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BackFedDataAnalytics/visual0721.R

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2025-07-21 16:52:39 +08:00
library(shiny)
library(DT)
library(dplyr)
library(readr)
library(Cairo)
library(ggplot2)
library(plotly)
library(stringi)
library(stringr)
library(datetime)
library(dplyr)
library(ggthemes)
library(RMySQL)
library(shinyCyJS)
csv_map <- list(
"按月统计" = "按月统计0.csv",
"最后六周按日统计" = "按日统计0.csv",
"按小细胞统计" = "按细胞统计0.csv",
"按省统计" = "按区域统计0.csv",
"按仪器统计" = "按仪器统计0.csv",
"按样本类型统计" = "按样本统计0.csv",
"按试剂批次统计" = "按批次统计0.csv",
"按试剂项目统计" = "按项目统计0.csv"
)
page<-1
max_pages<-1
ui <- fluidPage(
tags$head(tags$title("丹娜数据分析平台")),
tags$img(src = "dnklogo.png", height = "75px", alt = "Logo",style = "float: right;"),
titlePanel(
HTML("
<div style='text-align: left;'>
<div style='font-size: 28px; color: skyblue; font-weight: bold;'>丹娜数据分析平台</div>
<div style='font-size: 14px; color: skyblue;'>和迈仪器</div>
</div>
")
),
# titlePanel("丹娜数据分析平台-和迈仪器"),
sidebarLayout(
sidebarPanel(
width = 3, # 设置侧边栏宽度为 2（更小）
selectInput("stat_dim", "选择统计维度",
choices = names(csv_map)),
uiOutput("metric_group"),
uiOutput("stat_way"),
br(),
br(),
downloadButton("download_table", "下载表格数据")
),
mainPanel(
width = 9,
tabsetPanel(
tabPanel("图表展示",
uiOutput("pagination_ui"),
plotlyOutput("main_plot")),
tabPanel("数据表格", DTOutput("data_table")),
tabPanel("仪器与小细胞（coming soon)", ShinyCyJSOutput(outputId = "cy"))
)
)
)
)
# 定义服务器逻辑
server <- function(input, output) {
current_page <- reactiveVal(page)
# current_page <- reactiveVal()
output$download_table <- downloadHandler(
filename = function() {
paste0(input$stat_dim, "_", Sys.Date(), ".csv")
},
content = function(file) {
data <- data_raw()
write_excel_csv(data, file)
}
)
nodes <- data.frame(
id = c("A", "B", "C", "D"),
width = c(10, 20, 30, 40),
height = c(10, 20, 30, 40)
)
edges <- data.frame(
source = c("A", "B", "C", "D"),
target = c("B", "C", "D", "B")
)
nodes <- buildElems(nodes, type = "Node")
edges <- buildElems(edges, type = "Edge")
obj <- shinyCyJS(c(nodes, edges))
output$cy <- renderShinyCyJS(obj)
output$pagination_ui <- renderUI({
req(input$stat_dim, input$metric, input$stat_way_sel)
max_pages <- switch(input$stat_dim,
"最后六周按日统计" = {
if (input$stat_way_sel == "按日分省统计") {
ceiling(length(dfBy区域$省编号) / 6)
} else if (input$stat_way_sel == "按日分小细胞统计") {
ceiling(length(细胞0$细胞) / 6)
} else if (input$stat_way_sel == "按日分仪器统计") {
ceiling(length(仪器号List$仪器序列号) / 6)
} else 1
},
"按月统计" = {
if (input$stat_way_sel == "按月分省统计") {
ceiling(length(dfBy区域$省编号) / 6)
} else if (input$stat_way_sel == "按月分小细胞统计") {
ceiling(length(细胞0$细胞) / 6)
} else if (input$stat_way_sel == "按月分仪器统计") {
ceiling(length(仪器号List$仪器序列号) / 6)
} else 1
},
"按仪器统计" = max(仪器号List$GroupID),
"按试剂批次统计" = max(批次号List$GroupID),
"按试剂项目统计" = max(项目号List$GroupID),
"按小细胞统计" = 2,
1)
page<-current_page()
if(!is.numeric(page)) {
page<-1
} else {
if(page>max_pages) page<-max_pages
}
if (max_pages > 1) {
tagList(
actionButton("prev_page", "上一页"),
span(paste("第", page, "页 / 共", max_pages, "页")),
actionButton("next_page", "下一页")
)
}
})
observeEvent(input$prev_page, {
max_pages <- switch(input$stat_dim,
"最后六周按日统计" = {
if (input$stat_way_sel == "按日分省统计") {
ceiling(length(dfBy区域$省编号) / 6)
} else if (input$stat_way_sel == "按日分小细胞统计") {
ceiling(length(细胞0$细胞) / 6)
} else if (input$stat_way_sel == "按日分仪器统计") {
ceiling(length(仪器号List$仪器序列号) / 6)
} else 1
},
"按月统计" = {
if (input$stat_way_sel == "按月分省统计") {
ceiling(length(dfBy区域$省编号) / 6)
} else if (input$stat_way_sel == "按月分小细胞统计") {
ceiling(length(细胞0$细胞) / 6)
} else if (input$stat_way_sel == "按月分仪器统计") {
ceiling(length(仪器号List$仪器序列号) / 6)
} else 1
},
"按仪器统计" = max(仪器号List$GroupID),
"按试剂批次统计" = max(批次号List$GroupID),
"按试剂项目统计" = max(项目号List$GroupID),
"按小细胞统计" = 2,
1)
page<-min(current_page(),max_pages)
if (page > 1) current_page(page - 1) else 1
})
observeEvent(input$next_page, {
max_pages <- switch(input$stat_dim,
"最后六周按日统计" = {
if (input$stat_way_sel == "按日分省统计") {
ceiling(length(dfBy区域$省编号) / 6)
} else if (input$stat_way_sel == "按日分小细胞统计") {
ceiling(length(细胞0$细胞) / 6)
} else if (input$stat_way_sel == "按日分仪器统计") {
ceiling(length(仪器号List$仪器序列号) / 6)
} else 1
},
"按月统计" = {
if (input$stat_way_sel == "按月分省统计") {
ceiling(length(dfBy区域$省编号) / 6)
} else if (input$stat_way_sel == "按月分小细胞统计") {
ceiling(length(细胞0$细胞) / 6)
} else if (input$stat_way_sel == "按月分仪器统计") {
ceiling(length(仪器号List$仪器序列号) / 6)
} else 1
},
"按仪器统计" = max(仪器号List$GroupID),
"按试剂批次统计" = max(批次号List$GroupID),
"按试剂项目统计" = max(项目号List$GroupID),
"按小细胞统计" = 2,
1)
page<-min(current_page(),max_pages)
if (page<max_pages) current_page(page + 1) else max_pages
})
# 动态生成第二栏：指标分组
output$metric_group <- renderUI({
metric_choices <- switch(input$stat_dim,
"最后六周按日统计" = list("测试数、阳性数、有效数",
"阳性率、有效率",
"项目数、仪器数、批次数",
"省数、市数、小细胞数、样本数"),
"按月统计" = list("测试数、阳性数、有效数",
"阳性率、有效率",
"项目数、仪器数、批次数",
"省数、市数、小细胞数、样本数"),
"按小细胞统计"=list("测试数、阳性数、有效数",
"阳性率、有效率",
"项目数、仪器数、批次数",
"省数、市数、小细胞数、样本数",
"测试截止、测试开始"),
"按省统计" = list("测试数、阳性数、有效数",
"阳性率、有效率",
"项目数、仪器数、批次数",
"省数、市数、小细胞数、样本数",
"测试截止、测试开始"),
"按仪器统计" = list("测试数、阳性数、有效数",
"阳性率、有效率",
"项目数、仪器数、批次数",
"省数、市数、小细胞数、样本数",
"测试截止、测试开始"),
"按样本类型统计" = list("测试数、阳性数、有效数",
"阳性率、有效率",
"项目数、仪器数、批次数",
"省数、市数、小细胞数、样本数"),
"按试剂批次统计" = list("测试数、阳性数、有效数",
"阳性率、有效率",
"项目数、仪器数、批次数",
"省数、市数、小细胞数、样本数",
"测试截止、测试开始"),
"按试剂项目统计" = list("测试数、阳性数、有效数",
"阳性率、有效率",
"项目数、仪器数、批次数",
"省数、市数、小细胞数、样本数",
"测试截止、测试开始"))
selectInput("metric", "选择指标分组", choices = metric_choices)
})
# 动态生成第三栏：统计方式
output$stat_way <- renderUI({
way_choices <- switch(input$stat_dim,
"按月统计" = c("全部统计","按月分省统计","按月分小细胞统计","按月分仪器统计"),
"最后六周按日统计" = c("全部统计","按日分省统计", "按日分小细胞统计","按日分仪器统计"),
"按小细胞统计" = "全部统计",
"按省统计" = "全部统计",
"按仪器统计" = "全部统计",
"按样本类型统计" = "全部统计",
"按试剂批次统计" = "全部统计",
"按试剂项目统计"="全部统计")
if (is.character(way_choices)) {
selectInput("stat_way_sel", "选择统计方式", choices = way_choices)
} else {
NULL
}
})
data_raw <- reactive({
read_csv(csv_map[[input$stat_dim]])
})
# 生成数据表格
output$data_table <- renderDT({
datatable(data_raw(), options = list(pageLength = 10))
})
# 生成图表
output$main_plot <- renderPlotly({
req(input$stat_dim, input$metric, input$stat_way_sel)
data <- generate_data_table(input$stat_dim, input$metric)
# 把当前页码传进去
generate_plot(data, input$stat_dim, input$metric, input$stat_way_sel, current_page())
})
}
plotfunction<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,
text = paste( round(Count, 2)) ,fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# linewidth = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
plotfunctionVector仪器序列号<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
dfData<-dfData[(dfData$仪器序列号 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
plotfunctionVector批次名称<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
dfData<-dfData[(dfData$批次名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
plotfunctionVector批次名称Log<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
dfData<-dfData[(dfData$批次名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
scale_y_log10()+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
plotfunctionVector项目名称<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
dfData<-dfData[(dfData$项目名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
plotfunctionVector项目名称Log<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
dfData<-dfData[(dfData$项目名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
scale_y_log10()+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
plotfunctionLog<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
scale_y_log10()+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
plotfunctionVector仪器序列号Log<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
dfData<-dfData[(dfData$仪器序列号 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
scale_y_log10()+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
panelPlotByDayAndLocation<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
dfData00<-dfData00[dfData00$省编号 %in% choosenList,]
dfData00$省编号<-factor(dfData00$省编号,levels = choosenList)
plot1<-ggplot(dfData00, aes(x = testDay, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
facet_wrap( ~ 省编号,ncol=2) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
panel.border = element_rect(
color = "black", # 边框颜色
linewidth = 1., # 边框粗细
linetype = "solid", # 线型（solid/dashed/dotted）
fill = NA # 填充色（NA为透明）
),
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
panelPlotByMonthAndLocation<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
dfData00<-dfData00[dfData00$省编号 %in% choosenList,]
dfData00$省编号<-factor(dfData00$省编号,levels = choosenList)
plot1<-ggplot(dfData00, aes(x = testMonth, y = Count, text = paste( round(Count, 2)) ,fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
facet_wrap( ~ 省编号,ncol=2) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
panel.border = element_rect(
color = "black", # 边框颜色
linewidth = 1., # 边框粗细
linetype = "solid", # 线型（solid/dashed/dotted）
