1758 lines
81 KiB
R
1758 lines
81 KiB
R
library(readr)
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#library(data.table)
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library(Cairo)
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library(ggplot2)
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library(stringi)
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library(stringr)
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library(datetime)
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library(dplyr)
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library(ggthemes)
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library(RMySQL)
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plotfunction<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
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lth1<-length(dependentVariableNames)
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dfData00<-data.frame()
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for(i in 1:lth1){
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dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
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colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
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dfData00<-rbind(dfData00,dfData0)
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}
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plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, fill = Group)) +
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geom_col(
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position = position_dodge(width = 0.4), # 控制条间距
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width = 0.7 # 条宽度
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) +
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geom_line(
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aes(group = Group, color = Group),
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position = position_dodge(width = 0.4),
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size = 1,
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linetype="dashed",
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show.legend=FALSE,
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alpha = 1.0
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) +
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scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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geom_text(
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aes(label = round(Count,2)), # 标签内容
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position = position_dodge(width = 0.4), # 与柱子位置一致
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vjust = -0.4, # 垂直位置（负值向上）
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color = "black", # 标签颜色
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size = 1.2 # 字体大小
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) +
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labs(
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title = titleNames[1],
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x = titleNames[2],
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y = titleNames[3],
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fill = titleNames[4]
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) +
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scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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theme_minimal() + theme(
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plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
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axis.title.x = element_text(size = 12, face = "bold"),
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axis.title.y = element_text(size = 12, face = "bold"),
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axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
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legend.position = "right")
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plot1
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#return (list(plotdfDataNumber,b23,b33,b43,b53))
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}
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plotfunctionVector仪器序列号<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
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dfData<-dfData[(dfData$仪器序列号 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
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lth1<-length(dependentVariableNames)
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dfData00<-data.frame()
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for(i in 1:lth1){
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dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
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colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
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dfData00<-rbind(dfData00,dfData0)
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}
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plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, fill = Group)) +
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geom_col(
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position = position_dodge(width = 0.4), # 控制条间距
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width = 0.7 # 条宽度
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) +
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geom_line(
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aes(group = Group, color = Group),
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position = position_dodge(width = 0.4),
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size = 1,
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linetype="dashed",
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show.legend=FALSE,
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alpha = 1.0
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) +
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scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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geom_text(
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aes(label = round(Count,2)), # 标签内容
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position = position_dodge(width = 0.4), # 与柱子位置一致
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vjust = -0.4, # 垂直位置（负值向上）
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color = "black", # 标签颜色
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size = 1.2 # 字体大小
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) +
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labs(
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title = titleNames[1],
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x = titleNames[2],
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y = titleNames[3],
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fill = titleNames[4]
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) +
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scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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theme_minimal() + theme(
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plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
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axis.title.x = element_text(size = 12, face = "bold"),
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axis.title.y = element_text(size = 12, face = "bold"),
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axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
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legend.position = "right")
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plot1
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#return (list(plotdfDataNumber,b23,b33,b43,b53))
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}
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plotfunctionVector批次名称<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
