656 413 61
门店 2016-09-01 535 332 43
门店 2016-10-01 589 355 1
门店 2016-11-01 395 188 0

销售区域4

Megan

Column

通过率

坏账率

Column

数据

分类 时间 总量 通过量 坏账量
销售 2016-08-01 24 13 5
销售 2016-09-01 30 17 4
销售 2016-10-01 34 20 0
销售 2016-11-01 18 5 0
门店 2016-08-01 151 95 15
门店 2016-09-01 129 83 11
门店 2016-10-01 144 92 0
门店 2016-11-01 132 69 0

销售区域5

---
title: "销售分析"
author: "Lisa"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    social: menu
    source_code: embed
---

```{r setup, include=FALSE}
library(readxl)
library(highcharter)
library(dplyr);library(tidyr)
library(viridisLite)
library(forecast)
library(treemap)
library(flexdashboard)
library(rbokeh)
library(RgoogleMaps)
require(maps)
require(ggmap)
library(dplyr)
library(htmltools)
library(htmlwidgets)
library(metricsgraphics)
library(RColorBrewer)
library(leaflet)
library(googleVis)
library(shiny)
library(DT)
options(digits=2) # only show 2 digit numbers
```



```{r global, include=FALSE}
# load data in 'global' chunk so it can be shared by all users of the dashboard
ind=read_excel("销售.xlsx")
ind$时间=as.character(ind$时间)

place=read_excel("人员.xlsx")
#add lat and lon by "getGeoCode"
DF= cbind.data.frame(name=place$省份, lat = NA,lon = NA)
place_com =data.frame(place, t(sapply(DF$name, getGeoCode)))  

#set up color
col=c("#7ca82b","#f7518e","#cbed97","#f9528d","#ff0202","#a01c01")

```


Amanda
=======================================================================


Column {data-width=500}
-----------------------------------------------------------------------