fill = NA # 填充色（NA为透明）
),
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
panelPlotByDayAnd细胞<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
dfData00<-dfData00[dfData00$小细胞 %in% choosenList,]
dfData00$小细胞<-factor(dfData00$小细胞,levels = choosenList)
plot1<-ggplot(dfData00, aes(x = testDay, y = Count, text = paste( round(Count, 2)) ,fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
facet_wrap( ~ 小细胞,ncol=2) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
panel.border = element_rect(
color = "black", # 边框颜色
linewidth = 1., # 边框粗细
linetype = "solid", # 线型（solid/dashed/dotted）
fill = NA # 填充色（NA为透明）
),
legend.position = "right")+guides(color = "none")
#plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
panelPlotByMonthAnd细胞<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
dfData00<-dfData00[dfData00$小细胞 %in% choosenList,]
dfData00$小细胞<-factor(dfData00$小细胞,levels = choosenList)
plot1<-ggplot(dfData00, aes(x = testMonth, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
facet_wrap( ~ 小细胞,ncol=2) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
panel.border = element_rect(
color = "black", # 边框颜色
linewidth = 1., # 边框粗细
linetype = "solid", # 线型（solid/dashed/dotted）
fill = NA # 填充色（NA为透明）
),
legend.position = "right")+guides(color = "none")
#plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
pointPlotfunction批次<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
plot1 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(批次名称)))+
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
labs(
title = titleNames[1], # 主标题
x = titleNames[2], # X轴标签
y = titleNames[3], # Y轴标签
color = titleNames[4] # 图例标题
)+
# scale_x_date(
# date_labels = "%Y-%m-%d", # 格式符组合
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
# )+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 10,face = "bold"),
axis.title.y = element_text(size = 10,face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90),
legend.position = "right")+guides(color = "none")
#plot2
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
pointPlotfunction批次Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(批次名称)))+
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
labs(
title = titleNames[1], # 主标题
x = titleNames[2], # X轴标签
y = titleNames[3], # Y轴标签
color = titleNames[4] # 图例标题
)+
# scale_x_date(
# date_labels = "%Y-%m-%d", # 格式符组合
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
# )+
scale_y_log10()+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 10,face = "bold"),
axis.title.y = element_text(size = 10,face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90),
legend.position = "right")+guides(color = "none")
# plot2
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
pointPlotfunction仪器<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(仪器序列号)))+
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
labs(
title = titleNames[1], # 主标题
x = titleNames[2], # X轴标签
y = titleNames[3], # Y轴标签
color = titleNames[4] # 图例标题
)+
# scale_x_date(
# date_labels = "%Y-%m-%d", # 格式符组合
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
# )+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 10,face = "bold"),
axis.title.y = element_text(size = 10,face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90),
legend.position = "right")+guides(color = "none")
#plot2
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
pointPlotfunction仪器Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(仪器序列号)))+
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
labs(
title = titleNames[1], # 主标题
x = titleNames[2], # X轴标签
y = titleNames[3], # Y轴标签
color = titleNames[4] # 图例标题
)+
# scale_x_date(
# date_labels = "%Y-%m-%d", # 格式符组合
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
# )+
scale_y_log10()+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 10,face = "bold"),
axis.title.y = element_text(size = 10,face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90),
legend.position = "right")+guides(color = "none")
# plot2
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
pointPlotfunction样本<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(样本类型)))+
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
labs(
title = titleNames[1], # 主标题
x = titleNames[2], # X轴标签
y = titleNames[3], # Y轴标签
color = titleNames[4] # 图例标题
)+
# scale_x_date(
# date_labels = "%Y-%m-%d", # 格式符组合
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
# )+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 10,face = "bold"),
axis.title.y = element_text(size = 10,face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90),
legend.position = "right")+guides(color = "none")
# plot2
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
pointPlotfunction样本Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(样本类型)))+
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
labs(
title = titleNames[1], # 主标题
x = titleNames[2], # X轴标签
y = titleNames[3], # Y轴标签
color = titleNames[4] # 图例标题
)+
# scale_x_date(
# date_labels = "%Y-%m-%d", # 格式符组合
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
# )+
scale_y_log10()+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 10,face = "bold"),
axis.title.y = element_text(size = 10,face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90),
legend.position = "right")+guides(color = "none")
# plot2
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
pointPlotfunction项目<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(项目名称)))+
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
labs(
title = titleNames[1], # 主标题
x = titleNames[2], # X轴标签
y = titleNames[3], # Y轴标签
color = titleNames[4] # 图例标题
)+
# scale_x_date(
# date_labels = "%Y-%m-%d", # 格式符组合
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
# )+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 10,face = "bold"),
axis.title.y = element_text(size = 10,face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90),
legend.position = "right")+guides(color = "none")
# plot2
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
pointPlotfunction项目Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(项目名称)))+
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
labs(
title = titleNames[1], # 主标题
x = titleNames[2], # X轴标签
y = titleNames[3], # Y轴标签
color = titleNames[4] # 图例标题
)+
# scale_x_date(
# date_labels = "%Y-%m-%d", # 格式符组合
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
# )+
scale_y_log10()+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 10,face = "bold"),
axis.title.y = element_text(size = 10,face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90),
legend.position = "right")+guides(color = "none")
# plot2
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
plotfunctionByDay<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = testDay, y = Count, text = paste( round(Count, 2)) ,fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
# plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
plotfunctionBy区域<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = 省编号, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
#plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
plotfunctionBy仪器<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = 仪器序列号, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
#plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
plotfunctionBy仪器Log<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
plot1<-ggplot(dfData00, aes(x = 仪器序列号, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
scale_y_log10()+
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
legend.position = "right")+guides(color = "none")
#plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
#return (list(plotdfDataNumber,b23,b33,b43,b53))
}
panelPlotByDayAnd仪器<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
dfData00<-dfData00[dfData00$仪器序列号 %in% choosenList,]
dfData00$仪器序列号<-factor(dfData00$仪器序列号,levels = choosenList)
plot1<-ggplot(dfData00, aes(x = testDay, y = Count, text = paste( round(Count, 2)) ,fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
facet_wrap( ~ 仪器序列号,ncol=2) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
panel.border = element_rect(
color = "black", # 边框颜色
linewidth = 1., # 边框粗细
linetype = "solid", # 线型（solid/dashed/dotted）
fill = NA # 填充色（NA为透明）
),
legend.position = "right")+guides(color = "none")
#plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
panelPlotByMonthAnd仪器<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
dfData00<-dfData00[dfData00$仪器序列号 %in% choosenList,]
dfData00$仪器序列号<-factor(dfData00$仪器序列号,levels = choosenList)
plot1<-ggplot(dfData00, aes(x = testMonth, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
facet_wrap( ~ 仪器序列号,ncol=2) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
panel.border = element_rect(
color = "black", # 边框颜色
linewidth = 1., # 边框粗细
linetype = "solid", # 线型（solid/dashed/dotted）
fill = NA # 填充色（NA为透明）
),
legend.position = "right")+guides(color = "none")
#plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
panelPlotByDayAnd仪器<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
dfData00<-dfData00[dfData00$仪器序列号 %in% choosenList,]
dfData00$仪器序列号<-factor(dfData00$仪器序列号,levels = choosenList)
plot1<-ggplot(dfData00, aes(x = testDay, y = Count, text = paste( round(Count, 2)) ,fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
facet_wrap( ~ 仪器序列号,ncol=2) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
panel.border = element_rect(
color = "black", # 边框颜色
linewidth = 1., # 边框粗细
linetype = "solid", # 线型（solid/dashed/dotted）
fill = NA # 填充色（NA为透明）
),
legend.position = "right")+guides(color = "none")
#plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
panelPlotByMonthAnd仪器<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
lth1<-length(dependentVariableNames)
dfData00<-data.frame()
for(i in 1:lth1){
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
dfData00<-rbind(dfData00,dfData0)
}
dfData00<-dfData00[dfData00$仪器序列号 %in% choosenList,]
dfData00$仪器序列号<-factor(dfData00$仪器序列号,levels = choosenList)
plot1<-ggplot(dfData00, aes(x = testMonth, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
geom_col(
position = position_dodge(width = 0.4), # 控制条间距
width = 0.7 # 条宽度
) +
geom_line(
aes(group = Group, color = Group),
position = position_dodge(width = 0.4),
linewidth = 1,
linetype="dashed",
show.legend=FALSE,
alpha = 1.0
) +
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
# geom_text(
# aes(label = round(Count,2)), # 标签内容
# position = position_dodge(width = 0.4), # 与柱子位置一致
# vjust = -0.4, # 垂直位置（负值向上）
# color = "black", # 标签颜色
# size = 1.2 # 字体大小
# ) +
facet_wrap( ~ 仪器序列号,ncol=2) +
labs(
title = titleNames[1],
x = titleNames[2],
y = titleNames[3],
fill = titleNames[4]
) +
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
theme_minimal() + theme(
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
axis.title.x = element_text(size = 12, face = "bold"),
axis.title.y = element_text(size = 12, face = "bold"),
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
panel.border = element_rect(
color = "black", # 边框颜色
linewidth = 1., # 边框粗细
linetype = "solid", # 线型（solid/dashed/dotted）
fill = NA # 填充色（NA为透明）
),
legend.position = "right")+guides(color = "none")
#plot1
# Convert to interactive plot
plot1<-ggplotly(plot1, tooltip = "text")
return (plot1)
}
running_avg <- function(x, window = 3) {
sapply(seq_along(x), function(i) {
start <- max(1, i - window + 1)
mean(x[start:i],na.rm=TRUE)
})
}
lumping_avg<- function(x,window = 100) {
sapply(seq_along(x), function(i) {
start <- max(1, i - window + 1)
mean(x[start:i],na.rm=TRUE)
})
}
lumping_sd<- function(x,window = 100) {
sapply(seq_along(x), function(i) {
start <- max(1, i - window + 1)
sd(x[start:i],na.rm=TRUE)
})
}
rep6<-rep(1,6)
rep50<-rep(1,50)
rep0<-rep6
for(i in 1:1000) rep0<-c(rep0,rep6+i)
rep00<-rep50
for(i in 1:100) rep00<-c(rep00,rep50+i)
if(FALSE){
csv_files <- list.files(pattern = "\\UTF.csv$")
df00<-data.frame()
for(i in 1:length(csv_files)) {
#guess_encoding("historyRecord20.csv") # [[1]]$encoding
#df2 <- fread("historyRecord20250604175205UTF.csv",encoding = "UTF-8",fill = TRUE)
# df22 <- read.csv(csv_files[i],encoding = "UTF-8",fill = TRUE)
# colnames(df22)
# summary(df22)
df2 <- read.csv(csv_files[i],encoding = "UTF-8",fill = TRUE)
df2$批次名称<-as.character(df2$批次名称)
df2<-df2[!is.na(df2$批次名称),]
df2$是否阳性<-df2$结论
df2$是否阳性[df2$是否阳性=="阳性"]<-1.0
df2$是否阳性[df2$是否阳性=="阴性"]<-0.0
df2$是否阳性[df2$是否阳性=="无效"]<-0.5
df2$是否阳性<-as.numeric(df2$是否阳性)
df2$是否阳性[is.na(df2$是否阳性)]<-0.5
df2$结论[df2$结论=="阳性"]<-1.0
df2$结论[df2$结论=="阴性"]<-0.0
df2$结论<-as.numeric(df2$结论)
df2$是否有效<-1
df2$是否有效[df2$是否阳性==0.5]<-0
df00<-rbind(df00,df2)
}
write_excel_csv(df00,file="history06092025.csv")
df2<-df00
}
if(FALSE){
series<-read.csv("荧光层析设备1.csv",encoding = "UTF-8",fill = TRUE)
series1<-read.csv("FIC-Q100N.csv",encoding = "UTF-8",fill = TRUE)
series0<-series$仪器序列号[series$仪器序列号 %in% 仪器号List$仪器序列号]
series00<-series$仪器编号[series$仪器编号 %in% series1$仪器编号]
colnames(series[,1:13])
colnames(series1[,3:11])
仪器编号和序列号<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=FALSE)
#仪器编号和序列号all<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=TRUE)
colnames(仪器编号和序列号)
仪器编号和序列号$SIM卡号<- gsub("\t", " ", 仪器编号和序列号$SIM卡号)
仪器编号和序列号$返利表序号<- gsub("\n", "_", 仪器编号和序列号$返利表序号)
#仪器编号和序列号all$SIM卡号<- gsub("\t", " ", 仪器编号和序列号all$SIM卡号)
#仪器编号和序列号all$返利表序号<- gsub("\n", "_", 仪器编号和序列号all$返利表序号)
#仪器编号和序列号[仪器编号和序列号$仪器序列号=="781be43bb68f05bb",]
cname0<-c("仪器编号" , "仪器序列号" ,
"SIM卡号" , "发货时间" , "仪器类型" ,
"总测试量" , "最后一次开机时间" ,"时间差" ,
"开机地点" , "网络类型" , "ip地址" ,
"用户" , "用户CRM" , "返利表序号" ,
"申请日期" , "区域" , "客户编码" ,
"代理商名称" , "用户名称" , "规格" ,
"状态")
#write_excel_csv(仪器编号和序列号all[,cname0],file="仪器编号和序列号all.csv")
write_excel_csv(仪器编号和序列号[,cname0],file="仪器编号和序列号.csv")
}
if(FALSE){
series<-read.csv("荧光层析设备1.csv",encoding = "UTF-8",fill = TRUE)
series1<-read.csv("FIC-Q100N20250710.csv",encoding = "UTF-8",fill = TRUE)
series0<-series$仪器序列号[series$仪器序列号 %in% 仪器号List$仪器序列号]
series00<-series$仪器编号[series$仪器编号 %in% series1$仪器编号]
colnames(series)[1:13]
colnames(series1)[3:11]
仪器编号和序列号0<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=FALSE)
仪器编号和序列号1<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=TRUE)
仪器编号和序列号2<-merge(series[,1:13],series1[,3:11],by="仪器编号",all.y=TRUE,all.x=FALSE)
unique编号1<-unique(仪器编号和序列号1$仪器编号)
unique序列号1<-unique(仪器编号和序列号1$仪器序列号)
unique编号2<-unique(仪器编号和序列号2$仪器编号)
unique序列号2<-unique(仪器编号和序列号2$仪器序列号)
#仪器编号和序列号all<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=TRUE)
colnames(仪器编号和序列号1)
仪器编号和序列号0$SIM卡号<- gsub("\t", " ", 仪器编号和序列号0$SIM卡号)
仪器编号和序列号0$返利表序号<- gsub("\n", "_", 仪器编号和序列号0$返利表序号)
仪器编号和序列号1$SIM卡号<- gsub("\t", " ", 仪器编号和序列号1$SIM卡号)
仪器编号和序列号1$返利表序号<- gsub("\n", "_", 仪器编号和序列号1$返利表序号)
#仪器编号和序列号all$SIM卡号<- gsub("\t", " ", 仪器编号和序列号all$SIM卡号)
#仪器编号和序列号all$返利表序号<- gsub("\n", "_", 仪器编号和序列号all$返利表序号)
#仪器编号和序列号[仪器编号和序列号$仪器序列号=="781be43bb68f05bb",]
仪器编号和序列号1e<-仪器编号和序列号1[complete.cases(仪器编号和序列号1$区域),]
cname0<-c("仪器编号" , "仪器序列号" ,
"SIM卡号" , "发货时间" , "仪器类型" ,
"总测试量" , "最后一次开机时间" ,"时间差" ,
"开机地点" , "网络类型" , "ip地址" ,
"用户" , "用户CRM" , "返利表序号" ,
"申请日期" , "区域" , "客户编码" ,
"代理商名称" , "用户名称" , "规格" ,
"状态")
#write_excel_csv(仪器编号和序列号all[,cname0],file="仪器编号和序列号all.csv")
write_excel_csv(仪器编号和序列号1[,cname0],file="仪器编号和序列号1.csv")
mydb = dbConnect(MySQL(), user='root', password='My9521$$', dbname='和迈', host='192.168.11.223')
dbWriteTable(mydb, name='仪器编号和序列号1', value=仪器编号和序列号1)
dbDisconnect(mydb)
write_excel_csv(仪器编号和序列号1e[,cname0],file="仪器编号和序列号1e.csv")
mydb = dbConnect(MySQL(), user='root', password='My9521$$', dbname='和迈', host='192.168.11.223')
dbWriteTable(mydb, name='仪器编号和序列号1e', value=仪器编号和序列号1e)
dbDisconnect(mydb)
Numberof区域<-length(unique(仪器编号和序列号1e$区域))
listOfUnique细胞<-""
for(j in 1:Numberof区域) listOfUnique细胞<-paste(listOfUnique细胞,unique(仪器编号和序列号1e$区域)[j],sep="___")
细胞<-data.frame(cbind(1:Numberof区域,unique(df2andInf$区域)))
colnames(细胞)<-c("ID","细胞")
write_excel_csv(细胞,file="细胞.csv")
细胞1<-细胞[str_length(细胞$细胞)<=3,]
similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[3],sep=""),"%",sep=""), ignore_case = TRUE)
细胞$细胞[30]
细胞$细胞[43]
细胞$细胞[30]<-细胞$细胞[43]
similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[4],sep=""),"%",sep=""), ignore_case = TRUE)
细胞$细胞[9]
细胞$细胞[45]
细胞$细胞[45]<-细胞$细胞[9]
similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[5],sep=""),"%",sep=""), ignore_case = TRUE)
细胞$细胞[17]
细胞$细胞[46]
细胞$细胞[46]<-细胞$细胞[17]
similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[6],sep=""),"%",sep=""), ignore_case = TRUE)
细胞$细胞[11]
细胞$细胞[47]
细胞$细胞[47]<-细胞$细胞[11]
similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[7],sep=""),"%",sep=""), ignore_case = TRUE)
细胞$细胞[14]
细胞$细胞[54]
细胞$细胞[54]<-细胞$细胞[14]
similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[8],sep=""),"%",sep=""), ignore_case = TRUE)
细胞$细胞[63]
细胞$细胞[34]
细胞$细胞[63]<-细胞$细胞[34]
unique(细胞$细胞)
仪器编号和序列号1m<-仪器编号和序列号1e
仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[3],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[43]
仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[4],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[9]
仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[5],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[17]
仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[6],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[11]
仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[7],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[14]
仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[8],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[34]
仪器编号和序列号$小细胞[str_like(仪器编号和序列号$小细胞,paste(paste("%","陈凯 华中",sep=""),"%",sep=""), ignore_case = TRUE)]<-"华中 陈凯"
unique(仪器编号和序列号$小细胞)
write_excel_csv(仪器编号和序列号1m[,cname0],file="仪器编号和序列号1m.csv")
mydb = dbConnect(MySQL(), user='root', password='My9521$$', dbname='和迈', host='192.168.11.223')
dbWriteTable(mydb, name='仪器编号和序列号1m', value=仪器编号和序列号[,2:22])