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dfData<-dfData[(dfData$批次名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
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lth1<-length(dependentVariableNames)
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dfData00<-data.frame()
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for(i in 1:lth1){
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dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
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colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
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dfData00<-rbind(dfData00,dfData0)
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}
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plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, fill = Group)) +
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geom_col(
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position = position_dodge(width = 0.4), # 控制条间距
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width = 0.7 # 条宽度
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) +
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geom_line(
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aes(group = Group, color = Group),
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position = position_dodge(width = 0.4),
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size = 1,
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linetype="dashed",
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show.legend=FALSE,
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alpha = 1.0
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) +
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scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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geom_text(
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aes(label = round(Count,2)), # 标签内容
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position = position_dodge(width = 0.4), # 与柱子位置一致
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vjust = -0.4, # 垂直位置（负值向上）
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color = "black", # 标签颜色
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size = 1.2 # 字体大小
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) +
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labs(
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title = titleNames[1],
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x = titleNames[2],
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y = titleNames[3],
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fill = titleNames[4]
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) +
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scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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theme_minimal() + theme(
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plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
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axis.title.x = element_text(size = 12, face = "bold"),
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axis.title.y = element_text(size = 12, face = "bold"),
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axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
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legend.position = "right")
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plot1
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#return (list(plotdfDataNumber,b23,b33,b43,b53))
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}
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plotfunctionVector批次名称Log<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
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dfData<-dfData[(dfData$批次名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
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lth1<-length(dependentVariableNames)
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dfData00<-data.frame()
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for(i in 1:lth1){
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dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
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colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
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dfData00<-rbind(dfData00,dfData0)
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}
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plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, fill = Group)) +
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geom_col(
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position = position_dodge(width = 0.4), # 控制条间距
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width = 0.7 # 条宽度
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) +
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geom_line(
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aes(group = Group, color = Group),
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position = position_dodge(width = 0.4),
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size = 1,
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linetype="dashed",
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show.legend=FALSE,
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alpha = 1.0
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) +
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scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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geom_text(
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aes(label = round(Count,2)), # 标签内容
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position = position_dodge(width = 0.4), # 与柱子位置一致
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vjust = -0.4, # 垂直位置（负值向上）
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color = "black", # 标签颜色
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size = 1.2 # 字体大小
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) +
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labs(
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title = titleNames[1],
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x = titleNames[2],
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y = titleNames[3],
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fill = titleNames[4]
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) +
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scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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scale_y_log10()+
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theme_minimal() + theme(
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plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
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axis.title.x = element_text(size = 12, face = "bold"),
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axis.title.y = element_text(size = 12, face = "bold"),
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axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
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legend.position = "right")
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plot1
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#return (list(plotdfDataNumber,b23,b33,b43,b53))
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}
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plotfunctionVector项目名称<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
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dfData<-dfData[(dfData$项目名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
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lth1<-length(dependentVariableNames)
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dfData00<-data.frame()
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for(i in 1:lth1){
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dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