### 通过率

```{r}
#select 销售=乔健
sale=ind %>% filter(ind$姓名=="乔健")
pass_rate=sale %>% mutate(坏账率 = sale$坏账量/sale$通过量, 通过率 = sale$通过量/sale$总量) %>% mutate(未通过量 = sale$总量-sale$通过量) %>% select(分类,时间,通过量,未通过量,通过率)


#通过率
highchart() %>% 
    #hc_title(text = "坏账率") %>% 
    hc_legend(enabled = FALSE) %>% 
    hc_xAxis(categories = pass_rate$时间) %>% 
    hc_yAxis_multiples(
        list(
            title = list(text = "通过率"),
            align = "left",
            showFirstLabel = FALSE,
            showLastLabel = FALSE,
            labels = list(format = "{value}", useHTML = TRUE)
        ),
        
        list(
            title = list(text = "通过量"),
            align = "right",
            showFirstLabel = FALSE,
            showLastLabel = FALSE,
            labels = list(format = "{value} 单"),
            opposite = TRUE
        )
    ) %>% 
    hc_plotOptions(column = list(stacking = "normal")) %>%
    
    hc_add_series(name = "销售未通过量", 
                  type = "column",
                  data = filter(pass_rate,分类=="销售")$未通过量, 
                  yAxis = 1,
                  stack = "M",
                  color=col[2]) %>% 
    hc_add_series(name = "销售通过量", 
                  type = "column",
                  data = filter(pass_rate,分类=="销售")$通过量,
                  yAxis = 1,
                  stack = "M",
                  color=col[1]) %>%
    
    
    hc_add_series(name = "门店未通过量", 
                  type = "column",
                  data = filter(pass_rate,分类=="门店")$未通过量, 
                  yAxis = 1,
                  stack = "F",
                  color=col[4]) %>% 
    hc_add_series(name = "门店通过量", 
                  type = "column",
                  data = filter(pass_rate,分类=="门店")$通过量,
                  yAxis = 1,
                  stack = "F",
                  color=col[3]) %>%   #stack by group
    
    hc_add_series(name = "销售通过率", data = filter(pass_rate,分类=="门店")$通过率) %>%
    hc_add_series(name = "门店通过率", data = filter(pass_rate,分类=="销售")$通过率) %>%
    hc_tooltip(crosshairs = TRUE, #backgroundColor = "gray",
               #headerFormat = "This is a custom header
", shared = F, borderWidth = 5, valueDecimals = 2, pointFormat = "{series.name} : {point.y}
总量: {point.stackTotal}") #%>%hc_add_theme(hc_theme_economist()) ``` ### 坏账率 ```{r} bad_debt=sale %>% mutate(坏账率 = sale$坏账量/sale$通过量, 通过率 = sale$通过量/sale$总量) %>% mutate(非坏账量 = sale$通过量-sale$坏账量) %>% select(分类,时间,坏账量,非坏账量,坏账率) #坏账率 highchart() %>% #hc_title(text = "坏账率") %>% hc_legend(enabled = FALSE) %>% hc_xAxis(categories = bad_debt$时间) %>% hc_yAxis_multiples( list( title = list(text = "坏账率"), align = "left", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value}", useHTML = TRUE) ), list( title = list(text = "坏账量"), align = "right", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value} 单"), opposite = TRUE ) ) %>% hc_plotOptions(column = list(stacking = "normal")) %>% hc_add_series(name = "销售非坏账量", type = "column", data = filter(bad_debt,分类=="销售")$非坏账量, yAxis = 1, stack = "M", color=col[1]) %>% hc_add_series(name = "销售坏账量", type = "column", data = filter(bad_debt,分类=="销售")$坏账量, yAxis = 1, stack = "M", color=col[2]) %>% hc_add_series(name = "门店非坏账量", type = "column", data = filter(bad_debt,分类=="门店")$非坏账量, yAxis = 1, stack = "F", color=col[3]) %>% hc_add_series(name = "门店坏账量", type = "column", data = filter(bad_debt,分类=="门店")$坏账量, yAxis = 1, stack = "F", color=col[4]) %>% #stack by group hc_add_series(name = "门店坏账率", data = filter(bad_debt,分类=="门店")$坏账率, color=col[6]) %>% hc_add_series(name = "销售坏账率", data = filter(bad_debt,分类=="销售")$坏账率, color=col[5]) %>% hc_tooltip(crosshairs = TRUE, #backgroundColor = "gray", #headerFormat = "This is a custom header