dbDisconnect(mydb)
Numberof区域<-length(unique(仪器编号和序列号1m$小细胞))
listOfUnique细胞<-""
for(j in 1:Numberof区域) listOfUnique细胞<-paste(listOfUnique细胞,unique(仪器编号和序列号1m$小细胞)[j],sep="___")
细胞m<-data.frame(cbind(1:Numberof区域,unique(df2andInf$小细胞)))
colnames(细胞m)<-c("ID","细胞")
write_excel_csv(细胞m,file="细胞m.csv")
}
mydb = dbConnect(MySQL(), user='root', password='My9521$$', dbname='和迈', host='192.168.11.223')
dbListTables(mydb)
#dbListFields(mydb, '测试数据')
#仪器编号和序列号all<-read.csv("仪器编号和序列号all.csv",encoding = "UTF-8",fill = TRUE)
#仪器编号和序列号<-read.csv("仪器编号和序列号.csv",encoding = "UTF-8",fill = TRUE)
rs = dbSendQuery(mydb, "select * from 和迈.仪器编号和序列号1m ")
仪器编号和序列号 = fetch(rs, n=-1)
仪器编号和序列号<-仪器编号和序列号[!duplicated(仪器编号和序列号[,c("仪器编号","仪器序列号" )]),]
colnames(仪器编号和序列号)
#仪器编号和序列号<-distinct(仪器编号和序列号[,2:22])
#仪器编号和序列号<-read.csv("仪器编号和序列号.csv",encoding = "UTF-8",fill = TRUE)
rs = dbSendQuery(mydb, "select * from 和迈.和迈测试数据 ")
df2 = fetch(rs, n=-1)
dbDisconnect(mydb)
#df2 = fetch(rs, n=-1)
#df2 <- read.csv("history06092025.csv",encoding = "UTF-8",fill = TRUE)
colnames(df2)
cname00<-c( "序号" , "项目号" , "批次号" , "样品编号" ,
"项目名称" , "批次名称" , "测试时间" , "浓度1" ,
"结论" , "C值" , "T值" , "浓度2" ,
"浓度3" , "结论2" , "结论3" , "样本类型" ,
"省市编号" , "仪器序列号" , "T2值" , "T3值" ,
"仪器备注名称", "仪器投放区域", "详细地址")
df2<-distinct(df2[,cname00])
df2$批次名称<-as.character(df2$批次名称)
df2<-df2[!is.na(df2$批次名称),]
df2andInf<-merge(df2,仪器编号和序列号[,c("仪器编号","仪器序列号","发货时间" ,"申请日期" ,
"小细胞" , "客户编码" , "代理商名称" ,
"用户名称" , "规格" , "状态")],by="仪器序列号",all.x=TRUE,all.y=FALSE)
df2andInf$省编号<-(df2andInf$省市编号 %/% 10000)*10000
df2andInf$省名<-str_sub(df2andInf$详细地址,1,3)
df2andInf$省名[str_length(df2andInf$省名)<3]<-NA
df2andInf$省名[str_like(df2andInf$省编号,paste(paste("%","120000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"天津市"
df2andInf$省名[str_like(df2andInf$省编号,paste(paste("%","230000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"黑龙江"
df2andInf$省名[str_like(df2andInf$省编号,paste(paste("%","320000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"江苏省"
df2andInf$省名[str_like(df2andInf$省编号,paste(paste("%","420000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"湖北省"
df2andInf$省名[str_like(df2andInf$省编号,paste(paste("%","510000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"四川省"
df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","重庆市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"500000"
df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","广西壮",sep=""),"%",sep=""), ignore_case = TRUE)]<-"450000"
df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","江西省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"360000"
df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","北京市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"110000"
df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","河北省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"130000"
df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","上海市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"310000"
df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","浙江省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"330000"
df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","四川省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"510000"
df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","安徽省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"340000"
df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","贵州省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"520000"
df2andInf<-distinct(df2andInf)
#df2andInf0<-df2andInf[str_c(df2andInf$仪器编号, df2andInf$仪器序列号)!=NA,]
df2andInf$是否阳性<-df2andInf$结论
df2andInf$是否阳性[df2andInf$是否阳性=="阳性"]<-1.0
df2andInf$是否阳性[df2andInf$是否阳性=="阴性"]<-0.0
df2andInf$是否阳性[df2andInf$是否阳性=="无效"]<-0.5
df2andInf$是否阳性<-as.numeric(df2andInf$是否阳性)
df2andInf$是否阳性[is.na(df2andInf$是否阳性)]<-0.5
df2andInf$结论[df2andInf$结论=="阳性"]<-1.0
df2andInf$结论[df2andInf$结论=="阴性"]<-0.0
df2andInf$结论<-as.numeric(df2andInf$结论)
df2andInf$是否有效<-1
df2andInf$是否有效[df2andInf$是否阳性==0.5]<-0
Numberof项目号<-length(unique(df2andInf$项目号))
Numberof批次号<-length(unique(df2andInf$批次号))
Numberof样品编号<-length(unique(df2andInf$样品编号))
Numberof项目名称<-length(unique(df2andInf$项目名称))
Numberof批次名称<-length(unique(df2andInf$批次名称))
Numberof省编号<-length(unique(df2andInf$省编号))
Numberof省名<-length(unique(df2andInf$省名))
Numberof省市编号<-length(unique(df2andInf$省市编号))
Numberof仪器序列号<-length(unique(df2andInf$仪器序列号))
Numberof详细地址<-length(unique(df2andInf$详细地址))
Numberof小细胞<-length(unique(df2andInf$小细胞))
Numberof仪器备注名称<-length(unique(df2andInf$仪器备注名称))
Numberof仪器投放区域<-length(unique(df2andInf$仪器投放区域))
Numberof样本类型<-length(unique(df2andInf$样本类型))
if(FALSE){
省编号and省名<-data.frame(cbind(df2andInf$省编号,df2andInf$省名))
colnames(省编号and省名)<-c("省编号","省名")
省编号and省名<-省编号and省名[!duplicated(省编号and省名),]
省编号and省名<-省编号and省名[order(省编号and省名$省编号),]
省编号and省名$省名[str_like(省编号and省名$省编号,paste(paste("%","120000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"天津市"
省编号and省名$省名[str_like(省编号and省名$省编号,paste(paste("%","230000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"黑龙江"
省编号and省名$省名[str_like(省编号and省名$省编号,paste(paste("%","320000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"江苏省"
省编号and省名$省名[str_like(省编号and省名$省编号,paste(paste("%","420000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"湖北省"
省编号and省名$省名[str_like(省编号and省名$省编号,paste(paste("%","510000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"四川省"
省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","重庆市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"500000"
省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","广西壮",sep=""),"%",sep=""), ignore_case = TRUE)]<-"450000"
省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","江西省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"360000"
省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","北京市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"110000"
省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","河北省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"130000"
省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","上海市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"310000"
省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","浙江省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"330000"
省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","四川省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"510000"
省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","安徽省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"340000"
省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","贵州省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"520000"
省编号and省名<-省编号and省名[!duplicated(省编号and省名),]
}
summaryTable<-stri_join("Numberof测试: ",as.character(nrow(df2andInf)),
"\nNumberof项目名称: ", as.character(Numberof项目名称),
"\nNumberof批次号: ",as.character(Numberof批次号), " \n",
"Numberof样品编号： ",as.character(Numberof样品编号)," \n",
"Numberof批次名称: ",as.character(Numberof批次名称)," \n",
"Numberof省编号: ",as.character(Numberof省编号)," \n",
"Numberof省市编号: ",as.character(Numberof省市编号)," \n",
"Numberof仪器序列号: ",as.character(Numberof仪器序列号)," \n",
"Numberof详细地址: ",as.character(Numberof详细地址)," \n",
"Numberof小细胞: ",as.character(Numberof小细胞)," \n",
"Numberof样本类型: ",as.character(Numberof样本类型)," \n",sep="")
小细胞<-unique(df2andInf$小细胞)
Numberof小细胞<-length(小细胞)
细胞<-data.frame(cbind(1:Numberof小细胞,小细胞))
colnames(细胞)<-c("ID","细胞")
细胞0<-细胞[!(str_like(细胞$细胞,paste(paste("%","内部",sep=""),"%",sep=""), ignore_case = TRUE) |
str_like(细胞$细胞,paste(paste("%","客服",sep=""),"%",sep=""), ignore_case = TRUE) |
str_like(细胞$细胞,paste(paste("%","医学",sep=""),"%",sep=""), ignore_case = TRUE) ),]
细胞0<-细胞0[!is.na(细胞0$细胞),]
细胞0$ID<-1:nrow(细胞0)
write_excel_csv(细胞0,file="细胞0.csv")
summary(df2andInf$结论)
summary(df2andInf$是否阳性)
summary(df2andInf$是否有效)
#df2andInf$仪器序列号_批次名称<-str_c(df2andInf$仪器序列号,'_',df2andInf$批次名称)
colnames(df2andInf)
#colnames(df00)
#df2andInf00<-df2andInf0
summary(df2andInf$仪器序列号)
summary(df2andInf$批次名称)
df20<-df2andInf #[,c(1:11,16,17,20)]
df20$省编号<-str_c("省编号: ",df20$省编号)
df20<-df20[complete.cases(df20$测试时间), ]
df20<-df20[str_length(df20$测试时间)>10, ]
colnames(df20)
df20$浓度1<-as.numeric(df20$浓度1)
df20$C值<-as.numeric(df20$C值)
df20$T值<-as.numeric(df20$T值)
df20$ToverC值<-df20$T值/df20$C值
df20$ToverC值[df20$是否有效==0]<-NA
summary(as.numeric(df20$结论))
summary(df20$浓度1)
summary(df20$ToverC值)
summary(df20$testTimeFromeBegining)
colnames(df20)
df20$testMonth<-str_sub(df20$测试时间,1,7)
#df20$testMonthinNumber<-as.numeric(str_c(str_sub(df20$测试时间,1,4),str_sub(df20$测试时间,6,7)))
df20$testDay<-as.Date(str_sub(df20$测试时间,1,10))
df20<-df20[df20$testDay<="2025-06-05", ]
#df20<-df20[df20$testDay<=Sys.Date(), ]
df20<-df20[complete.cases(df20$testDay), ]
summary(df20$testDay)
df20$testTime<-as.datetime(str_sub(df20$测试时间,1,19),format='%Y-%m-%d %H:%M:%S')
duration<-(max(df20$testTime,na.rm = TRUE)-min(df20$testTime,na.rm = TRUE))/(60.*60.*24.)
df20$testTimeFromeToday<-(max(df20$testTime,na.rm = TRUE)-df20$testTime)/(60.*60.*24.)+1.