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colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
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dfData00<-rbind(dfData00,dfData0)
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}
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plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, fill = Group)) +
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geom_col(
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position = position_dodge(width = 0.4), # 控制条间距
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width = 0.7 # 条宽度
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) +
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geom_line(
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aes(group = Group, color = Group),
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position = position_dodge(width = 0.4),
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size = 1,
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linetype="dashed",
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show.legend=FALSE,
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alpha = 1.0
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) +
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scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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geom_text(
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aes(label = round(Count,2)), # 标签内容
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position = position_dodge(width = 0.4), # 与柱子位置一致
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||
vjust = -0.4, # 垂直位置（负值向上）
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color = "black", # 标签颜色
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size = 1.2 # 字体大小
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) +
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labs(
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title = titleNames[1],
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x = titleNames[2],
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y = titleNames[3],
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fill = titleNames[4]
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) +
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scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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theme_minimal() + theme(
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plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
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axis.title.x = element_text(size = 12, face = "bold"),
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axis.title.y = element_text(size = 12, face = "bold"),
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axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
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legend.position = "right")
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plot1
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#return (list(plotdfDataNumber,b23,b33,b43,b53))
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}
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plotfunctionVector项目名称Log<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
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dfData<-dfData[(dfData$项目名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
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lth1<-length(dependentVariableNames)
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dfData00<-data.frame()
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for(i in 1:lth1){
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dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
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colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
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dfData00<-rbind(dfData00,dfData0)
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}
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plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, fill = Group)) +
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geom_col(
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position = position_dodge(width = 0.4), # 控制条间距
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width = 0.7 # 条宽度
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) +
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geom_line(
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aes(group = Group, color = Group),
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position = position_dodge(width = 0.4),
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size = 1,
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linetype="dashed",
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show.legend=FALSE,
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alpha = 1.0
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) +
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scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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geom_text(
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aes(label = round(Count,2)), # 标签内容
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||
position = position_dodge(width = 0.4), # 与柱子位置一致
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||
vjust = -0.4, # 垂直位置（负值向上）
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||
color = "black", # 标签颜色
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||
size = 1.2 # 字体大小
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) +
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labs(
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title = titleNames[1],
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x = titleNames[2],
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y = titleNames[3],
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fill = titleNames[4]
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) +
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scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
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scale_y_log10()+
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theme_minimal() + theme(
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plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
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axis.title.x = element_text(size = 12, face = "bold"),
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axis.title.y = element_text(size = 12, face = "bold"),
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axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
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legend.position = "right")
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plot1
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#return (list(plotdfDataNumber,b23,b33,b43,b53))
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}
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plotfunctionLog<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
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lth1<-length(dependentVariableNames)
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dfData00<-data.frame()
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for(i in 1:lth1){
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dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
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colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
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dfData00<-rbind(dfData00,dfData0)
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}
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plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, fill = Group)) +
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geom_col(
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position = position_dodge(width = 0.4), # 控制条间距
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||
width = 0.7 # 条宽度
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||
) +
|
||
geom_line(
