From 669a9377a70b67ffb983f9fe979400f522d44d08 Mon Sep 17 00:00:00 2001 From: MingYang Date: Tue, 10 Jun 2025 17:14:04 +0800 Subject: [PATCH] Upload files to "/" --- analyticsRecord06052025.R | 2944 +++++++++++++++++++++++++++++++++++++ 1 file changed, 2944 insertions(+) create mode 100644 analyticsRecord06052025.R diff --git a/analyticsRecord06052025.R b/analyticsRecord06052025.R new file mode 100644 index 0000000..69e41e2 --- /dev/null +++ b/analyticsRecord06052025.R @@ -0,0 +1,2944 @@ +cairo_pdf("dataAnalyticsExample06052025.pdf", width = 8, height = 6,family = "SimHei" ) + +library(readr) +library(data.table) +library(Cairo) +library(ggplot2) +library(stringr) +library(datetime) +library(dplyr) +library(ggthemes) + +#guess_encoding("historyRecord20.csv") # [[1]]$encoding +df2 <- fread("historyRecord20250604175205UTF.csv",encoding = "UTF-8",fill = TRUE) + +df2$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$是否阳性==0.5]<-0 +summary(df2$结论) +summary(df2$是否阳性) +summary(df2$是否有效) + +#df2$仪器序列号_批次名称<-str_c(df2$仪器序列号,'_',df2$批次名称) + + +colnames(df2) +#df200<-df20 +summary(df2$仪器序列号) +summary(df2$批次名称) +unique(df2$批次名称) +unique(df2$仪器序列号) + +unique(df2$省市编号) +unique(df2$详细地址) + +unique(df2$仪器投放区域) +unique(df2$仪器备注名称) + + +df20<-df2 #[,c(1:11,16,17,20)] +df20$省市编号<-str_c("省市编号: ",df20$省市编号) + +colnames(df20) + + +# df20$testTime<-str_sub(df20$测试时间,1,19) +# df20$date<-as.Date(str_sub(df20$测试时间,1,10)) +# df20$time<-str_sub(df20$测试时间,12,19) +# df20$time0<-as.time(df20$time) + +df20$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$testTime<-as.datetime(str_sub(df20$测试时间,1,19),format='%Y-%m-%d %H:%M:%S') + +duration<-difftime(max(df20$testTime,na.rm = TRUE),min(df20$testTime,na.rm = TRUE),unit="hour")/24 + +df20$testTimeFromeBegining<-as.numeric(difftime(df20$testTime,min(df20$testTime,na.rm = TRUE),unit="hour")/24) + +summary(df20$testTimeFromeBegining) +dayMax<-max(df20$testTimeFromeBegining) +df20<-df20[dayMax-df20$testTimeFromeBegining<730,] + +#unique(df20$仪器序列号_批次名称) + +df20 <- df20[order(df20$批次名称,df20$testTimeFromeBegining),] + +running_avg <- function(x, window = 3) { + sapply(seq_along(x), function(i) { + start <- max(1, i - window + 1) + mean(x[start:i],na.rm=TRUE) + }) +} +lumping_avg<- function(x) { + sapply(seq_along(x), function(i) { + mean(x[1:i],na.rm=TRUE) + }) +} +lumping_sd<- function(x) { + sapply(seq_along(x), function(i) { + sd(x[1:i],na.rm=TRUE) + }) +} + +df20$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 <- df20[order(df20$testTimeFromeBegining),] + +df20 <- df20 %>% group_by(批次名称) %>% transform( + 浓度1移动均值 = running_avg(浓度1,20), + C值移动均值 = running_avg(C值,20), + T值移动均值 = running_avg(T值,20), + ToverC值移动均值 = running_avg(ToverC值,20), + 结论移动均值 = running_avg(结论,20) +) + +# df20$浓度1移动均值<-running_avg(df20$浓度1, 20) +# df20$C值移动均值<-running_avg(df20$C值, 20) +# df20$T值移动均值<-running_avg(df20$T值, 20) +# df20$ToverC值移动均值<-running_avg(df20$ToverC值, 20) +# df20$结论移动均值<-running_avg(df20$结论, 20) + +df20$浓度1累计均值<-lumping_avg(df20$浓度1) +df20$C值累计均值<-lumping_avg(df20$C值) +df20$T值累计均值<-lumping_avg(df20$T值) +df20$ToverC值累计均值<-lumping_avg(df20$ToverC值) +df20$结论累计均值<-lumping_avg(df20$结论) + +# df20$浓度1累计标差<-lumping_sd(df20$浓度1) +# df20$C值累计标差<-lumping_sd(df20$C值) +# df20$T值累计标差<-lumping_sd(df20$T值) +# df20$ToverC值累计标差<-lumping_sd(df20$ToverC值) +# df20$结论累计标差<-lumping_sd(df20$结论移动均值) + +df20$浓度1累计标差<-lumping_sd(df20$浓度1移动均值) +df20$C值累计标差<-lumping_sd(df20$C值移动均值) +df20$T值累计标差<-lumping_sd(df20$T值移动均值) +df20$ToverC值累计标差<-lumping_sd(df20$ToverC值移动均值) +df20$结论累计标差<-lumping_sd(df20$结论移动均值) + +df20$浓度1允许波动范围<-df20$浓度1累计均值+2*df20$浓度1累计标差 +df20$C值允许波动范围<-df20$C值累计均值+2*df20$C值累计标差 +df20$T值允许波动范围<-df20$T值累计均值+2*df20$T值累计标差 +df20$ToverC值允许波动范围<-df20$ToverC值累计均值+2*df20$ToverC值累计标差 +df20$结论允许波动范围<-df20$结论累计均值+2*df20$结论累计标差 + +summary(df20$浓度1移动均值) +summary(df20$running_avg) +summary(df20$浓度1累计均值) +summary(df20$浓度1累计标差) +summary(df20$结论累计均值) + + +dfByDayAndLocation <- df20 %>% group_by(testDay,testMonth,省市编号) %>% summarise( + 测试数 = n(), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + 仪器数=length(unique(仪器序列号)), + 批次数=length(unique(批次名称)), +) +dfByDayAndLocation$阳性率<-dfByDayAndLocation$阳性数/dfByDayAndLocation$有效数 +dfByDayAndLocation$有效率<-dfByDayAndLocation$有效数/dfByDayAndLocation$测试数 +dfByDayAndLocation$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),] + +lastDay<-last(dfByDayAndLocation$testDay) +dfByDayAndLocation<-dfByDayAndLocation[lastDay-dfByDayAndLocation$testDay<=21,] + + +dfByMonthAndLocation <- df20 %>% group_by(testMonth,省市编号) %>% 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), + 仪器数=length(unique(仪器序列号)), + 批次数=length(unique(批次名称)), +) +dfByMonthAndLocation$阳性率<-dfByMonthAndLocation$阳性数/dfByMonthAndLocation$有效数 +dfByMonthAndLocation$有效率<-dfByMonthAndLocation$有效数/dfByMonthAndLocation$测试数 +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$testMonth),] + +dfByMonth <- df20 %>% group_by(testMonth) %>% summarise( + 测试数 = n(), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + 仪器数=length(unique(仪器序列号)), + 批次数=length(unique(批次名称)), + 区域数=length(unique(省市编号)) +) +dfByMonth$阳性率<-dfByMonth$阳性数/dfByMonth$有效数 +dfByMonth$有效率<-dfByMonth$有效数/dfByMonth$测试数 +dfByMonth$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$有效数) +dfByMonth$区域数<-as.integer(dfByMonth$区域数) +dfByMonth <- dfByMonth[order(dfByMonth$testMonth),] + +dfBy区域 <- df20 %>% group_by(省市编号) %>% summarise( + 仪器数=length(unique(仪器序列号)), + 批次数=length(unique(批次名称)), + 测试数 = n(), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + 区域开始 = min(testTimeFromeBegining,na.rm = TRUE), + 区域截止 = max(testTimeFromeBegining,na.rm = TRUE) +) +dfBy区域$阳性率<-dfBy区域$阳性数/dfBy区域$有效数 +dfBy区域$有效率<-dfBy区域$有效数/dfBy区域$测试数 +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批次 <- df20 %>% group_by(批次名称) %>% summarise( + 仪器数=length(unique(仪器序列号)), + 测试数 = n(), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + 批次开始 = min(testTimeFromeBegining,na.rm = TRUE), + 批次截止 = max(testTimeFromeBegining,na.rm = TRUE), + 区域数=length(unique(省市编号)) +) +dfBy批次$阳性率<-dfBy批次$阳性数/dfBy批次$有效数 +dfBy批次$有效率<-dfBy批次$有效数/dfBy批次$测试数 +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$区域数<-as.integer(dfBy批次$区域数) + +dfBy仪器 <- df20 %>% group_by(仪器序列号) %>% summarise( + 批次数=length(unique(批次名称)), + 测试数 = n(), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + 批次开始 = min(testTimeFromeBegining,na.rm = TRUE), + 批次截止 = max(testTimeFromeBegining,na.rm = TRUE), + 区域数=length(unique(省市编号)) +) +dfBy仪器$阳性率<-dfBy仪器$阳性数/dfBy仪器$有效数 +dfBy仪器$有效率<-dfBy仪器$有效数/dfBy仪器$测试数 +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$区域数<-as.integer(dfBy仪器$区域数) + +dfByDayAndLocation测试数<-cbind("测试数",dfByDayAndLocation[,c(1:3,4)]) +dfByDayAndLocation有效数<-cbind("有效数",dfByDayAndLocation[,c(1:3,6)]) +dfByDayAndLocation阳性数<-cbind("阳性数",dfByDayAndLocation[,c(1:3,5)]) +colnames(dfByDayAndLocation测试数)<-c("group","Day","Month", "省市编号", "count") +colnames(dfByDayAndLocation有效数)<-c("group","Day","Month", "省市编号", "count") +colnames(dfByDayAndLocation阳性数)<-c("group","Day","Month", "省市编号", "count") +dfByDayAndLocationNumber<-rbind(rbind(dfByDayAndLocation测试数,dfByDayAndLocation有效数),dfByDayAndLocation阳性数) +#dfByDayAndLocationNumber$省市编号<-str_c("省市编号: ",dfByDayAndLocationNumber$省市编号) + +dfByDayNumber <- dfByDayAndLocationNumber %>% group_by(group,Day,Month) %>% summarise( + count=sum(count,na.rm = TRUE)) + + +dfByDayAndLocation <- df20 %>% group_by(testDay,testMonth,省市编号) %>% 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), + 仪器数=length(unique(仪器序列号)), + 批次数=length(unique(批次名称)), +) +dfByDayAndLocation$阳性率<-dfByDayAndLocation$阳性数/dfByDayAndLocation$有效数 +dfByDayAndLocation$有效率<-dfByDayAndLocation$有效数/dfByDayAndLocation$测试数 +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$testDay),] + +lastDay<-last(dfByDayAndLocation$testDay) +dfByDayAndLocation<-dfByDayAndLocation[lastDay-dfByDayAndLocation$testDay<=21,] + +dfByDay <- df20 %>% group_by(testMonth,testDay) %>% summarise( + 测试数 = n(), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + 仪器数=length(unique(仪器序列号)), + 批次数=length(unique(批次名称)), + 区域数=length(unique(省市编号)) +) +dfByDay$阳性率<-dfByDay$阳性数/dfByDay$有效数 +dfByDay$有效率<-dfByDay$有效数/dfByDay$测试数 +dfByDay$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$有效数) +dfByDay$区域数<-as.integer(dfByDay$区域数) +dfByDay <- dfByDay[order(dfByDay$testDay),] +dfByDay<-dfByDay[lastDay-dfByDay$testDay<=21,] + + +dfByDayAndLocation测试数<-cbind("测试数",dfByDayAndLocation[,c(1:3,4)]) +dfByDayAndLocation有效数<-cbind("有效数",dfByDayAndLocation[,c(1:3,6)]) +dfByDayAndLocation阳性数<-cbind("阳性数",dfByDayAndLocation[,c(1:3,5)]) +colnames(dfByDayAndLocation测试数)<-c("group","Day","Month", "省市编号", "count") +colnames(dfByDayAndLocation有效数)<-c("group","Day","Month", "省市编号", "count") +colnames(dfByDayAndLocation阳性数)<-c("group","Day","Month", "省市编号", "count") +dfByDayAndLocationNumber<-rbind(rbind(dfByDayAndLocation测试数,dfByDayAndLocation有效数),dfByDayAndLocation阳性数) +#dfByDayAndLocationNumber$省市编号<-str_c("省市编号: ",dfByDayAndLocationNumber$省市编号) + +dfByDayNumber <- dfByDayAndLocationNumber %>% group_by(group,Day,Month) %>% summarise( + count=sum(count,na.rm = TRUE)) + + +dfByDayAndLocation有效率<-cbind("有效率",dfByDayAndLocation[,c(1,2,3,10)]) +dfByDayAndLocation阳性率<-cbind("阳性率",dfByDayAndLocation[,c(1,2,3,9)]) +colnames(dfByDayAndLocation有效率)<-c("group","Day","Month", "省市编号", "Ratio") +colnames(dfByDayAndLocation阳性率)<-c("group","Day","Month", "省市编号", "Ratio") +dfByDayAndLocationRatio<-rbind(dfByDayAndLocation有效率,dfByDayAndLocation阳性率) +#dfByDayAndLocationRatio$省市编号<-str_c("省市编号: ",dfByDayAndLocationRatio$省市编号) + +dfByDay有效率<-cbind("有效率",dfByDay[,c(1,2,10)]) +dfByDay阳性率<-cbind("阳性率",dfByDay[,c(1,2,9)]) +colnames(dfByDay有效率)<-c("group","Month","Day","Ratio") +colnames(dfByDay阳性率)<-c("group","Month","Day","Ratio") + +dfByDayRatio<-rbind(dfByDay有效率,dfByDay阳性率) + +dfByDayAndLocation仪器数<-cbind("仪器数",dfByDayAndLocation[,c(1,2,3,7)]) +dfByDayAndLocation批次数<-cbind("批次数",dfByDayAndLocation[,c(1,2,3,8)]) +colnames(dfByDayAndLocation仪器数)<-c("group","Day","Month", "省市编号", "Count") +colnames(dfByDayAndLocation批次数)<-c("group","Day","Month", "省市编号", "Count") +dfByDayAndLocationCount<-rbind(dfByDayAndLocation仪器数,dfByDayAndLocation批次数) +#dfByDayAndLocationCount$省市编号<-str_c("省市编号: ",dfByDayAndLocationCount$省市编号) + +dfByDay仪器数<-cbind("仪器数",dfByDay[,c(1,2,6)]) +dfByDay批次数<-cbind("批次数",dfByDay[,c(1,2,7)]) +dfByDay区域数<-cbind("区域数",dfByDay[,c(1,2,8)]) +colnames(dfByDay仪器数)<-c("group","Month","Day","count") +colnames(dfByDay批次数)<-c("group","Month","Day","count") +colnames(dfByDay区域数)<-c("group","Month","Day","count") +dfByDayCount<-rbind(rbind(dfByDay仪器数,dfByDay批次数),dfByDay区域数) + +dfByMonthAndLocation测试数<-cbind("测试数",dfByMonthAndLocation[,c(1,2,3)]) +dfByMonthAndLocation有效数<-cbind("有效数",dfByMonthAndLocation[,c(1,2,5)]) +dfByMonthAndLocation阳性数<-cbind("阳性数",dfByMonthAndLocation[,c(1,2,4)]) +colnames(dfByMonthAndLocation测试数)<-c("group","month","省市编号", "count") +colnames(dfByMonthAndLocation有效数)<-c("group","month","省市编号", "count") +colnames(dfByMonthAndLocation阳性数)<-c("group","month","省市编号", "count") +dfByMonthAndLocationNumber<-rbind(rbind(dfByMonthAndLocation测试数,dfByMonthAndLocation有效数),dfByMonthAndLocation阳性数) +#dfByMonthAndLocationNumber$省市编号<-str_c("省市编号: ",dfByMonthAndLocationNumber$省市编号) + +dfByMonthNumber <- dfByMonthAndLocationNumber %>% group_by(group,month) %>% summarise( + count=sum(count,na.rm = TRUE)) + +dfByMonthAndLocation有效率<-cbind("有效率",dfByMonthAndLocation[,c(1,2,9)]) +dfByMonthAndLocation阳性率<-cbind("阳性率",dfByMonthAndLocation[,c(1,2,8)]) +colnames(dfByMonthAndLocation有效率)<-c("group","month","省市编号", "Ratio") +colnames(dfByMonthAndLocation阳性率)<-c("group","month","省市编号", "Ratio") +dfByMonthAndLocationRatio<-rbind(dfByMonthAndLocation有效率,dfByMonthAndLocation阳性率) +#dfByMonthAndLocationRatio$省市编号<-str_c("省市编号: ",dfByMonthAndLocationRatio$省市编号) + +dfByMonth有效率<-cbind("有效率",dfByMonth[,c(1,9)]) +dfByMonth阳性率<-cbind("阳性率",dfByMonth[,c(1,8)]) +colnames(dfByMonth有效率)<-c("group","month","Ratio") +colnames(dfByMonth阳性率)<-c("group","month","Ratio") + +dfByMonthRatio<-rbind(dfByMonth有效率,dfByMonth阳性率) + +dfByMonthAndLocation仪器数<-cbind("仪器数",dfByMonthAndLocation[,c(1,2,6)]) +dfByMonthAndLocation批次数<-cbind("批次数",dfByMonthAndLocation[,c(1,2,7)]) +colnames(dfByMonthAndLocation仪器数)<-c("group","month","省市编号", "Count") +colnames(dfByMonthAndLocation批次数)<-c("group","month","省市编号", "Count") +dfByMonthAndLocationCount<-rbind(dfByMonthAndLocation仪器数,dfByMonthAndLocation批次数) +#dfByMonthAndLocationCount$省市编号<-str_c("省市编号: ",dfByMonthAndLocationCount$省市编号) + +dfByMonth仪器数<-cbind("仪器数",dfByMonth[,c(1,5)]) +dfByMonth批次数<-cbind("批次数",dfByMonth[,c(1,6)]) +dfByMonth区域数<-cbind("区域数",dfByMonth[,c(1,7)]) +colnames(dfByMonth仪器数)<-c("group","month","count") +colnames(dfByMonth批次数)<-c("group","month","count") +colnames(dfByMonth区域数)<-c("group","month","count") +dfByMonthCount<-rbind(rbind(dfByMonth仪器数,dfByMonth批次数),dfByMonth区域数) + +dfby区域Number <- dfByMonthAndLocationNumber %>% group_by(group,省市编号) %>% summarise( + count=sum(count,na.rm = TRUE)) + +dfBy区域有效率<-cbind("有效率",dfBy区域[,c(1,10)]) +dfBy区域阳性率<-cbind("阳性率",dfBy区域[,c(1,9)]) +colnames(dfBy区域有效率)<-c("group","区域","Ratio") +colnames(dfBy区域阳性率)<-c("group","区域","Ratio") + +dfBy区域Ratio<-rbind(dfBy区域有效率,dfBy区域阳性率) +#dfBy区域Ratio$区域<-str_c("省市编号: ",dfBy区域Ratio$区域) + + +dfBy区域仪器数<-cbind("仪器数",dfBy区域[,c(1,2)]) +dfBy区域批次数<-cbind("批次数",dfBy区域[,c(1,3)]) +colnames(dfBy区域仪器数)<-c("group","区域","count") +colnames(dfBy区域批次数)<-c("group","区域","count") +dfBy区域Count<-rbind(dfBy区域仪器数,dfBy区域批次数) +#dfBy区域Count$区域<-str_c("省市编号: ",dfBy区域Count$区域) + +dfBy区域开始<-cbind("区域开始",dfBy区域[,c(1,7)]) +dfBy区域截止<-cbind("区域截止",dfBy区域[,c(1,8)]) +colnames(dfBy区域开始)<-c("group","区域","time") +colnames(dfBy区域截止)<-c("group","区域","time") +dfBy区域time<-rbind(dfBy区域开始,dfBy区域截止) +#dfBy区域time$区域<-str_c("省市编号: ",dfBy区域time$区域) + +dfBy批次测试数<-cbind("测试数",dfBy批次[,c(1,3)]) +dfBy批次有效数<-cbind("有效数",dfBy批次[,c(1,5)]) +dfBy批次阳性数<-cbind("阳性数",dfBy批次[,c(1,4)]) +colnames(dfBy批次测试数)<-c("group","批次","count") +colnames(dfBy批次有效数)<-c("group","批次","count") +colnames(dfBy批次阳性数)<-c("group","批次","count") +dfBy批次Number<-rbind(dfBy批次测试数,rbind(dfBy批次有效数,dfBy批次阳性数)) + +dfBy批次有效率<-cbind("有效率",dfBy批次[,c(1,10)]) +dfBy批次阳性率<-cbind("阳性率",dfBy批次[,c(1,9)]) +colnames(dfBy批次有效率)<-c("group","批次","Ratio") +colnames(dfBy批次阳性率)<-c("group","批次","Ratio") + +dfBy批次Ratio<-rbind(dfBy批次有效率,dfBy批次阳性率) + +dfBy批次仪器数<-cbind("仪器数",dfBy批次[,c(1,2)]) +dfBy批次区域数<-cbind("区域数",dfBy批次[,c(1,8)]) +colnames(dfBy批次仪器数)<-c("group","批次","count") +colnames(dfBy批次区域数)<-c("group","批次","count") +dfBy批次Count<-rbind(dfBy批次仪器数,dfBy批次区域数) + +dfBy批次开始<-cbind("批次开始",dfBy批次[,c(1,6)]) +dfBy批次截止<-cbind("批次截止",dfBy批次[,c(1,7)]) +colnames(dfBy批次开始)<-c("group","批次","time") +colnames(dfBy批次截止)<-c("group","批次","time") +dfBy批次time<-rbind(dfBy批次开始,dfBy批次截止) + + +dfBy仪器测试数<-cbind("测试数",dfBy仪器[,c(1,3)]) +dfBy仪器有效数<-cbind("有效数",dfBy仪器[,c(1,5)]) +dfBy仪器阳性数<-cbind("阳性数",dfBy仪器[,c(1,4)]) +colnames(dfBy仪器测试数)<-c("group","仪器","count") +colnames(dfBy仪器有效数)<-c("group","仪器","count") +colnames(dfBy仪器阳性数)<-c("group","仪器","count") +dfBy仪器Number<-rbind(dfBy仪器测试数,rbind(dfBy仪器有效数,dfBy仪器阳性数)) + + +dfBy仪器有效率<-cbind("有效率",dfBy仪器[,c(1,10)]) +dfBy仪器阳性率<-cbind("阳性率",dfBy仪器[,c(1,9)]) +colnames(dfBy仪器有效率)<-c("group","仪器","Ratio") +colnames(dfBy仪器阳性率)<-c("group","仪器","Ratio") + +dfBy仪器Ratio<-rbind(dfBy仪器有效率,dfBy仪器阳性率) + + +dfBy仪器批次数<-cbind("批次数",dfBy仪器[,c(1,2)]) +dfBy仪器区域数<-cbind("区域数",dfBy仪器[,c(1,8)]) +colnames(dfBy仪器批次数)<-c("group","仪器","count") +colnames(dfBy仪器区域数)<-c("group","仪器","count") +dfBy仪器Count<-rbind(dfBy仪器批次数,dfBy仪器区域数) + +dfBy仪器开始<-cbind("仪器开始",dfBy仪器[,c(1,6)]) +dfBy仪器截止<-cbind("仪器截止",dfBy仪器[,c(1,7)]) +colnames(dfBy仪器开始)<-c("group","仪器","time") +colnames(dfBy仪器截止)<-c("group","仪器","time") +dfBy仪器time<-rbind(dfBy仪器开始,dfBy仪器截止) + +dfBy区域top4<-dfBy区域$省市编号[order(-dfBy区域$测试数)][1:4] +dfBy区域top4<-dfBy区域top4[!is.na(dfBy区域top4)] +dfBy批次top4<-dfBy批次$批次名称[order(-dfBy批次$测试数)][1:4] +dfBy批次top4<-dfBy批次top4[!is.na(dfBy批次top4)] +dfBy仪器top4<-dfBy仪器$仪器序列号[order(-dfBy仪器$测试数)][1:4] +dfBy仪器top4<-dfBy仪器top4[!is.na(dfBy仪器top4)] + +df20Top4区域<-df20[df20$省市编号 %in% dfBy区域top4,] +df20Top4批次<-df20[df20$批次名称 %in% dfBy批次top4,] +df20Top4仪器<-df20[df20$仪器序列号 %in% dfBy仪器top4,] + +df20Top4区域$省市编号<-factor(df20Top4区域$省市编号,levels = dfBy区域top4) +df20Top4批次$批次名称<-factor(df20Top4批次$批次名称,levels = dfBy批次top4) +df20Top4仪器$仪器序列号<-factor(df20Top4仪器$仪器序列号,levels = dfBy仪器top4) + +dfByDayAndLocationNumber<-dfByDayAndLocationNumber[dfByDayAndLocationNumber$省市编号 %in% dfBy区域top4,] +dfByDayAndLocationNumber$省市编号<-factor(dfByDayAndLocationNumber$省市编号,levels = dfBy区域top4) + +dfByDayAndLocationCount<-dfByDayAndLocationCount[dfByDayAndLocationCount$省市编号 %in% dfBy区域top4,] +dfByDayAndLocationCount$省市编号<-factor(dfByDayAndLocationCount$省市编号,levels = dfBy区域top4) + +dfByDayAndLocationRatio<-dfByDayAndLocationRatio[dfByDayAndLocationRatio$省市编号 %in% dfBy区域top4,] +dfByDayAndLocationRatio$省市编号<-factor(dfByDayAndLocationRatio$省市编号,levels = dfBy区域top4) + +dfByMonthAndLocationRatio<-dfByMonthAndLocationRatio[dfByMonthAndLocationRatio$省市编号 %in% dfBy区域top4,] +dfByMonthAndLocationRatio$省市编号<-factor(dfByMonthAndLocationRatio$省市编号,levels = dfBy区域top4) + +dfByMonthAndLocationCount<-dfByMonthAndLocationCount[dfByMonthAndLocationCount$省市编号 %in% dfBy区域top4,] +dfByMonthAndLocationCount$省市编号<-factor(dfByMonthAndLocationCount$省市编号,levels = dfBy区域top4) + +dfByMonthAndLocationNumber<-dfByMonthAndLocationNumber[dfByMonthAndLocationNumber$省市编号 %in% dfBy区域top4,] +dfByMonthAndLocationNumber$省市编号<-factor(dfByMonthAndLocationNumber$省市编号,levels = dfBy区域top4) + +#dfByDayNumber1<-dfByDayNumber[dfByDayNumber$Month=="2024-09",] +plotdfByDayNumber<-ggplot(dfByDayNumber, aes(x = Day, y = count, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "blue","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 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 + ) + + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "最后三周按日测试统计", + x = "测试时间", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "blue","green")) + # 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") + +plotdfByDayNumber + + + +plotdfByDayLocationNumber<-ggplot(dfByDayAndLocationNumber, aes(x = Day, y = count, 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "blue","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 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( ~ 省市编号,ncol=2) + + labs( + title = "最后三周按日按地区测试统计", + x = "测试时间", + y = "数值统计", + fill = "" + ) + + scale_fill_manual(values = c("red", "blue","green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotdfByDayLocationNumber + +plotdfByDayRatio<-ggplot(dfByDayRatio, aes(x = Day, y = Ratio, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = round(Ratio,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 + ) + + # geom_text(aes(label=Ratio),vjust=1.6,size=1,color="white")+ + labs( + title = "最后三周按日测试统计", + x = "测试时间", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red","green")) + # 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") + +plotdfByDayRatio + +plotdfByDayLocationRatio<-ggplot(dfByDayAndLocationRatio, aes(x = Day, y = Ratio, 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = round(Ratio,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( ~ 省市编号,ncol=2) + + labs( + title = "最后三周按日按地区测试统计", + x = "测试时间", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotdfByDayLocationRatio + +plotdfByDayCount<-ggplot(dfByDayCount, aes(x = Day, y = count, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "blue","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 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 + ) + + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "最后三周按日测试统计", + x = "测试时间", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "blue","green")) + # 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") + +plotdfByDayCount + +plotdfByDayLocationCount<-ggplot(dfByDayAndLocationCount, aes(x = Day, y = Count, 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = Count), # 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( ~ 省市编号,ncol=2) + + labs( + title = "最后三周按日按地区统计", + x = "测试时间", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotdfByDayLocationCount + +plotdfByMonthNumber<-ggplot(dfByMonthNumber, aes(x = month, y = count, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "blue","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 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 = "每月测试统计", + x = "测试时间", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "blue","green")) + # 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") + +plotdfByMonthNumber + +plotdfByMonthLocationNumber<-ggplot(dfByMonthAndLocationNumber, aes(x = month, y = count, 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "blue","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 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( ~ 省市编号,ncol=2) + + labs( + title = "每月分区测试统计", + x = "测试时间", + y = "数值统计", + fill = "" + ) + + scale_fill_manual(values = c("red", "blue","green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotdfByMonthLocationNumber + +plotdfByMonthRatio<-ggplot(dfByMonthRatio, aes(x = month, y = Ratio, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = round(Ratio,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 + ) + + # geom_text(aes(label=Ratio),vjust=1.6,size=1,color="white")+ + labs( + title = "每月测试统计", + x = "测试时间", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red","green")) + # 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") + +plotdfByMonthRatio + +plotdfByMonthLocationRatio<-ggplot(dfByMonthAndLocationRatio, aes(x = month, y = Ratio, 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = round(Ratio,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( ~ 省市编号,ncol=2) + + labs( + title = "每月分区测试统计", + x = "测试时间", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotdfByMonthLocationRatio + +plotdfByMonthCount<-ggplot(dfByMonthCount, aes(x = month, y = count, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "blue","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 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 + ) + + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "每月测试统计", + x = "测试时间", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "blue","green")) + # 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") + +plotdfByMonthCount + +plotdfByMonthLocationCount<-ggplot(dfByMonthAndLocationCount, aes(x = month, y = Count, 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = Count), # 标签内容 + position = position_dodge(width = 0.4), # 与柱子位置一致 + vjust = -0.8, # 垂直位置（负值向上） + color = "black", # 标签颜色 + size = 2.0 # 字体大小 + ) + + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "每月分区测试统计", + x = "测试时间", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotdfByMonthLocationCount + +plotdfby区域Number<-ggplot(dfby区域Number, aes(x = 省市编号, y = count, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "blue","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 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 + ) + + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "分区测试统计", + x = "测试区域", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "blue","green")) + # 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") + +plotdfby区域Number + + +plotdfBy区域Ratio<-ggplot(dfBy区域Ratio, aes(x = 区域, y = Ratio, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = round(Ratio,2)), # 标签内容 + position = position_dodge(width = 0.4), # 与柱子位置一致 + vjust = -0.8, # 垂直位置（负值向上） + color = "black", # 标签颜色 + size = 2.0 # 字体大小 + ) + + labs( + title = "分区测试统计", + x = "测试区域", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red","green")) + # 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") + +plotdfBy区域Ratio + +plotdfBy区域Count<-ggplot(dfBy区域Count, aes(x = 区域, y = count, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 标签内容 + position = position_dodge(width = 0.4), # 与柱子位置一致 + vjust = -0.8, # 垂直位置（负值向上） + color = "black", # 标签颜色 + size = 2.0 # 字体大小 + ) + + labs( + title = "分区测试统计", + x = "测试区域", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "green")) + # 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") + +plotdfBy区域Count + +if(FALSE) { +plotdfBy区域timeBox <- ggplot(df20, aes(x=省市编号, y=testDay,color=省市编号)) + + geom_boxplot(show.legend = FALSE)+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "分区测试时间统计", + x = "测试区域", + y = "测试时间", + fill = "" + ) + + 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") + +plotdfBy区域timeBox +} + +plotdfBy批次Number<-ggplot(dfBy批次Number, aes(x = 批次, y = count, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + geom_line( + aes(group = group, color = group), + position = position_dodge(width = 0.4), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "blue","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_col( + position = position_dodge(width = 0.4), # 控制条间距 + width = 0.7 # 条宽度 + ) + + geom_text( + aes(label = count), # 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 = "试剂分批测试统计", + x = "测试批次", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "blue","green")) + # 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") + +plotdfBy批次Number + +plotdfBy批次Ratio<-ggplot(dfBy批次Ratio, aes(x = 批次, y = Ratio, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = round(Ratio,2)), # 标签内容 + position = position_dodge(width = 0.4), # 与柱子位置一致 + vjust = -0.8, # 垂直位置（负值向上） + color = "black", # 标签颜色 + size = 2.0 # 字体大小 + ) + + labs( + title = "试剂分批测试统计", + x = "测试批次", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red","green")) + # 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") + +plotdfBy批次Ratio + +plotdfBy批次Count<-ggplot(dfBy批次Count, aes(x = 批次, y = count, fill = group)) + + # geom_bar(stat="identity",区域 + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 标签内容 + position = position_dodge(width = 0.4), # 与柱子位置一致 + vjust = -0.6, # 垂直位置（负值向上） + color = "black", # 标签颜色 + size = 2.0 # 字体大小 + ) + + labs( + title = "试剂分批测试统计", + x = "测试批次", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "green")) + # 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") + +plotdfBy批次Count + +plotdfBy批次timeBox <- ggplot(df20, aes(x=批次名称, y=testDay,color=批次名称)) + + geom_boxplot(show.legend = FALSE)+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "试剂分批时间统计", + x = "批次名称", + y = "测试时间", + fill = "" + ) + + 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") + +plotdfBy批次timeBox + +plotdfBy仪器Number<-ggplot(dfBy仪器Number, aes(x = 仪器, y = count, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red", "blue","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 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 + ) + + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "仪器测试统计", + x = "测试仪器", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "blue","green")) + # 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") + +plotdfBy仪器Number + + +plotdfBy仪器Ratio<-ggplot(dfBy仪器Ratio, aes(x = 仪器, y = Ratio, fill = group)) + + # geom_bar(stat="identity", + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = round(Ratio,2)), # 标签内容 + position = position_dodge(width = 0.4), # 与柱子位置一致 + vjust = -0.8, # 垂直位置（负值向上） + color = "black", # 标签颜色 + size = 2.0 # 字体大小 + ) + + labs( + title = "仪器测试统计", + x = "测试仪器", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red","green")) + # 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") + +plotdfBy仪器Ratio + +plotdfBy仪器Count<-ggplot(dfBy仪器Count, aes(x = 仪器, y = count, fill = group)) + + # geom_bar(stat="identity",区域 + # position = position_dodge() + # ) + + 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), + size = 1, + linetype="dashed", + show.legend=FALSE, + alpha = 1.0 + ) + + scale_color_manual(values = c("red","green")) + # 自定义颜色 + # geom_point( + # aes(color = group), + # position = position_dodge(width = 0.4), + # size = 3 + # ) + + geom_text( + aes(label = count), # 标签内容 + position = position_dodge(width = 0.4), # 与柱子位置一致 + vjust = -0.8, # 垂直位置（负值向上） + color = "black", # 标签颜色 + size = 2.0 # 字体大小 + ) + + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "仪器测试统计", + x = "测试仪器", + y = "统计数值", + fill = "" + ) + + scale_fill_manual(values = c("red", "green")) + # 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") + +plotdfBy仪器Count + +plotdfBy仪器timeBox <- ggplot(df20, aes(x=仪器序列号, y=testDay,color=仪器序列号)) + + geom_boxplot(show.legend = FALSE)+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "仪器测试时间统计", + x = "仪器名称/序列号", + y = "测试时间", + fill = "" + ) + + 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") + +plotdfBy仪器timeBox + + +plot浓度1批次Box <- ggplot(df20, aes(x=批次名称, y=浓度1,color=省市编号)) + + geom_boxplot()+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "浓度与试剂批次关系统计", + x = "批次名称", + y = "浓度1", + fill = "" + ) + + 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") + +plot浓度1批次Box + +plot浓度1仪器Box <- ggplot(df20, aes(x=仪器序列号, y=浓度1,color=省市编号)) + + geom_boxplot()+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "浓度与仪器关系统计", + x = "仪器名称/序列号", + y = "浓度1", + fill = "" + ) + + 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") + +plot浓度1仪器Box + +plotC值批次Box <- ggplot(df20, aes(x=批次名称, y=C值,color=省市编号)) + + geom_boxplot()+ + scale_y_log10()+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "C值与试剂批次关系统计", + x = "批次名称", + y = "C值", + fill = "" + ) + + 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") + +plotC值批次Box + +plotC值仪器Box <- ggplot(df20, aes(x=仪器序列号, y=C值,color=省市编号)) + + geom_boxplot()+ + scale_y_log10()+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "C值与仪器关系统计", + x = "仪器名称/序列号", + y = "C值", + fill = "" + ) + + 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") + +plotC值仪器Box + +plotT值批次Box <- ggplot(df20, aes(x=批次名称, y=T值,color=省市编号)) + + geom_boxplot()+ + scale_y_log10()+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "T值与试剂批次关系统计", + x = "批次名称", + y = "T值", + fill = "" + ) + + 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") + +plotT值批次Box + +plotT值仪器Box <- ggplot(df20, aes(x=仪器序列号, y=T值,color=省市编号)) + + geom_boxplot()+ + scale_y_log10()+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "T值与仪器关系统计", + x = "仪器名称/序列号", + y = "T值", + fill = "" + ) + + 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") + +plotT值仪器Box + +plotToverC值批次Box <- ggplot(df20, aes(x=批次名称, y=ToverC值,color=省市编号)) + + geom_boxplot()+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "T/C值与试剂批次关系统计", + x = "批次名称", + y = "T/C值", + fill = "" + ) + + 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") + +plotToverC值批次Box + +plotToverC值仪器Box <- ggplot(df20, aes(x=仪器序列号, y=ToverC值,color=省市编号)) + + geom_boxplot()+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "T/C值与仪器关系统计", + x = "仪器名称/序列号", + y = "T/C值", + fill = "" + ) + + 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") + +plotToverC值仪器Box + +plot结论移动均值批次Box <- ggplot(df20, aes(x=批次名称, y=结论移动均值,color=省市编号)) + + geom_boxplot()+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "阳性率与试剂批次关系统计", + x = "批次名称", + y = "结论移动均值", + fill = "" + ) + + 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") + +plot结论移动均值批次Box + +plot结论移动均值仪器Box <- ggplot(df20, aes(x=仪器序列号, y=结论移动均值,color=省市编号)) + + geom_boxplot()+ + # geom_text(aes(label=count),vjust=1.6,size=1,color="white")+ + labs( + title = "阳性率与仪器关系统计", + x = "仪器名称/序列号", + y = "结论移动均值", + fill = "" + ) + + 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") + +plot结论移动均值仪器Box + +xmin<-min(df20$testDay) +xmax<-max(df20$testDay) + +ymax<-max(6,quantile(df20$浓度1,probs = 0.95, # 要计算的百分位（0-1之间） + na.rm = TRUE)) +plot浓度1by批次 <- ggplot(df20)+geom_point(aes(testDay, 浓度1,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(0, ymax)+theme(legend.position ="right")+ + labs( + title = "浓度", # 主标题 + x = "测试日期", # X轴标签 + y = "浓度1", # Y轴标签 + color = "批次名称" # 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") + +plot浓度1by批次 + + +plot浓度1批次<-ggplot(df20Top4批次)+geom_point(aes(testDay, 浓度1),color="orange")+ + 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.)+ + facet_wrap( ~ 批次名称,ncol=2) + + labs( + title = "浓度与试剂批次关系", # 主标题 + x = "测试日期", # X轴标签 + y = "浓度1" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plot浓度1批次 + +plot浓度1by省市编号 <- ggplot(df20)+geom_point(aes(testDay, 浓度1,color=as.character(省市编号)))+ + 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(0, ymax)+theme(legend.position ="right")+ + labs( + title = "浓度", # 主标题 + x = "测试日期", # X轴标签 + y = "浓度1", # Y轴标签 + color = "" # 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") + +plot浓度1by省市编号 + + +plot浓度1省市编号<-ggplot(df20Top4区域)+geom_point(aes(testDay, 浓度1),color="orange")+ + 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.)+ + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "浓度与地域关系", # 主标题 + x = "测试日期", # X轴标签 + y = "浓度1" )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plot浓度1省市编号 + +ymax<-max(6,quantile(df20$浓度1,probs = 0.95, # 要计算的百分位（0-1之间） + na.rm = TRUE)) +plot浓度1by仪器 <- ggplot(df20)+geom_point(aes(testDay, 浓度1,color=as.character(仪器序列号)))+ + geom_line(aes(testDay,浓度1移动均值),color="blue")+ + geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "浓度", # 主标题 + x = "测试日期", # X轴标签 + y = "浓度1", # Y轴标签 + color = "仪器序列号" # 图例标题 + )+ + scale_x_date( + date_labels = "%Y-%m-%d", # 格式符组合 + date_breaks = "1 month" # 标签间隔（如 "2 weeks"） + )+ + theme_minimal() + theme( + plot.title = element_text(size = 14, face = "bold", hjust = 0.5), + axis.title.x = element_text(size = 10,face = "bold"), + axis.title.y = element_text(size = 10,face = "bold"), + axis.text.x = element_text(size = 8, face = "bold",angle=90), + legend.position = "right") + +plot浓度1by仪器 + + +plot浓度1仪器<-ggplot(df20Top4仪器)+geom_point(aes(testDay, 浓度1),color="orange")+ + geom_line(aes(testDay,浓度1移动均值),color="blue")+ + geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 仪器序列号,ncol=2) + + labs( + title = "浓度与仪器关系", # 主标题 + x = "测试日期", # X轴标签 + y = "浓度1" )+ + scale_fill_manual(values = c("red", "green")) + # 自定义颜色 + theme_minimal() + theme( + plot.title = element_text(size = 14, face = "bold", hjust = 0.5), + axis.title.x = element_text(size = 12,face = "bold"), + axis.title.y = element_text(size = 12,face = "bold"), + axis.text.x = element_text(size = 8, face = "bold",angle=90) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plot浓度1仪器 + +ymax<-max(6,quantile(df20$C值,probs = 0.98, # 要计算的百分位（0-1之间） + na.rm = TRUE)) +plotC值by批次 <- ggplot(df20)+geom_point(aes(testDay, C值,color=as.character(批次名称)))+ + geom_line(aes(testDay,C值移动均值),color="blue")+ + geom_line(aes(testDay,C值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,C值允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + scale_y_log10()+ + labs( + title = "C值", # 主标题 + x = "测试日期", # X轴标签 + y = "C值", # Y轴标签 + color = "批次名称" # 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") + +plotC值by批次 + + +plotC值批次<-ggplot(df20Top4批次)+geom_point(aes(testDay, C值),color="orange")+ + geom_line(aes(testDay,C值移动均值),color="blue")+ + geom_line(aes(testDay,C值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,C值允许波动范围),color="red",linewidth=1.)+ + scale_y_log10()+ + facet_wrap( ~ 批次名称,ncol=2) + + labs( + title = "C值与试剂批次关系", # 主标题 + x = "测试日期", # X轴标签 + y = "C值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotC值批次 + + +plotC值by省市编号 <- ggplot(df20)+geom_point(aes(testDay, C值,color=as.character(省市编号)))+ + geom_line(aes(testDay,C值移动均值),color="blue")+ + geom_line(aes(testDay,C值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,C值允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "C值", # 主标题 + x = "测试日期", # X轴标签 + y = "C值", # Y轴标签 + color = "" # 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") + +plotC值by省市编号 + + +plotC值省市编号<-ggplot(df20Top4区域)+geom_point(aes(testDay, C值),color="orange")+ + geom_line(aes(testDay,C值移动均值),color="blue")+ + geom_line(aes(testDay,C值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,C值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "C值与地域关系", # 主标题 + x = "测试日期", # X轴标签 + y = "C值" )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotC值省市编号 + +plotC值by仪器 <- ggplot(df20)+geom_point(aes(testDay, C值,color=as.character(仪器序列号)))+ + geom_line(aes(testDay,C值移动均值),color="blue")+ + geom_line(aes(testDay,C值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,C值允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "C值", # 主标题 + x = "测试日期", # X轴标签 + y = "C值", # Y轴标签 + color = "仪器序列号" # 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") + +plotC值by仪器 + + +plotC值仪器<-ggplot(df20Top4仪器)+geom_point(aes(testDay, C值),color="orange")+ + geom_line(aes(testDay,C值移动均值),color="blue")+ + geom_line(aes(testDay,C值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,C值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 仪器序列号,ncol=2) + + labs( + title = "C值与仪器关系", # 主标题 + x = "测试日期", # X轴标签 + y = "C值" )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotC值仪器 + +ymax<-max(6,quantile(df20$T值,probs = 0.98, # 要计算的百分位（0-1之间） + na.rm = TRUE)) +plotT值by批次 <- ggplot(df20)+geom_point(aes(testDay, T值,color=as.character(批次名称)))+ + geom_line(aes(testDay,T值移动均值),color="blue")+ + geom_line(aes(testDay,T值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,T值允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "T值", # 主标题 + x = "测试日期", # X轴标签 + y = "T值", # Y轴标签 + color = "批次名称" # 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") + +plotT值by批次 + + +plotT值批次<-ggplot(df20Top4批次)+geom_point(aes(testDay, T值),color="orange")+ + geom_line(aes(testDay,T值移动均值),color="blue")+ + geom_line(aes(testDay,T值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,T值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 批次名称,ncol=2) + + labs( + title = "T值与试剂批次关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotT值批次 + + +plotT值by省市编号 <- ggplot(df20)+geom_point(aes(testDay, T值,color=as.character(省市编号)))+ + geom_line(aes(testDay,T值移动均值),color="blue")+ + geom_line(aes(testDay,T值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,T值允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "T值", # 主标题 + x = "测试日期", # X轴标签 + y = "T值", # Y轴标签 + color = "" # 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") + +plotT值by省市编号 + + +plotT值省市编号<-ggplot(df20Top4区域)+geom_point(aes(testDay, T值),color="orange")+ + geom_line(aes(testDay,T值移动均值),color="blue")+ + geom_line(aes(testDay,T值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,T值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "T值与地域关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T值" )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotT值省市编号 + +plotT值by仪器 <- ggplot(df20)+geom_point(aes(testDay, T值,color=as.character(仪器序列号)))+ + geom_line(aes(testDay,T值移动均值),color="blue")+ + geom_line(aes(testDay,T值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,T值允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "T值", # 主标题 + x = "测试日期", # X轴标签 + y = "T值", # Y轴标签 + color = "仪器序列号" # 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") + +plotT值by仪器 + + +plotT值仪器<-ggplot(df20Top4仪器)+geom_point(aes(testDay, T值),color="orange")+ + geom_line(aes(testDay,T值移动均值),color="blue")+ + geom_line(aes(testDay,T值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,T值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 仪器序列号,ncol=2) + + labs( + title = "T值与仪器关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T值" )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotT值仪器 + +ymax<-max(6,quantile(df20$ToverC值,probs = 0.98, # 要计算的百分位（0-1之间） + na.rm = TRUE)) +plotToverC值by批次 <- ggplot(df20)+geom_point(aes(testDay, ToverC值,color=as.character(批次名称)))+ + geom_line(aes(testDay,ToverC值移动均值),color="blue")+ + geom_line(aes(testDay,ToverC值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,ToverC值允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "T/C值", # 主标题 + x = "测试日期", # X轴标签 + y = "T/C值", # Y轴标签 + color = "批次名称" # 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") + +plotToverC值by批次 + + +plotToverC值批次<-ggplot(df20Top4批次)+geom_point(aes(testDay, ToverC值),color="orange")+ + geom_line(aes(testDay,ToverC值移动均值),color="blue")+ + geom_line(aes(testDay,ToverC值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,ToverC值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 批次名称,ncol=2) + + labs( + title = "T/C值与试剂批次关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T/C值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotToverC值批次 + + +plotToverC值by省市编号 <- ggplot(df20)+geom_point(aes(testDay, ToverC值,color=as.character(省市编号)))+ + geom_line(aes(testDay,ToverC值移动均值),color="blue")+ + geom_line(aes(testDay,ToverC值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,ToverC值允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "T/C值", # 主标题 + x = "测试日期", # X轴标签 + y = "T/C值", # Y轴标签 + color = "" # 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") + +plotToverC值by省市编号 + + +plotToverC值省市编号<-ggplot(df20Top4区域)+geom_point(aes(testDay, ToverC值),color="orange")+ + geom_line(aes(testDay,ToverC值移动均值),color="blue")+ + geom_line(aes(testDay,ToverC值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,ToverC值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "T/C值与地域关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T/C值" )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotToverC值省市编号 + +plotToverC值by仪器 <- ggplot(df20)+geom_point(aes(testDay, ToverC值,color=as.character(仪器序列号)))+ + geom_line(aes(testDay,ToverC值移动均值),color="blue")+ + geom_line(aes(testDay,ToverC值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,ToverC值允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "T/C值", # 主标题 + x = "测试日期", # X轴标签 + y = "T/C值", # Y轴标签 + color = "仪器序列号" # 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") + +plotToverC值by仪器 + + +plotToverC值仪器<-ggplot(df20Top4仪器)+geom_point(aes(testDay, ToverC值),color="orange")+ + geom_line(aes(testDay,ToverC值移动均值),color="blue")+ + geom_line(aes(testDay,ToverC值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,ToverC值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 仪器序列号,ncol=2) + + labs( + title = "T/C值与仪器关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T/C值" )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotToverC值仪器 + +ymax<-1.0 +plot结论by批次 <- ggplot(df20)+geom_point(aes(testDay, 是否阳性,color=as.character(批次名称)))+ + geom_line(aes(testDay,结论移动均值),color="blue")+ + geom_line(aes(testDay,结论累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,结论允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "结论/阳性率", # 主标题 + x = "测试日期", # X轴标签 + y = "结论/阳性率", # Y轴标签 + color = "批次名称" # 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") + +plot结论by批次 + + +plot结论批次<-ggplot(df20Top4批次)+geom_point(aes(testDay, 是否阳性),color="orange")+ + geom_line(aes(testDay,结论移动均值),color="blue")+ + geom_line(aes(testDay,结论累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,结论允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 批次名称,ncol=2) + + labs( + title = "结论/阳性率与试剂批次关系", # 主标题 + x = "测试日期", # X轴标签 + y = "结论/阳性率" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plot结论批次 + + +plot结论by省市编号 <- ggplot(df20)+geom_point(aes(testDay, 是否阳性,color=as.character(省市编号)))+ + geom_line(aes(testDay,结论移动均值),color="blue")+ + geom_line(aes(testDay,结论累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,结论允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "结论/阳性率", # 主标题 + x = "测试日期", # X轴标签 + y = "结论/阳性率", # Y轴标签 + color = "" # 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") + +plot结论by省市编号 + + +plot结论省市编号<-ggplot(df20Top4区域)+geom_point(aes(testDay, 是否阳性),color="orange")+ + geom_line(aes(testDay,结论移动均值),color="blue")+ + geom_line(aes(testDay,结论累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,结论允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "结论/阳性率与地域关系", # 主标题 + x = "测试日期", # X轴标签 + y = "结论/阳性率" )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plot结论省市编号 + +plot结论by仪器 <- ggplot(df20)+geom_point(aes(testDay, 是否阳性,color=as.character(仪器序列号)))+ + geom_line(aes(testDay,结论移动均值),color="blue")+ + geom_line(aes(testDay,结论累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,结论允许波动范围),color="red",linewidth=1.)+ + xlim(xmin, xmax) + ylim(0, ymax)+theme(legend.position ="right")+ + labs( + title = "结论/阳性率", # 主标题 + x = "测试日期", # X轴标签 + y = "结论/阳性率", # Y轴标签 + color = "仪器序列号" # 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") + +plot结论by仪器 + + +plot结论仪器<-ggplot(df20Top4仪器)+geom_point(aes(testDay, 是否阳性),color="orange")+ + geom_line(aes(testDay,结论移动均值),color="blue")+ + geom_line(aes(testDay,结论累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,结论允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 仪器序列号,ncol=2) + + labs( + title = "结论/阳性率与仪器关系", # 主标题 + x = "测试日期", # X轴标签 + y = "结论/阳性率" )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plot结论仪器 +df20$结论Outlier<-1 +df20$结论Outlier[df20$结论允许波动范围-df20$结论移动均值>0 & + df20$结论移动均值-(df20$结论累计均值-2*df20$结论累计标差)>0]<-0 +df20$结论Outlier[is.na(df20$结论累计标差)]<-NA +summary(df20$结论Outlier) + +dfBy批次Outlier <- df20 %>% group_by(批次名称) %>% summarise( + outlierCount=sum(结论Outlier,na.rm=TRUE)) +dfBy批次Outliertop4<-dfBy批次Outlier$批次名称[order(-dfBy批次Outlier$outlierCount)][1:4] +dfBy批次Outliertop4<-dfBy批次Outliertop4[!is.na(dfBy批次Outliertop4)] + + +df20Top4批次Outlier<-df20[df20$批次名称 %in% dfBy批次Outliertop4,] +df20Top4批次Outlier$批次名称<-factor(df20Top4批次Outlier$批次名称,levels = dfBy批次Outliertop4) + +plot浓度1批次Outlier<-ggplot(df20Top4批次Outlier)+geom_point(aes(testDay, 浓度1),color="orange")+ + 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.)