#max0<-max(df20$testTime,na.rm=TRUE)
#min0<-min(df20$testTime,na.rm=TRUE)
#unique(dfBy样本$样本类型)
#max0-min0
#max(df20$testDay,na.rm=TRUE)
#min(df20$testDay,na.rm=TRUE)
#clean_df <- df20[complete.cases(df20[,c("小细胞")]), ]
#summary(clean_df)
summary(df20$testTimeFromeToday)
dayMax<-max(df20$testTimeFromeToday,na.rm = TRUE)
df2000<-df20
df20<-df20[df20$testTimeFromeToday<=730,]
#df20<-df20[complete.cases(df20$测试时间), ]
lastDay<-max(df20$testDay,na.rm = TRUE)
df20dayLast21<-df20[lastDay-df20$testDay<21,]
dfByDay <- df2000 %>% group_by(testMonth,testDay) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号))
)
dfByDay$阳性率<-round(dfByDay$阳性数/dfByDay$有效数,3)
dfByDay$有效率<-round(dfByDay$有效数/dfByDay$测试数,3)
dfByDay$阳性数<-as.integer(dfByDay$阳性数)
dfByDay$测试数<-as.integer(dfByDay$测试数)
dfByDay$有效数<-as.integer(dfByDay$有效数)
dfByDay$省数<-as.integer(dfByDay$省数)
dfByDay <- dfByDay[order(lastDay-dfByDay$testDay),]
#dfByDay <- dfByDay[lastDay-dfByDay$testDay<42,]
#dfByDay<-dfByDay[lastDay-dfByDay$testDay<=21,]
write_excel_csv(dfByDay,file="按日统计0.csv")
dfByMonth <- df2000 %>% group_by(testMonth) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号))
)
dfByMonth$阳性率<-round(dfByMonth$阳性数/dfByMonth$有效数,3)
dfByMonth$有效率<-round(dfByMonth$有效数/dfByMonth$测试数,3)
dfByMonth$阳性数<-as.integer(dfByMonth$阳性数)
dfByMonth$测试数<-as.integer(dfByMonth$测试数)
dfByMonth$有效数<-as.integer(dfByMonth$有效数)
dfByMonth$省数<-as.integer(dfByMonth$省数)
dfByMonth <- dfByMonth[order(dfByMonth$testMonth),]
dfByMonth <- dfByMonth[nrow(dfByMonth):1,]
write_excel_csv(dfByMonth,file="按月统计0.csv")
dfBy项目 <- df2000 %>% group_by(项目名称) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号)),
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
)
dfBy项目$阳性率<-round(dfBy项目$阳性数/dfBy项目$有效数,3)
dfBy项目$有效率<-round(dfBy项目$有效数/dfBy项目$测试数,3)
dfBy项目$阳性数<-as.integer(dfBy项目$阳性数)
dfBy项目$测试数<-as.integer(dfBy项目$测试数)
dfBy项目$有效数<-as.integer(dfBy项目$有效数)
dfBy项目 <- dfBy项目[order(-dfBy项目$测试数),]
write_excel_csv(dfBy项目,file="按项目统计0.csv")
dfBy样本 <- df2000 %>% group_by(样本类型) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号)),
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
)
dfBy样本$阳性率<-round(dfBy样本$阳性数/dfBy样本$有效数,3)
dfBy样本$有效率<-round(dfBy样本$有效数/dfBy样本$测试数,3)
dfBy样本$阳性数<-as.integer(dfBy样本$阳性数)
dfBy样本$测试数<-as.integer(dfBy样本$测试数)
dfBy样本$有效数<-as.integer(dfBy样本$有效数)
dfBy样本 <- dfBy样本[order(-dfBy样本$测试数),]
write_excel_csv(dfBy样本,file="按样本统计0.csv")
dfBy细胞 <- df2000 %>% group_by(小细胞) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号)),
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
)
dfBy细胞$阳性率<-round(dfBy细胞$阳性数/dfBy细胞$有效数,3)
dfBy细胞$有效率<-round(dfBy细胞$有效数/dfBy细胞$测试数,3)
dfBy细胞$阳性数<-as.integer(dfBy细胞$阳性数)
dfBy细胞$测试数<-as.integer(dfBy细胞$测试数)
dfBy细胞$有效数<-as.integer(dfBy细胞$有效数)
dfBy细胞 <- dfBy细胞[order(-dfBy细胞$测试数),]
write_excel_csv(dfBy细胞,file="按细胞统计0.csv")
dfBy区域 <- df2000 %>% group_by(省编号) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号)),
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
)
dfBy区域$阳性率<-round(dfBy区域$阳性数/dfBy区域$有效数,3)
dfBy区域$有效率<-round(dfBy区域$有效数/dfBy区域$测试数,3)
dfBy区域$阳性数<-as.integer(dfBy区域$阳性数)
dfBy区域$测试数<-as.integer(dfBy区域$测试数)
dfBy区域$有效数<-as.integer(dfBy区域$有效数)
dfBy区域 <- dfBy区域[order(-dfBy区域$测试数),]
write_excel_csv(dfBy区域,file="按区域统计0.csv")
省编号<-dfBy区域$省编号
省编号0<-省编号[str_length(省编号)>8]
dfBy区域<-dfBy区域[dfBy区域$省编号 %in% 省编号0,]
dfBy批次 <- df2000 %>% group_by(批次名称) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号)),
最早测试=min(testDay,na.rm = TRUE),
最近测试=max(testDay,na.rm = TRUE),
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
)
dfBy批次$阳性率<-round(dfBy批次$阳性数/dfBy批次$有效数,3)
dfBy批次$有效率<-round(dfBy批次$有效数/dfBy批次$测试数,3)
dfBy批次$阳性数<-as.integer(dfBy批次$阳性数)
dfBy批次$测试数<-as.integer(dfBy批次$测试数)
dfBy批次$有效数<-as.integer(dfBy批次$有效数)
dfBy批次$省数<-as.integer(dfBy批次$省数)
dfBy批次 <- dfBy批次[order(-dfBy批次$测试数),]
write_excel_csv(dfBy批次,file="按批次统计0.csv")
df20001<-cbind(df2000,IDIndex=1:nrow(df2000))
dfBy仪器 <- df20001 %>% group_by(仪器序列号) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号)),
earliestIndex=min(IDIndex),
medianIndex=median(IDIndex),
latestIndex=max(IDIndex),
最早测试=min(testDay,na.rm = TRUE),
最近测试=max(testDay,na.rm = TRUE),
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
)
dfBy仪器$阳性率<-round(dfBy仪器$阳性数/dfBy仪器$有效数,3)
dfBy仪器$有效率<-round(dfBy仪器$有效数/dfBy仪器$测试数,3)
dfBy仪器$阳性数<-as.integer(dfBy仪器$阳性数)
dfBy仪器$测试数<-as.integer(dfBy仪器$测试数)
dfBy仪器$有效数<-as.integer(dfBy仪器$有效数)
dfBy仪器$最早测试地点<-df2000$详细地址[dfBy仪器$earliestIndex]
dfBy仪器$中期测试地点<-df2000$详细地址[dfBy仪器$medianIndex]
dfBy仪器$最后测试地点<-df2000$详细地址[dfBy仪器$latestIndex]
dfBy仪器 <- dfBy仪器[order(-dfBy仪器$测试数),]
cname0<-c( "仪器序列号" ,"最早测试地点","中期测试地点", "最后测试地点",
"批次数" , "测试数" , "样本数" , "项目数" ,
"阳性数", "有效数" , "最早测试" , "最近测试" , "测试开始" ,
"测试截止", "阳性率" , "有效率")
write_excel_csv(dfBy仪器[,cname0],file="按仪器统计0.csv")
cname0<-c( "仪器序列号" ,"仪器编号" ,"最早测试地点","中期测试地点", "最后测试地点",
"开机地点" , "批次数" , "测试数" , "样本数" , "项目数" ,
"阳性数", "有效数" , "最早测试" , "最近测试" , "测试开始" ,
"测试截止", "阳性率" , "有效率",
"SIM卡号" , "发货时间" , "仪器类型" ,
"总测试量" , "最后一次开机时间" ,"时间差" ,
"网络类型" , "ip地址" ,
"用户" , "用户CRM" , "返利表序号" ,
"申请日期" , "小细胞" , "客户编码" ,
"代理商名称" , "用户名称" , "规格" ,
"状态")
colnames(dfBy仪器)
dfBy仪器andInf<-merge(dfBy仪器,仪器编号和序列号,by="仪器序列号",all.x=TRUE,all.y=FALSE)
colnames(dfBy仪器andInf)
dfBy仪器andInf <- dfBy仪器andInf[order(-dfBy仪器andInf$测试截止),][,cname0]
#dfBy仪器andInf0<-distinct(dfBy仪器andInf)
write_excel_csv(dfBy仪器andInf,file="仪器统计andInf.csv")
dfBy仪器andInfall<-merge(dfBy仪器,仪器编号和序列号,by="仪器序列号",all.x=TRUE,all.y=TRUE)
dfBy仪器andInfall <- dfBy仪器andInfall[order(-dfBy仪器andInfall$测试截止),][,cname0]
#dfBy仪器andInfall0<-distinct(dfBy仪器andInfall)
write_excel_csv(dfBy仪器andInfall,file="仪器统计andInfall.csv")
colnames(仪器编号和序列号)
notFound<-仪器编号和序列号[!(仪器编号和序列号$仪器序列号 %in% dfBy仪器$仪器序列号),]
colnames(notFound)
cname1<-c( "仪器序列号" ,"仪器编号" ,
"开机地点" ,
"SIM卡号" , "发货时间" , "仪器类型" ,
"总测试量" , "最后一次开机时间" ,"时间差" ,
"网络类型" , "ip地址" ,
"用户" , "用户CRM" , "返利表序号" ,
"申请日期" , "小细胞" , "客户编码" ,
"代理商名称" , "用户名称" , "规格" ,
"状态")
#notFound[,cname1]
#notFound0<-distinct(notFound)
write_excel_csv(notFound[,cname1],file="仪器统计Notfound.csv")
if(FALSE) {
CRMNotFound <- read.csv("CRMNotFound.csv",encoding = "UTF-8",fill = TRUE)
NoTestSince05012025 <- read.csv("NoTestSince05012025.csv",encoding = "UTF-8",fill = TRUE)