", shared = F, borderWidth = 5, valueDecimals = 2, pointFormat = "{series.name} : {point.y}
总量: {point.stackTotal}") ``` Column {data-width=500} ----------------------------------------------------------------------- ### 数据 ```{r} #sale$ID[1:5]="销售" #datatable(sale)# %>% formatPercentage(c('坏账率',"通过率"), 2) #%>% formatDate("时间",'toLocaleDateString') knitr::kable(sale[,-1]) ``` ### 销售区域1 ```{r} #use leaflet to plot m=place_com %>% filter(place_com$姓名=="乔健") content <- paste0("姓名: Amanda", "
省份: ", m$省份, "
快捷到岗日期: ", m$快捷到岗日期, "
销售编号: ", m$销售编号) m %>% leaflet() %>% addTiles() %>% setView(lng=104.19540, lat=35.86166, zoom = 4) %>% addMarkers(lat = ~ lat, lng = ~ lon, popup =content ) ``` ```{r, results='asis', echo=FALSE,eval=FALSE} #use givsGeoChart to plot Geo <- gvisGeoChart(place[1,], locationvar="code", hovervar="姓名", options=list(region="CN", displayMode="regions", #show to show data value resolution="provinces", colorAxis="{colors:['#71196E', '#71196E']}", #backgroundColor="#FCFFA4", width=600, height=400)) #plot(Geo) Tbl <- gvisTable(place[1,]) G=gvisMerge(Geo, Tbl) print(G,"chart") ``` Angela ======================================================================= Column {data-width=500} ----------------------------------------------------------------------- ### 通过率 ```{r} #select 销售=张鹤立 sale=ind %>% filter(ind$姓名=="张鹤立") pass_rate=sale %>% mutate(坏账率 = sale$坏账量/sale$通过量, 通过率 = sale$通过量/sale$总量) %>% mutate(未通过量 = sale$总量-sale$通过量) %>% select(分类,时间,通过量,未通过量,通过率) #通过率 highchart() %>% #hc_title(text = "坏账率") %>% hc_legend(enabled = FALSE) %>% hc_xAxis(categories = pass_rate$时间) %>% hc_yAxis_multiples( list( title = list(text = "通过率"), align = "left", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value}", useHTML = TRUE) ), list( title = list(text = "通过量"), align = "right", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value} 单"), opposite = TRUE ) ) %>% hc_plotOptions(column = list(stacking = "normal")) %>% hc_add_series(name = "销售未通过量", type = "column", data = filter(pass_rate,分类=="销售")$未通过量, yAxis = 1, stack = "M", color=col[2]) %>% hc_add_series(name = "销售通过量", type = "column", data = filter(pass_rate,分类=="销售")$通过量, yAxis = 1, stack = "M", color=col[1]) %>% hc_add_series(name = "门店未通过量", type = "column", data = filter(pass_rate,分类=="门店")$未通过量, yAxis = 1, stack = "F", color=col[4]) %>% hc_add_series(name = "门店通过量", type = "column", data = filter(pass_rate,分类=="门店")$通过量, yAxis = 1, stack = "F", color=col[3]) %>% #stack by group hc_add_series(name = "销售通过率", data = filter(pass_rate,分类=="门店")$通过率) %>% hc_add_series(name = "门店通过率", data = filter(pass_rate,分类=="销售")$通过率) %>% hc_tooltip(crosshairs = TRUE, #backgroundColor = "gray", #headerFormat = "This is a custom header
", shared = F, borderWidth = 5, valueDecimals = 2, pointFormat = "{series.name} : {point.y}