+ + facet_wrap( ~ 批次名称,ncol=2) + + labs( + title = "浓度与试剂批次关系", # 主标题 + x = "测试日期", # X轴标签 + y = "浓度1" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plot浓度1批次Outlier + +plotC值批次Outlier<-ggplot(df20Top4批次Outlier)+geom_point(aes(testDay, C值),color="orange")+ + geom_line(aes(testDay,C值移动均值),color="blue")+ + geom_line(aes(testDay,C值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,C值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 批次名称,ncol=2) + + labs( + title = "C值与试剂批次关系", # 主标题 + x = "测试日期", # X轴标签 + y = "C值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotC值批次Outlier + + +plotT值批次Outlier<-ggplot(df20Top4批次Outlier)+geom_point(aes(testDay, T值),color="orange")+ + geom_line(aes(testDay,T值移动均值),color="blue")+ + geom_line(aes(testDay,T值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,T值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 批次名称,ncol=2) + + labs( + title = "T值与试剂批次关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotT值批次Outlier + +plotToverC值批次Outlier<-ggplot(df20Top4批次Outlier)+geom_point(aes(testDay, ToverC值),color="orange")+ + geom_line(aes(testDay,ToverC值移动均值),color="blue")+ + geom_line(aes(testDay,ToverC值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,ToverC值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 批次名称,ncol=2) + + labs( + title = "T/C值与试剂批次关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T/C值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plotToverC值批次Outlier + +plot结论批次Outlier<-ggplot(df20Top4批次Outlier)+geom_point(aes(testDay, 是否阳性),color="orange")+ + geom_line(aes(testDay,结论移动均值),color="blue")+ + geom_line(aes(testDay,结论累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,结论允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 批次名称,ncol=2) + + labs( + title = "结论/阳性率与试剂批次关系", # 主标题 + x = "测试日期", # X轴标签 + y = "结论/阳性率" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + +plot结论批次Outlier + +if(FALSE){ + dfBy区域Outlier <- df20 %>% group_by(省市编号) %>% summarise( + outlierCount=sum(结论Outlier,na.rm=TRUE)) + dfBy区域Outliertop4<-dfBy区域Outlier$省市编号[order(-dfBy区域Outlier$outlierCount)][1:4] + dfBy区域Outliertop4<-dfBy区域Outliertop4[!is.na(dfBy区域Outliertop4)] + + + df20Top4区域Outlier<-df20[df20$省市编号 %in% dfBy区域Outliertop4,] + df20Top4区域Outlier$省市编号<-factor(df20Top4区域Outlier$省市编号,levels = dfBy区域Outliertop4) + + plot浓度1区域Outlier<-ggplot(df20Top4区域Outlier)+geom_point(aes(testDay, 浓度1),color="orange")+ + 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.)+ + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "浓度与地域关系", # 主标题 + x = "测试日期", # X轴标签 + y = "浓度1" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + + plot浓度1区域Outlier + + plotC值区域Outlier<-ggplot(df20Top4区域Outlier)+geom_point(aes(testDay, C值),color="orange")+ + geom_line(aes(testDay,C值移动均值),color="blue")+ + geom_line(aes(testDay,C值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,C值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "C值与地域关系", # 主标题 + x = "测试日期", # X轴标签 + y = "C值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + + plotC值区域Outlier + + + plotT值区域Outlier<-ggplot(df20Top4区域Outlier)+geom_point(aes(testDay, T值),color="orange")+ + geom_line(aes(testDay,T值移动均值),color="blue")+ + geom_line(aes(testDay,T值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,T值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "T值与地域关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + + plotT值区域Outlier + + plotToverC值区域Outlier<-ggplot(df20Top4区域Outlier)+geom_point(aes(testDay, ToverC值),color="orange")+ + geom_line(aes(testDay,ToverC值移动均值),color="blue")+ + geom_line(aes(testDay,ToverC值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,ToverC值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "T/C值与地域关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T/C值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + + plotToverC值区域Outlier + + plot结论区域Outlier<-ggplot(df20Top4区域Outlier)+geom_point(aes(testDay, 是否阳性),color="orange")+ + geom_line(aes(testDay,结论移动均值),color="blue")+ + geom_line(aes(testDay,结论累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,结论允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 省市编号,ncol=2) + + labs( + title = "结论/阳性率与地域关系", # 主标题 + x = "测试日期", # X轴标签 + y = "结论/阳性率" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + + plot结论区域Outlier +} +if(FALSE){ + dfBy仪器Outlier <- df20 %>% group_by(仪器序列号) %>% summarise( + outlierCount=sum(结论Outlier,na.rm=TRUE)) + dfBy仪器Outliertop4<-dfBy仪器Outlier$仪器序列号[order(-dfBy仪器Outlier$outlierCount)][1:4] + dfBy仪器Outliertop4<-dfBy仪器Outliertop4[!is.na(dfBy仪器Outliertop4)] + + + df20Top4仪器Outlier<-df20[df20$仪器序列号 %in% dfBy仪器Outliertop4,] + df20Top4仪器Outlier$仪器序列号<-factor(df20Top4仪器Outlier$仪器序列号,levels = dfBy仪器Outliertop4) + + plot浓度1仪器Outlier<-ggplot(df20Top4仪器Outlier)+geom_point(aes(testDay, 浓度1),color="orange")+ + 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.)+ + facet_wrap( ~ 仪器序列号,ncol=2) + + labs( + title = "浓度与仪器关系", # 主标题 + x = "测试日期", # X轴标签 + y = "浓度1" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + + plot浓度1仪器Outlier + + plotC值仪器Outlier<-ggplot(df20Top4仪器Outlier)+geom_point(aes(testDay, C值),color="orange")+ + geom_line(aes(testDay,C值移动均值),color="blue")+ + geom_line(aes(testDay,C值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,C值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 仪器序列号,ncol=2) + + labs( + title = "C值与仪器关系", # 主标题 + x = "测试日期", # X轴标签 + y = "C值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + + plotC值仪器Outlier + + + plotT值仪器Outlier<-ggplot(df20Top4仪器Outlier)+geom_point(aes(testDay, T值),color="orange")+ + geom_line(aes(testDay,T值移动均值),color="blue")+ + geom_line(aes(testDay,T值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,T值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 仪器序列号,ncol=2) + + labs( + title = "T值与仪器关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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) , + panel.border = element_rect( + color = "black", # 边框颜色 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + + plotT值仪器Outlier + + plotToverC值仪器Outlier<-ggplot(df20Top4仪器Outlier)+geom_point(aes(testDay, ToverC值),color="orange")+ + geom_line(aes(testDay,ToverC值移动均值),color="blue")+ + geom_line(aes(testDay,ToverC值累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,ToverC值允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 仪器序列号,ncol=2) + + labs( + title = "T/C值与仪器关系", # 主标题 + x = "测试日期", # X轴标签 + y = "T/C值" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + + plotToverC值仪器Outlier + + plot结论仪器Outlier<-ggplot(df20Top4仪器Outlier)+geom_point(aes(testDay, 是否阳性),color="orange")+ + geom_line(aes(testDay,结论移动均值),color="blue")+ + geom_line(aes(testDay,结论累计均值),color="green",linewidth=1.)+ + geom_line(aes(testDay,结论允许波动范围),color="red",linewidth=1.)+ + facet_wrap( ~ 仪器序列号,ncol=2) + + labs( + title = "结论/阳性率与仪器关系", # 主标题 + x = "测试日期", # X轴标签 + y = "结论/阳性率" + )+ + scale_fill_manual(values = c("red", "green")) + # 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 + size = 1., # 边框粗细 + linetype = "solid", # 线型（solid/dashed/dotted） + fill = NA # 填充色（NA为透明） + ), + legend.position = "right") + + plot结论仪器Outlier +} + +dev.off() \ No newline at end of file