colnames(CRMNotFound)[c(3,4,5)]<-c("销售申请时间NoCRM","销售申请区域NoCRM","销售申请时代理商名称NoCRM")
colnames(NoTestSince05012025) [9]<-"备注NoTest"
feedbackData<-merge(CRMNotFound,NoTestSince05012025,by="仪器编号",all.x=TRUE,all.y=TRUE)
colnames(feedbackData)
colnames(feedbackData)[10]<-"用户onCRM"
write_excel_csv(feedbackData,file="feedbackData07042025.csv")
仪器编号和序列号feedbackData<-merge(仪器编号和序列号,feedbackData,by="仪器编号",all.x=TRUE,all.y=TRUE)
colnames(仪器编号和序列号feedbackData)
dfBy仪器feedbackDataandInf<-merge(dfBy仪器,仪器编号和序列号feedbackData,by="仪器序列号",all.x=TRUE,all.y=FALSE)
colnames(dfBy仪器feedbackDataandInf)
cname0<-c( "仪器序列号" ,"仪器编号" ,"最早测试地点","中期测试地点", "最后测试地点",
"开机地点" , "批次数" , "测试数" , "样本数" , "项目数" ,
"阳性数", "有效数" , "最早测试" , "最近测试" , "测试开始" ,
"测试截止", "阳性率" , "有效率",
"SIM卡号" , "发货时间" , "仪器类型" ,
"总测试量" , "最后一次开机时间" ,"时间差" ,
"网络类型" , "ip地址" ,
"用户" , "用户CRM" , "返利表序号" ,
"申请日期" , "小细胞" , "客户编码" ,
"代理商名称" , "用户名称" , "规格" ,
"状态","销售申请时间" , "销售申请时间NoCRM" ,
"销售申请区域NoCRM" , "销售申请时代理商名称NoCRM",
"是否装机" , "未装机原因" ,
"备注" , "最后测试时间" ,
"用户onCRM" , "销售申请日期" ,
"销售申请区域" , "销售申请时代理商名称" ,
"销售申请时用户名称" , "无测试原因" ,
"备注NoTest" )
dfBy仪器feedbackDataandInf <- dfBy仪器feedbackDataandInf[order(-dfBy仪器feedbackDataandInf$测试截止),][,cname0]
write_excel_csv(dfBy仪器feedbackDataandInf,file="仪器统计feedbackandInf.csv")
dfBy仪器feedbackDataandInfall<-merge(dfBy仪器,仪器编号和序列号feedbackData,by="仪器序列号",all.x=TRUE,all.y=TRUE)
dfBy仪器feedbackDataandInfall <- dfBy仪器feedbackDataandInfall[order(-dfBy仪器feedbackDataandInfall$测试截止),][,cname0]
write_excel_csv(dfBy仪器feedbackDataandInfall,file="仪器统计feedbackandInfall.csv")
colnames(仪器编号和序列号feedbackData)
notFoundfeedBack<-仪器编号和序列号feedbackData[!(仪器编号和序列号feedbackData$仪器序列号 %in% dfBy仪器$仪器序列号),]
cname1<-c( "仪器序列号" ,"仪器编号" ,
"开机地点" ,
"SIM卡号" , "发货时间" , "仪器类型" ,
"总测试量" , "最后一次开机时间" ,"时间差" ,
"网络类型" , "ip地址" ,
"用户" , "用户CRM" , "返利表序号" ,
"申请日期" , "小细胞" , "客户编码" ,
"代理商名称" , "用户名称" , "规格" ,
"状态","销售申请时间" , "销售申请时间NoCRM" ,
"销售申请区域NoCRM" , "销售申请时代理商名称NoCRM",
"是否装机" , "未装机原因" ,
"备注" , "最后测试时间" ,
"用户onCRM" , "销售申请日期" ,
"销售申请区域" , "销售申请时代理商名称" ,
"销售申请时用户名称" , "无测试原因" ,
"备注NoTest" )
colnames(notFoundfeedBack)
write_excel_csv(notFoundfeedBack[,cname1],file="仪器统计NotfoundfeedBack.csv")
}
dfByDayAndLocation <- df2000 %>% group_by(testDay,testMonth,省编号) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号))
)
dfByDayAndLocation$阳性率<-round(dfByDayAndLocation$阳性数/dfByDayAndLocation$有效数,3)
dfByDayAndLocation$有效率<-round(dfByDayAndLocation$有效数/dfByDayAndLocation$测试数,3)
dfByDayAndLocation$阳性数<-as.integer(dfByDayAndLocation$阳性数)
dfByDayAndLocation$测试数<-as.integer(dfByDayAndLocation$测试数)
dfByDayAndLocation$有效数<-as.integer(dfByDayAndLocation$有效数)
dfByDayAndLocation <- dfByDayAndLocation[order(dfByDayAndLocation$testDay),]
dfByDayAndLocation<-dfByDayAndLocation[dfByDayAndLocation$省编号 %in% 省编号0,]
dfByMonthAndLocation <- df20 %>% group_by(testMonth,省编号) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号))
)
dfByMonthAndLocation$阳性率<-round(dfByMonthAndLocation$阳性数/dfByMonthAndLocation$有效数,3)
dfByMonthAndLocation$有效率<-round(dfByMonthAndLocation$有效数/dfByMonthAndLocation$测试数,3)
dfByMonthAndLocation$阳性数<-as.integer(dfByMonthAndLocation$阳性数)
dfByMonthAndLocation$测试数<-as.integer(dfByMonthAndLocation$测试数)
dfByMonthAndLocation$有效数<-as.integer(dfByMonthAndLocation$有效数)
dfByMonthAndLocation <- dfByMonthAndLocation[order(dfByMonthAndLocation$testMonth),]
dfByMonthAndLocation<-dfByMonthAndLocation[dfByMonthAndLocation$省编号 %in% 省编号0,]
dfByDayAnd细胞 <- df2000 %>% group_by(testDay,testMonth,小细胞) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号))
)
dfByDayAnd细胞$阳性率<-round(dfByDayAnd细胞$阳性数/dfByDayAnd细胞$有效数,3)
dfByDayAnd细胞$有效率<-round(dfByDayAnd细胞$有效数/dfByDayAnd细胞$测试数,3)
dfByDayAnd细胞$阳性数<-as.integer(dfByDayAnd细胞$阳性数)
dfByDayAnd细胞$测试数<-as.integer(dfByDayAnd细胞$测试数)
dfByDayAnd细胞$有效数<-as.integer(dfByDayAnd细胞$有效数)
dfByDayAnd细胞 <- dfByDayAnd细胞[order(dfByDayAnd细胞$testDay),]
dfByMonthAnd细胞 <- df20 %>% group_by(testMonth,小细胞) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号))
)
dfByMonthAnd细胞$阳性率<-round(dfByMonthAnd细胞$阳性数/dfByMonthAnd细胞$有效数,3)
dfByMonthAnd细胞$有效率<-round(dfByMonthAnd细胞$有效数/dfByMonthAnd细胞$测试数,3)
dfByMonthAnd细胞$阳性数<-as.integer(dfByMonthAnd细胞$阳性数)
dfByMonthAnd细胞$测试数<-as.integer(dfByMonthAnd细胞$测试数)
dfByMonthAnd细胞$有效数<-as.integer(dfByMonthAnd细胞$有效数)
dfByMonthAnd细胞 <- dfByMonthAnd细胞[order(dfByMonthAnd细胞$testMonth),]
dfByDayAnd仪器 <- df2000 %>% group_by(testDay,testMonth,仪器序列号) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号))
)
dfByDayAnd仪器$阳性率<-round(dfByDayAnd仪器$阳性数/dfByDayAnd仪器$有效数,3)
dfByDayAnd仪器$有效率<-round(dfByDayAnd仪器$有效数/dfByDayAnd仪器$测试数,3)
dfByDayAnd仪器$阳性数<-as.integer(dfByDayAnd仪器$阳性数)
dfByDayAnd仪器$测试数<-as.integer(dfByDayAnd仪器$测试数)
dfByDayAnd仪器$有效数<-as.integer(dfByDayAnd仪器$有效数)
dfByDayAnd仪器 <- dfByDayAnd仪器[order(dfByDayAnd仪器$testDay),]
dfByMonthAnd仪器 <- df20 %>% group_by(testMonth,仪器序列号) %>% summarise(
测试数 = n(),
阳性数=sum(结论,na.rm = TRUE),
有效数=sum(是否有效,na.rm = TRUE),
样本数=length(unique(样本类型)),
项目数=length(unique(项目名称)),
仪器数=length(unique(仪器序列号)),
批次数=length(unique(批次名称)),
小细胞数=length(unique(小细胞)),
市数=length(unique(省市编号)),
省数=length(unique(省编号))
)
dfByMonthAnd仪器$阳性率<-round(dfByMonthAnd仪器$阳性数/dfByMonthAnd仪器$有效数,3)
dfByMonthAnd仪器$有效率<-round(dfByMonthAnd仪器$有效数/dfByMonthAnd仪器$测试数,3)
dfByMonthAnd仪器$阳性数<-as.integer(dfByMonthAnd仪器$阳性数)
dfByMonthAnd仪器$测试数<-as.integer(dfByMonthAnd仪器$测试数)
dfByMonthAnd仪器$有效数<-as.integer(dfByMonthAnd仪器$有效数)
dfByMonthAnd仪器 <- dfByMonthAnd仪器[order(dfByMonthAnd仪器$testMonth),]
仪器号List0<-cbind(dfBy仪器,GroupID=rep00[1:length(dfBy仪器$仪器序列号)])
仪器号List<-仪器号List0[,c(1,ncol(仪器号List0))]
仪器号ikmax<-max(仪器号List$GroupID)
dfBy仪器$仪器序列号<-factor(dfBy仪器$仪器序列号,levels = 仪器号List[,1])
批次号List0<-cbind(dfBy批次,GroupID=rep00[1:length(dfBy批次$批次名称)])
批次号List<-批次号List0[,c(1,ncol(批次号List0))]
批次号ikmax<-max(批次号List$GroupID)
dfBy批次$批次名称<-factor(dfBy批次$批次名称,levels = 批次号List[,1])
项目号List0<-cbind(dfBy项目,GroupID=rep00[1:length(dfBy项目$项目名称)])
项目号List<-项目号List0[,c(1,ncol(项目号List0))]
项目号ikmax<-max(项目号List$GroupID)
dfBy项目$项目名称<-factor(dfBy项目$项目名称,levels = 项目号List[,1])
# 图表生成函数
dfByDay1<-dfByDay[lastDay-dfByDay$testDay<42,]
dfByDayAndLocation1<-dfByDayAndLocation[lastDay-dfByDayAndLocation$testDay<42,]
dfByMonth1<-dfByMonth[1:30,]