总量: {point.stackTotal}") #%>%hc_add_theme(hc_theme_economist()) ``` ### 坏账率 ```{r} bad_debt=sale %>% mutate(坏账率 = sale$坏账量/sale$通过量, 通过率 = sale$通过量/sale$总量) %>% mutate(非坏账量 = sale$通过量-sale$坏账量) %>% select(分类,时间,坏账量,非坏账量,坏账率) #坏账率 highchart() %>% #hc_title(text = "坏账率") %>% hc_legend(enabled = FALSE) %>% hc_xAxis(categories = bad_debt$时间) %>% hc_yAxis_multiples( list( title = list(text = "坏账率"), align = "left", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value}", useHTML = TRUE) ), list( title = list(text = "坏账量"), align = "right", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value} 单"), opposite = TRUE ) ) %>% hc_plotOptions(column = list(stacking = "normal")) %>% hc_add_series(name = "销售非坏账量", type = "column", data = filter(bad_debt,分类=="销售")$非坏账量, yAxis = 1, stack = "M", color=col[1]) %>% hc_add_series(name = "销售坏账量", type = "column", data = filter(bad_debt,分类=="销售")$坏账量, yAxis = 1, stack = "M", color=col[2]) %>% hc_add_series(name = "门店非坏账量", type = "column", data = filter(bad_debt,分类=="门店")$非坏账量, yAxis = 1, stack = "F", color=col[3]) %>% hc_add_series(name = "门店坏账量", type = "column", data = filter(bad_debt,分类=="门店")$坏账量, yAxis = 1, stack = "F", color=col[4]) %>% #stack by group hc_add_series(name = "门店坏账率", data = filter(bad_debt,分类=="门店")$坏账率, color=col[6]) %>% hc_add_series(name = "销售坏账率", data = filter(bad_debt,分类=="销售")$坏账率, color=col[5]) %>% hc_tooltip(crosshairs = TRUE, #backgroundColor = "gray", #headerFormat = "This is a custom header
", shared = F, borderWidth = 5, valueDecimals = 2, pointFormat = "{series.name} : {point.y}
总量: {point.stackTotal}") ``` Column {data-width=500} ----------------------------------------------------------------------- ### 数据 ```{r} knitr::kable(sale[,-1]) ``` ### 销售区域2 ```{r} #地图地点 m=place_com %>% filter(place_com$姓名=="张鹤立") content <- paste0("姓名: Angela", "
省份: ", m$省份, "
快捷到岗日期: ", m$快捷到岗日期, "
销售编号: ", m$销售编号) m %>% leaflet() %>% addTiles() %>% setView(lng=104.19540, lat=35.86166, zoom = 4) %>% addMarkers(lat = ~ lat, lng = ~ lon, popup =content ) ``` Justin ======================================================================= Column {data-width=500} ----------------------------------------------------------------------- ### 通过率 ```{r} #select 销售=张德康 sale=ind %>% filter(ind$姓名=="张德康") pass_rate=sale %>% mutate(坏账率 = sale$坏账量/sale$通过量, 通过率 = sale$通过量/sale$总量) %>% mutate(未通过量 = sale$总量-sale$通过量) %>% select(分类,时间,通过量,未通过量,通过率) #通过率 highchart() %>% #hc_title(text = "坏账率") %>% hc_legend(enabled = FALSE) %>% hc_xAxis(categories = pass_rate$时间) %>% hc_yAxis_multiples( list( title = list(text = "通过率"), align = "left", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value}", useHTML = TRUE) ), list( title = list(text = "通过量"), align = "right", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value} 单"), opposite = TRUE ) ) %>% hc_plotOptions(column = list(stacking = "normal")) %>% hc_add_series(name = "销售未通过量", type = "column", data = filter(pass_rate,分类=="销售")$未通过量, yAxis = 1, stack = "M", color=col[2]) %>% hc_add_series(name = "销售通过量", type = "column", data = filter(pass_rate,分类=="销售")$通过量, yAxis = 1, stack = "M", color=col[1]) %>% hc_add_series(name = "门店未通过量", type = "column", data = filter(pass_rate,分类=="门店")$未通过量, yAxis = 1, stack = "F", color=col[4]) %>% hc_add_series(name = "门店通过量", type = "column", data = filter(pass_rate,分类=="门店")$通过量, yAxis = 1, stack = "F", color=col[3]) %>% #stack by group hc_add_series(name = "销售通过率", data = filter(pass_rate,分类=="门店")$通过率) %>% hc_add_series(name = "门店通过率", data = filter(pass_rate,分类=="销售")$通过率) %>% hc_tooltip(crosshairs = TRUE, #backgroundColor = "gray", #headerFormat = "This is a custom header