dfByDayAnd细胞1<-dfByDayAnd细胞[lastDay-dfByDayAnd细胞$testDay<42,]
lenhalf<-length(dfBy细胞$小细胞)/2
dfBy细胞1<-dfBy细胞[dfBy细胞$小细胞 %in% dfBy细胞$小细胞[1:lenhalf],]
dfBy细胞2<-dfBy细胞[dfBy细胞$小细胞 %in% dfBy细胞$小细胞[(1+lenhalf):length(dfBy细胞$小细胞)],]
generate_data_table <- function(dim, metric) {
data <- switch(dim,
"按月统计" = read_csv("按月统计0.csv"),
"最后六周按日统计" = read_csv("按日统计0.csv"),
"按小细胞统计"=read_csv("按细胞统计0.csv"),
"按省统计" = read_csv("按区域统计0.csv"),
"按仪器统计" = read_csv("按仪器统计0.csv"),
"按样本类型统计" = read_csv("按样本统计0.csv"),
"按试剂批次统计" = read_csv("按批次统计0.csv"),
"按试剂项目统计" = read_csv("按项目统计0.csv"))
metrics <- switch(metric,
"测试数、阳性数、有效数" = c("测试数", "阳性数", "有效数"),
"阳性率、有效率" = c("阳性率", "有效率"),
"项目数、仪器数、批次数" = c("批次数", "项目数", "仪器数"),
"省数、市数、小细胞数、样本数" = c("省数", "市数", "小细胞数","样本数"),
"测试截止、测试开始" = c("测试截止", "测试开始"))
data %>% select(all_of(metrics))
}
generate_plot <- function(data, dim, metric, way, page = 1) {
max_pages <- switch(dim,
"最后六周按日统计" = {
if (way == "按日分省统计") {
ceiling(length(dfBy区域$省编号) / 6)
} else if (way == "按日分小细胞统计") {
ceiling(length(细胞0$细胞) / 6)
} else if (way == "按日分仪器统计") {
ceiling(length(仪器号List$仪器序列号) / 6)
} else 1
},
"按月统计" = {
if (way == "按月分省统计") {
ceiling(length(dfBy区域$省编号) / 6)
} else if (way == "按月分小细胞统计") {
ceiling(length(细胞0$细胞) / 6)
} else if (way == "按月分仪器统计") {
ceiling(length(仪器号List$仪器序列号) / 6)
} else 1
},
"按仪器统计" = max(仪器号List$GroupID),
"按试剂批次统计" = max(批次号List$GroupID),
"按试剂项目统计" = max(项目号List$GroupID),
"按小细胞统计" = 2,
1)
# cat(page)
per <- 6 # 每页子图数量
if(!is.numeric(page)) {
page<-1
offset<-0
} else {
if(page>max_pages) page<-max_pages
offset<- (page - 1) * per # 起始下标
}
# offset<-6
# ---- 函数内部的小工具：切片 ----
slice_vec <- function(vec, offset, per) {
vec[ (offset + 1) : min(offset + per, length(vec)) ]
}
# cat("1,", page)
# ---- 开始分发 ----
p <- switch(dim,
# ---------- 1. 最后六周按日统计 ----------
"最后六周按日统计" = {
switch(way,
"按日分省统计" = {
choosenList <- slice_vec(dfBy区域$省编号, offset, per)
if(length(choosenList) == 0) return(NULL)
switch(metric,
"测试数、阳性数、有效数" = {
panelPlotByDayAndLocation(dfByDayAndLocation1, choosenList,
"testDay", "省编号",
c("测试数","有效数","阳性数"),
c("最后六周按日分省统计","测试时间","统计数值",""))
},
"阳性率、有效率" = {
panelPlotByDayAndLocation(dfByDayAndLocation1, choosenList,
"testDay", "省编号",
c("有效率","阳性率"),
c("最后六周按日分省统计","测试时间","统计数值",""))
},
"项目数、仪器数、批次数" = {
panelPlotByDayAndLocation(dfByDayAndLocation1, choosenList,
"testDay", "省编号",
c("项目数","仪器数","批次数"),
c("最后六周按日分省统计","测试时间","统计数值",""))
},
"省数、市数、小细胞数、样本数" = {
panelPlotByDayAndLocation(dfByDayAndLocation1, choosenList,
"testDay", "省编号",
c("样本数","市数","小细胞数"),
c("最后六周按日分省统计","测试时间","统计数值",""))
}
)
},
"按日分小细胞统计" = {
choosenList <- slice_vec(细胞0$细胞, offset, per)
if(length(choosenList) == 0) return(NULL)
switch(metric,
"测试数、阳性数、有效数" = {
panelPlotByDayAnd细胞(dfByDayAnd细胞1, choosenList,
"testDay", "小细胞",
c("测试数","有效数","阳性数"),
c("最后六周按日分小细胞统计","测试时间","统计数值",""))
},
"阳性率、有效率" = {
panelPlotByDayAnd细胞(dfByDayAnd细胞1, choosenList,
"testDay", "小细胞",
c("有效率","阳性率"),
c("最后六周按日分小细胞统计","测试时间","统计数值",""))
},
"项目数、仪器数、批次数" = {
panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList,independentVariableName="testDay",panelName="小细胞",
dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("最后六周按日分小细胞统计","测试时间","统计数值",""))
},
"省数、市数、小细胞数、样本数" = {
panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList,independentVariableName="testDay",panelName="小细胞",
dependentVariableNames=c("样本数","市数","省数"),titleNames=c("最后六周按日分小细胞统计","测试时间","统计数值",""))
}
)
},
"按日分仪器统计" = {
choosenList <- slice_vec(仪器号List$仪器序列号, offset, per)
if(length(choosenList) == 0) return(NULL)
switch(metric,
"测试数、阳性数、有效数" = {
panelPlotByDayAnd仪器(dfData=dfByDayAnd仪器,choosenList,independentVariableName="testDay",panelName="仪器序列号",
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日分仪器统计","测试时间","统计数值",""))
},
"阳性率、有效率" = {
panelPlotByDayAnd仪器(dfData=dfByDayAnd仪器,choosenList,independentVariableName="testDay",panelName="仪器序列号",
dependentVariableNames=c("有效率","阳性率"),titleNames=c("最后六周按日分仪器统计","测试时间","统计数值",""))
},
"项目数、仪器数、批次数" = {
panelPlotByDayAnd仪器(dfData=dfByDayAnd仪器,choosenList,independentVariableName="testDay",panelName="仪器序列号",
dependentVariableNames=c("项目数","批次数"),titleNames=c("最后六周按日分仪器统计","测试时间","统计数值",""))
},
"省数、市数、小细胞数、样本数" = {
panelPlotByDayAnd仪器(dfData=dfByDayAnd仪器,choosenList,independentVariableName="testDay",panelName="仪器序列号",
dependentVariableNames=c("样本数","市数","省数","小细胞数"),titleNames=c("最后六周按日分仪器统计","测试时间","统计数值",""))
}
)
},
"全部统计" = {
switch(metric,
"测试数、阳性数、有效数" =
plotfunction(dfByDay1, "testDay", c("测试数","有效数","阳性数"),
c("最后六周按日统计","测试时间","统计数值","")),
"阳性率、有效率" =
plotfunction(dfByDay1, "testDay", c("有效率","阳性率"),
c("最后六周按日统计","测试时间","统计数值","")),
"项目数、仪器数、批次数" =
plotfunction(dfByDay1, "testDay", c("项目数","仪器数","批次数"),
c("最后六周按日统计","测试时间","统计数值","")),
"省数、市数、小细胞数、样本数" =
plotfunction(dfByDay1, "testDay", c("样本数","市数","省数","小细胞数"),
c("最后六周按日统计","测试时间","统计数值",""))
)
}
)
},
# ---------- 2. 按月统计 ----------
"按月统计" = {
switch(way,
"按月分省统计" = {
choosenList <- slice_vec(dfBy区域$省编号, offset, per)
if(length(choosenList) == 0) return(NULL)
switch(metric,
"测试数、阳性数、有效数" = {
panelPlotByMonthAndLocation(dfByMonthAndLocation, choosenList,
"testMonth", "省编号",
c("测试数","有效数","阳性数"),
c("按月分省统计","测试时间","统计数值",""))
},
"阳性率、有效率" = {
panelPlotByMonthAndLocation(dfByMonthAndLocation, choosenList,
"testMonth", "省编号",
c("有效率","阳性率"),
c("按月分省统计","测试时间","统计数值",""))
},
"项目数、仪器数、批次数" = {
panelPlotByMonthAndLocation(dfByMonthAndLocation, choosenList,
"testMonth", "省编号",
c("项目数","仪器数","批次数"),
c("按月分省统计","测试时间","统计数值",""))
},
"省数、市数、小细胞数、样本数" = {
panelPlotByMonthAndLocation(dfByMonthAndLocation, choosenList,
"testMonth", "省编号",
c("样本数","市数","小细胞数"),
c("按月分省统计","测试时间","统计数值",""))
}
)
},
"按月分小细胞统计" = {
choosenList <- slice_vec(细胞0$细胞, offset, per)
if(length(choosenList) == 0) return(NULL)
switch(metric,
"测试数、阳性数、有效数" = {
panelPlotByMonthAnd细胞(dfByMonthAnd细胞, choosenList,
"testMonth", "小细胞",
c("测试数","有效数","阳性数"),
c("按月分小细胞统计","测试时间","统计数值",""))
},
"阳性率、有效率" = {
panelPlotByMonthAnd细胞(dfByMonthAnd细胞, choosenList,
"testMonth", "小细胞",
c("有效率","阳性率"),
c("按月分小细胞统计","测试时间","统计数值",""))
},
"项目数、仪器数、批次数" = {
panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList,independentVariableName="testMonth",panelName="小细胞",
dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按月分小细胞统计","测试时间","统计数值",""))
},
"省数、市数、小细胞数、样本数" = {
panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList,independentVariableName="testMonth",panelName="小细胞",
dependentVariableNames=c("样本数","市数","省数","小细胞数"),titleNames=c("按月分小细胞统计","测试时间","统计数值",""))
}
)
},
"按月分仪器统计" = {
choosenList <- slice_vec(仪器号List$仪器序列号, offset, per)
if(length(choosenList) == 0) return(NULL)
switch(metric,
"测试数、阳性数、有效数" = {
panelPlotByMonthAnd仪器(dfData=dfByMonthAnd仪器,choosenList,independentVariableName="testMonth",panelName="仪器序列号",
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分仪器统计","测试时间","统计数值",""))
},
"阳性率、有效率" = {
panelPlotByMonthAnd仪器(dfData=dfByMonthAnd仪器,choosenList,independentVariableName="testMonth",panelName="仪器序列号",
dependentVariableNames=c("有效率","阳性率"),titleNames=c("按月分仪器统计","测试时间","统计数值",""))
},
"项目数、仪器数、批次数" = {
panelPlotByMonthAnd仪器(dfData=dfByMonthAnd仪器,choosenList,independentVariableName="testMonth",panelName="仪器序列号",
dependentVariableNames=c("项目数","批次数"),titleNames=c("按月分仪器统计","测试时间","统计数值",""))
},
"省数、市数、小细胞数、样本数" = {
panelPlotByMonthAnd仪器(dfData=dfByMonthAnd仪器,choosenList,independentVariableName="testMonth",panelName="仪器序列号",
dependentVariableNames=c("样本数","市数","省数"),titleNames=c("按月分仪器统计","测试时间","统计数值",""))
}
)
},
"全部统计" = {
switch(metric,
"测试数、阳性数、有效数" =
plotfunction(dfByMonth1, "testMonth", c("测试数","有效数","阳性数"),
c("按月统计","测试时间","统计数值","")),
"阳性率、有效率" =
plotfunction(dfByMonth1, "testMonth", c("有效率","阳性率"),
c("按月统计","测试时间","统计数值","")),
"项目数、仪器数、批次数" =
plotfunction(dfByMonth1, "testMonth", c("项目数","仪器数","批次数"),
c("按月统计","测试时间","统计数值","")),
"省数、市数、小细胞数、样本数" =
plotfunction(dfByMonth1, "testMonth", c("样本数","市数","省数","小细胞数"),
c("按月统计","测试时间","统计数值",""))
)
}
)
},
"按小细胞统计" = {
if (page == 1) {
switch(metric,
"测试数、阳性数、有效数" = plotfunction(dfBy细胞1,"小细胞",c("测试数","有效数","阳性数"),c("按小细胞统计","小细胞","统计数值","")),
"阳性率、有效率" = plotfunction(dfBy细胞1, "小细胞", c("有效率","阳性率"), c("按小细胞统计","小细胞","统计数值","")),
"项目数、仪器数、批次数" = plotfunction(dfBy细胞1, "小细胞", c("项目数","仪器数","批次数"), c("按小细胞统计","小细胞","统计数值","")),
"省数、市数、小细胞数、样本数" = plotfunction(dfBy细胞1, "小细胞", c("样本数","市数","省数"), c("按小细胞统计","小细胞","统计数值","")),
"测试截止、测试开始" = plotfunctionLog(dfBy细胞1, "小细胞", c("测试开始","测试截止"), c("按小细胞统计","小细胞","多少天之前",""))
)
} else if (page == 2) {
switch(metric,
"测试数、阳性数、有效数" = plotfunction(dfBy细胞2,"小细胞",c("测试数","有效数","阳性数"),c("按小细胞统计","小细胞","统计数值","")),
"阳性率、有效率" = plotfunction(dfBy细胞2, "小细胞", c("有效率","阳性率"), c("按小细胞统计","小细胞","统计数值","")),
"批次数、项目数、仪器数" = plotfunction(dfBy细胞2, "小细胞", c("项目数","仪器数","批次数"), c("按小细胞统计","小细胞","统计数值","")),
"省数、市数、小细胞数、样本数" = plotfunction(dfBy细胞2, "小细胞", c("样本数","市数","省数"), c("按小细胞统计","小细胞","统计数值","")),
"测试截止、测试开始" = plotfunctionLog(dfBy细胞2, "小细胞", c("测试开始","测试截止"), c("按小细胞统计","小细胞","多少天之前",""))
)
}
},
# ---------- 3. 其它维度（不需要分页） ----------
"按省统计" = {
switch(metric,
"测试数、阳性数、有效数" = plotfunction(dfBy区域, "省编号", c("测试数","有效数","阳性数"), c("按省统计","省编号","统计数值","")),
"阳性率、有效率" = plotfunction(dfBy区域, "省编号", c("有效率","阳性率"), c("按省统计","省编号","统计数值","")),
"批次数、项目数、仪器数" = plotfunction(dfBy区域, "省编号", c("项目数","仪器数","批次数"), c("按省统计","省编号","统计数值","")),
"省数、市数、小细胞数、样本数" = plotfunction(dfBy区域, "省编号", c("样本数","市数","小细胞数"), c("按省统计","省编号","统计数值","")),
"测试截止、测试开始" = plotfunctionLog(dfBy区域, "省编号", c("测试开始","测试截止"), c("按省统计","省编号","多少天之前",""))
)
},
"按仪器统计" = {
if(!is.numeric(page)) return(NULL)
if(page<1 | page>max(仪器号List$GroupID) | is.na(page)) return(NULL)
switch(metric,
"测试数、阳性数、有效数" = plotfunctionVector仪器序列号(page, 仪器号List, dfBy仪器, "仪器序列号", c("测试数","有效数","阳性数"), c("按仪器统计","仪器序列号","统计数值","")),
"阳性率、有效率" = plotfunctionVector仪器序列号(page, 仪器号List, dfBy仪器, "仪器序列号", c("有效率","阳性率"), c("按仪器统计","仪器序列号","统计数值","")),
"批次数、项目数、样本数" = plotfunctionVector仪器序列号(page, 仪器号List, dfBy仪器, "仪器序列号", c("项目数","批次数"), c("按仪器统计","仪器序列号","统计数值","")),
"省数、项目数、小细胞数、样本数" = plotfunctionVector仪器序列号(page, 仪器号List, dfBy仪器, "仪器序列号", c("样本数","省数", "市数","小细胞数"), c("按仪器统计","仪器序列号","统计数值","")),
"测试截止、测试开始" = plotfunctionVector仪器序列号Log(page, 仪器号List, dfBy仪器, "仪器序列号", c("测试开始","测试截止"), c("按仪器统计","仪器序列号","多少天之前",""))
)
},
"按样本类型统计" = {
switch(metric,
"测试数、阳性数、有效数" = plotfunction(dfBy样本, "样本类型", c("测试数","有效数","阳性数"), c("按样本类型统计","样本类型","统计数值","")),
"阳性率、有效率" = plotfunction(dfBy样本, "样本类型", c("有效率","阳性率"), c("按样本类型统计","样本类型","统计数值","")),
"批次数、省数、项目数、小细胞数" = plotfunction(dfBy样本, "样本类型", c("项目数","仪器数","批次数"), c("按样本类型统计","样本类型","统计数值","")),
"批次数、省数、项目数、小细胞数" = plotfunction(dfBy样本, "样本类型", c("省数", "市数","小细胞数"), c("按样本类型统计","样本类型","统计数值","")),
"测试截止、测试开始" = plotfunctionLog(dfBy样本, "样本类型", c("测试开始","测试截止"), c("按样本类型统计","样本类型","多少天之前",""))
)
},
"按试剂批次统计" = {
if(!is.numeric(page)) return(NULL)
if(page<1 | page>max(批次号List$GroupID) | is.na(page)) return(NULL)
switch(metric,
"测试数、阳性数、有效数" = plotfunctionVector批次名称(page, 批次号List, dfBy批次, "批次名称", c("测试数","有效数","阳性数"), c("按批次统计","批次名称","统计数值","")),
"阳性率、有效率" = plotfunctionVector批次名称(page, 批次号List, dfBy批次, "批次名称", c("有效率","阳性率"), c("按试剂批次统计","批次名称","统计数值","")),
"省数、项目数、小细胞数、样本数" = plotfunctionVector批次名称(page, 批次号List, dfBy批次, "批次名称", c("项目数","仪器数"), c("按试剂批次统计","批次名称","统计数值","")),
"省数、项目数、小细胞数、样本数" = plotfunctionVector批次名称(page, 批次号List, dfBy批次, "批次名称", c("样本数","省数", "市数","小细胞数"), c("按试剂批次统计","批次名称","统计数值","")),
"测试截止、测试开始" = plotfunctionVector批次名称Log(page, 批次号List, dfBy批次, "批次名称", c("测试开始","测试截止"), c("按试剂批次统计","批次名称","多少天之前",""))
)
},
"按试剂项目统计" = {
if(!is.numeric(page)) return(NULL)
if(page<1 | page>max(项目号List$GroupID) | is.na(page)) return(NULL)
switch(metric,
"测试数、阳性数、有效数" = plotfunctionVector项目名称(page, 项目号List, dfBy项目, "项目名称", c("测试数","有效数","阳性数"), c("按项目统计","项目名称","统计数值","")),
"阳性率、有效率" = plotfunctionVector项目名称(page, 项目号List, dfBy项目, "项目名称", c("有效率","阳性率"), c("按试剂项目统计","项目名称","统计数值","")),
"批次数、省数、小细胞数、样本数" = plotfunctionVector项目名称(page, 项目号List, dfBy项目, "项目名称", c("仪器数","批次数"), c("按试剂项目统计","项目名称","统计数值","")),
"省数、项目数、小细胞数、样本数" = plotfunctionVector项目名称(page, 项目号List, dfBy项目, "项目名称", c("样本数","省数", "市数","小细胞数"), c("按试剂项目统计","项目名称","统计数值","")),
"测试截止、测试开始" = plotfunctionVector项目名称Log(page, 项目号List, dfBy项目, "项目名称", c("测试开始","测试截止"), c("按试剂项目统计","项目名称","多少天之前",""))
)
}
)
return(p)
}
shinyApp(ui = ui, server = server)
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