", shared = F, borderWidth = 5, valueDecimals = 2, pointFormat = "{series.name} : {point.y}
总量: {point.stackTotal}") #%>%hc_add_theme(hc_theme_economist()) ``` ### 坏账率 ```{r} bad_debt=sale %>% mutate(坏账率 = sale$坏账量/sale$通过量, 通过率 = sale$通过量/sale$总量) %>% mutate(非坏账量 = sale$通过量-sale$坏账量) %>% select(分类,时间,坏账量,非坏账量,坏账率) #坏账率 highchart() %>% #hc_title(text = "坏账率") %>% hc_legend(enabled = FALSE) %>% hc_xAxis(categories = bad_debt$时间) %>% hc_yAxis_multiples( list( title = list(text = "坏账率"), align = "left", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value}", useHTML = TRUE) ), list( title = list(text = "坏账量"), align = "right", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value} 单"), opposite = TRUE ) ) %>% hc_plotOptions(column = list(stacking = "normal")) %>% hc_add_series(name = "销售非坏账量", type = "column", data = filter(bad_debt,分类=="销售")$非坏账量, yAxis = 1, stack = "M", color=col[1]) %>% hc_add_series(name = "销售坏账量", type = "column", data = filter(bad_debt,分类=="销售")$坏账量, yAxis = 1, stack = "M", color=col[2]) %>% hc_add_series(name = "门店非坏账量", type = "column", data = filter(bad_debt,分类=="门店")$非坏账量, yAxis = 1, stack = "F", color=col[3]) %>% hc_add_series(name = "门店坏账量", type = "column", data = filter(bad_debt,分类=="门店")$坏账量, yAxis = 1, stack = "F", color=col[4]) %>% #stack by group hc_add_series(name = "门店坏账率", data = filter(bad_debt,分类=="门店")$坏账率, color=col[6]) %>% hc_add_series(name = "销售坏账率", data = filter(bad_debt,分类=="销售")$坏账率, color=col[5]) %>% hc_tooltip(crosshairs = TRUE, #backgroundColor = "gray", #headerFormat = "This is a custom header
", shared = F, borderWidth = 5, valueDecimals = 2, pointFormat = "{series.name} : {point.y}
总量: {point.stackTotal}") ``` Column {data-width=500} ----------------------------------------------------------------------- ### 数据 ```{r} knitr::kable(sale[,-1]) ``` ### 销售区域3 ```{r} #地图地点 m=place_com %>% filter(place_com$姓名=="张德康") content <- paste0("姓名: Justin", "
省份: ", m$省份, "
快捷到岗日期: ", m$快捷到岗日期, "
销售编号: ", m$销售编号) m %>% leaflet() %>% addTiles() %>% setView(lng=104.19540, lat=35.86166, zoom = 4) %>% addMarkers(lat = ~ lat, lng = ~ lon, popup =content ) ``` Taylor ======================================================================= Column {data-width=500} ----------------------------------------------------------------------- ### 通过率 ```{r} #select 销售=义鑫 sale=ind %>% filter(ind$姓名=="义鑫") pass_rate=sale %>% mutate(坏账率 = sale$坏账量/sale$通过量, 通过率 = sale$通过量/sale$总量) %>% mutate(未通过量 = sale$总量-sale$通过量) %>% select(分类,时间,通过量,未通过量,通过率) #通过率 highchart() %>% #hc_title(text = "坏账率") %>% hc_legend(enabled = FALSE) %>% hc_xAxis(categories = pass_rate$时间) %>% hc_yAxis_multiples( list( title = list(text = "通过率"), align = "left", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value}", useHTML = TRUE) ), list( title = list(text = "通过量"), align = "right", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value} 单"), opposite = TRUE ) ) %>% hc_plotOptions(column = list(stacking = "normal")) %>% hc_add_series(name = "销售未通过量", type = "column", data = filter(pass_rate,分类=="销售")$未通过量, yAxis = 1, stack = "M", color=col[2]) %>% hc_add_series(name = "销售通过量", type = "column", data = filter(pass_rate,分类=="销售")$通过量, yAxis = 1, stack = "M", color=col[1]) %>% hc_add_series(name = "门店未通过量", type = "column", data = filter(pass_rate,分类=="门店")$未通过量, yAxis = 1, stack = "F", color=col[4]) %>% hc_add_series(name = "门店通过量", type = "column", data = filter(pass_rate,分类=="门店")$通过量, yAxis = 1, stack = "F", color=col[3]) %>% #stack by group hc_add_series(name = "销售通过率", data = filter(pass_rate,分类=="门店")$通过率) %>% hc_add_series(name = "门店通过率", data = filter(pass_rate,分类=="销售")$通过率) %>% hc_tooltip(crosshairs = TRUE, #backgroundColor = "gray", #headerFormat = "This is a custom header
", shared = F, borderWidth = 5, valueDecimals = 2, pointFormat = "{series.name} : {point.y}
总量: {point.stackTotal}") #%>%hc_add_theme(hc_theme_economist()) ``` ### 坏账率 ```{r} bad_debt=sale %>% mutate(坏账率 = sale$坏账量/sale$通过量, 通过率 = sale$通过量/sale$总量) %>% mutate(非坏账量 = sale$通过量-sale$坏账量) %>% select(分类,时间,坏账量,非坏账量,坏账率) #坏账率 highchart() %>% #hc_title(text = "坏账率") %>% hc_legend(enabled = FALSE) %>% hc_xAxis(categories = bad_debt$时间) %>% hc_yAxis_multiples( list( title = list(text = "坏账率"), align = "left", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value}", useHTML = TRUE) ), list( title = list(text = "坏账量"), align = "right", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value} 单"), opposite = TRUE ) ) %>% hc_plotOptions(column = list(stacking = "normal")) %>% hc_add_series(name = "销售非坏账量", type = "column", data = filter(bad_debt,分类=="销售")$非坏账量, yAxis = 1, stack = "M", color=col[1]) %>% hc_add_series(name = "销售坏账量", type = "column", data = filter(bad_debt,分类=="销售")$坏账量, yAxis = 1, stack = "M", color=col[2]) %>% hc_add_series(name = "门店非坏账量", type = "column", data = filter(bad_debt,分类=="门店")$非坏账量, yAxis = 1, stack = "F", color=col[3]) %>% hc_add_series(name = "门店坏账量", type = "column", data = filter(bad_debt,分类=="门店")$坏账量, yAxis = 1, stack = "F", color=col[4]) %>% #stack by group hc_add_series(name = "门店坏账率", data = filter(bad_debt,分类=="门店")$坏账率, color=col[6]) %>% hc_add_series(name = "销售坏账率", data = filter(bad_debt,分类=="销售")$坏账率, color=col[5]) %>% hc_tooltip(crosshairs = TRUE, #backgroundColor = "gray", #headerFormat = "This is a custom header
", shared = F, borderWidth = 5, valueDecimals = 2, pointFormat = "{series.name} : {point.y}
总量: {point.stackTotal}") ``` Column {data-width=500} ----------------------------------------------------------------------- ### 数据 ```{r} knitr::kable(sale[,-1]) ``` ### 销售区域4 ```{r} #地图地点 m=place_com %>% filter(place_com$姓名=="义鑫") content <- paste0("姓名: Taylor", "
省份: ", m$省份, "
快捷到岗日期: ", m$快捷到岗日期, "
销售编号: ", m$销售编号) m %>% leaflet() %>% addTiles() %>% setView(lng=104.19540, lat=35.86166, zoom = 4) %>% addMarkers(lat = ~ lat, lng = ~ lon, popup =content ) ``` Megan ======================================================================= Column {data-width=500} ----------------------------------------------------------------------- ### 通过率 ```{r} #select 销售=肖卓 sale=ind %>% filter(ind$姓名=="肖卓") pass_rate=sale %>% mutate(坏账率 = sale$坏账量/sale$通过量, 通过率 = sale$通过量/sale$总量) %>% mutate(未通过量 = sale$总量-sale$通过量) %>% select(分类,时间,通过量,未通过量,通过率) #通过率 highchart() %>% #hc_title(text = "坏账率") %>% hc_legend(enabled = FALSE) %>% hc_xAxis(categories = pass_rate$时间) %>% hc_yAxis_multiples( list( title = list(text = "通过率"), align = "left", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value}", useHTML = TRUE) ), list( title = list(text = "通过量"), align = "right", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value} 单"), opposite = TRUE ) ) %>% hc_plotOptions(column = list(stacking = "normal")) %>% hc_add_series(name = "销售未通过量", type = "column", data = filter(pass_rate,分类=="销售")$未通过量, yAxis = 1, stack = "M", color=col[2]) %>% hc_add_series(name = "销售通过量", type = "column", data = filter(pass_rate,分类=="销售")$通过量, yAxis = 1, stack = "M", color=col[1]) %>% hc_add_series(name = "门店未通过量", type = "column", data = filter(pass_rate,分类=="门店")$未通过量, yAxis = 1, stack = "F", color=col[4]) %>% hc_add_series(name = "门店通过量", type = "column", data = filter(pass_rate,分类=="门店")$通过量, yAxis = 1, stack = "F", color=col[3]) %>% #stack by group hc_add_series(name = "销售通过率", data = filter(pass_rate,分类=="门店")$通过率) %>% hc_add_series(name = "门店通过率", data = filter(pass_rate,分类=="销售")$通过率) %>% hc_tooltip(crosshairs = TRUE, #backgroundColor = "gray", #headerFormat = "This is a custom header
", shared = F, borderWidth = 5, valueDecimals = 2, pointFormat = "{series.name} : {point.y}
总量: {point.stackTotal}") #%>%hc_add_theme(hc_theme_economist()) ``` ### 坏账率 ```{r} bad_debt=sale %>% mutate(坏账率 = sale$坏账量/sale$通过量, 通过率 = sale$通过量/sale$总量) %>% mutate(非坏账量 = sale$通过量-sale$坏账量) %>% select(分类,时间,坏账量,非坏账量,坏账率) #坏账率 highchart() %>% #hc_title(text = "坏账率") %>% hc_legend(enabled = FALSE) %>% hc_xAxis(categories = bad_debt$时间) %>% hc_yAxis_multiples( list( title = list(text = "坏账率"), align = "left", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value}", useHTML = TRUE) ), list( title = list(text = "坏账量"), align = "right", showFirstLabel = FALSE, showLastLabel = FALSE, labels = list(format = "{value} 单"), opposite = TRUE ) ) %>% hc_plotOptions(column = list(stacking = "normal")) %>% hc_add_series(name = "销售非坏账量", type = "column", data = filter(bad_debt,分类=="销售")$非坏账量, yAxis = 1, stack = "M", color=col[1]) %>% hc_add_series(name = "销售坏账量", type = "column", data = filter(bad_debt,分类=="销售")$坏账量, yAxis = 1, stack = "M", color=col[2]) %>% hc_add_series(name = "门店非坏账量", type = "column", data = filter(bad_debt,分类=="门店")$非坏账量, yAxis = 1, stack = "F", color=col[3]) %>% hc_add_series(name = "门店坏账量", type = "column", data = filter(bad_debt,分类=="门店")$坏账量, yAxis = 1, stack = "F", color=col[4]) %>% #stack by group hc_add_series(name = "门店坏账率", data = filter(bad_debt,分类=="门店")$坏账率, color=col[6]) %>% hc_add_series(name = "销售坏账率", data = filter(bad_debt,分类=="销售")$坏账率, color=col[5]) %>% hc_tooltip(crosshairs = TRUE, #backgroundColor = "gray", #headerFormat = "This is a custom header
", shared = F, borderWidth = 5, valueDecimals = 2, pointFormat = "{series.name} : {point.y}
总量: {point.stackTotal}") ``` Column {data-width=500} ----------------------------------------------------------------------- ### 数据 ```{r} knitr::kable(sale[,-1]) ``` ### 销售区域5 ```{r} #地图地点 m=place_com %>% filter(place_com$姓名=="肖卓") content <- paste0("姓名: Megan", "
省份: ", m$省份, "
快捷到岗日期: ", m$快捷到岗日期, "
销售编号: ", m$销售编号) m %>% leaflet() %>% addTiles() %>% setView(lng=104.19540, lat=35.86166, zoom = 4) %>% addMarkers(lat = ~ lat, lng = ~ lon, popup =content ) ```