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||
aes(group = Group, color = Group),
|
||
position = position_dodge(width = 0.4),
|
||
size = 1,
|
||
linetype="dashed",
|
||
show.legend=FALSE,
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||
alpha = 1.0
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||
) +
|
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scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
|
||
geom_text(
|
||
aes(label = round(Count,2)), # 标签内容
|
||
position = position_dodge(width = 0.4), # 与柱子位置一致
|
||
vjust = -0.4, # 垂直位置（负值向上）
|
||
color = "black", # 标签颜色
|
||
size = 1.2 # 字体大小
|
||
) +
|
||
labs(
|
||
title = titleNames[1],
|
||
x = titleNames[2],
|
||
y = titleNames[3],
|
||
fill = titleNames[4]
|
||
) +
|
||
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
|
||
scale_y_log10()+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 12, face = "bold"),
|
||
axis.title.y = element_text(size = 12, face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
|
||
legend.position = "right")
|
||
|
||
plot1
|
||
#return (list(plotdfDataNumber,b23,b33,b43,b53))
|
||
|
||
}
|
||
|
||
plotfunctionVector仪器序列号Log<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
|
||
dfData<-dfData[(dfData$仪器序列号 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
|
||
lth1<-length(dependentVariableNames)
|
||
dfData00<-data.frame()
|
||
for(i in 1:lth1){
|
||
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
|
||
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
|
||
dfData00<-rbind(dfData00,dfData0)
|
||
}
|
||
|
||
plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, 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","yellow")) + # 自定义颜色
|
||
geom_text(
|
||
aes(label = round(Count,2)), # 标签内容
|
||
position = position_dodge(width = 0.4), # 与柱子位置一致
|
||
vjust = -0.4, # 垂直位置（负值向上）
|
||
color = "black", # 标签颜色
|
||
size = 1.2 # 字体大小
|
||
) +
|
||
labs(
|
||
title = titleNames[1],
|
||
x = titleNames[2],
|
||
y = titleNames[3],
|
||
fill = titleNames[4]
|
||
) +
|
||
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
|
||
scale_y_log10()+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 12, face = "bold"),
|
||
axis.title.y = element_text(size = 12, face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
|
||
legend.position = "right")
|
||
|
||
plot1
|
||
#return (list(plotdfDataNumber,b23,b33,b43,b53))
|
||
|
||
}
|
||
|
||
panelPlotByDayAndLocation<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
|
||
lth1<-length(dependentVariableNames)
|
||
dfData00<-data.frame()
|
||
for(i in 1:lth1){
|
||
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
|
||
colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
|
||
dfData00<-rbind(dfData00,dfData0)
|
||
}
|
||
dfData00<-dfData00[dfData00$省编号 %in% choosenList,]
|
||
dfData00$省编号<-factor(dfData00$省编号,levels = choosenList)
|
||
|
||
plot1<-ggplot(dfData00, aes(x = testDay, y = Count, fill = Group)) +
|
||
geom_col(
|
||
position = position_dodge(width = 0.4), # 控制条间距
|
||
width = 0.7 # 条宽度
|
||
) +
|
||
geom_line(
|
||
aes(group = Group, color = Group),
|
||
position = position_dodge(width = 0.4),
|
||
size = 1,
|
||
linetype="dashed",
|
||
show.legend=FALSE,
|
||
alpha = 1.0
|
||
) +
|
||
scale_color_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
|
||
geom_text(
|
||
aes(label = round(Count,2)), # 标签内容
|
||
position = position_dodge(width = 0.4), # 与柱子位置一致
|
||
vjust = -0.4, # 垂直位置（负值向上）
|
||
color = "black", # 标签颜色
|
||
size = 1.2 # 字体大小
|
||
) +
|
||
facet_wrap( ~ 省编号,ncol=2) +
|
||
labs(
|
||
title = titleNames[1],
|
||
x = titleNames[2],
|
||
y = titleNames[3],
|
||
fill = titleNames[4]
|
||
) +
|
||
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 12, face = "bold"),
|
||
axis.title.y = element_text(size = 12, face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
|
||
panel.border = element_rect(
|
||
color = "black", # 边框颜色
|
||
size = 1., # 边框粗细
|
||
linetype = "solid", # 线型（solid/dashed/dotted）
|
||
fill = NA # 填充色（NA为透明）
|
||
),
|
||
legend.position = "right")
|
||
plot1
|
||
}
|
||
|
||
panelPlotByMonthAndLocation<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
|
||
lth1<-length(dependentVariableNames)
|
||
dfData00<-data.frame()
|
||
for(i in 1:lth1){
|
||
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
|
||
colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
|
||
dfData00<-rbind(dfData00,dfData0)
|
||
}
|
||
dfData00<-dfData00[dfData00$省编号 %in% choosenList,]
|
||
dfData00$省编号<-factor(dfData00$省编号,levels = choosenList)
|
||
|
||
plot1<-ggplot(dfData00, aes(x = testMonth, y = Count, 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","yellow")) + # 自定义颜色
|
||
geom_text(
|
||
aes(label = round(Count,2)), # 标签内容
|
||
position = position_dodge(width = 0.4), # 与柱子位置一致
|
||
vjust = -0.4, # 垂直位置（负值向上）
|
||
color = "black", # 标签颜色
|
||
size = 1.2 # 字体大小
|
||
) +
|
||
facet_wrap( ~ 省编号,ncol=2) +
|
||
labs(
|
||
title = titleNames[1],
|
||
x = titleNames[2],
|
||
y = titleNames[3],
|
||
fill = titleNames[4]
|
||
) +
|
||
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 12, face = "bold"),
|
||
axis.title.y = element_text(size = 12, face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
|
||
panel.border = element_rect(
|
||
color = "black", # 边框颜色
|
||
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")
|
||
plot1
|
||
}
|
||
|
||
pointPlotfunction批次<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
|
||
|
||
plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],color=as.character(批次名称)))+
|
||
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
|
||
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
|
||
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
|
||
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
|
||
labs(
|
||
title = titleNames[1], # 主标题
|
||
x = titleNames[2], # X轴标签
|
||
y = titleNames[3], # Y轴标签
|
||
color = titleNames[4] # 图例标题
|
||
)+
|
||
# scale_x_date(
|
||
# date_labels = "%Y-%m-%d", # 格式符组合
|
||
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
|
||
# )+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 10,face = "bold"),
|
||
axis.title.y = element_text(size = 10,face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90),
|
||
legend.position = "right")
|
||
|
||
plot2
|
||
|
||
}
|
||
|
||
pointPlotfunction批次Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
|
||
|
||
plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],color=as.character(批次名称)))+
|
||
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
|
||
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
|
||
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
|
||
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
|
||
labs(
|
||
title = titleNames[1], # 主标题
|
||
x = titleNames[2], # X轴标签
|
||
y = titleNames[3], # Y轴标签
|
||
color = titleNames[4] # 图例标题
|
||
)+
|
||
# scale_x_date(
|
||
# date_labels = "%Y-%m-%d", # 格式符组合
|
||
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
|
||
# )+
|
||
scale_y_log10()+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 10,face = "bold"),
|
||
axis.title.y = element_text(size = 10,face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90),
|
||
legend.position = "right")
|
||
|
||
plot2
|
||
|
||
}
|
||
|
||
pointPlotfunction仪器<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
|
||
|
||
plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],color=as.character(仪器序列号)))+
|
||
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
|
||
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
|
||
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
|
||
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
|
||
labs(
|
||
title = titleNames[1], # 主标题
|
||
x = titleNames[2], # X轴标签
|
||
y = titleNames[3], # Y轴标签
|
||
color = titleNames[4] # 图例标题
|
||
)+
|
||
# scale_x_date(
|
||
# date_labels = "%Y-%m-%d", # 格式符组合
|
||
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
|
||
# )+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 10,face = "bold"),
|
||
axis.title.y = element_text(size = 10,face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90),
|
||
legend.position = "right")
|
||
|
||
plot2
|
||
|
||
}
|
||
|
||
pointPlotfunction仪器Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
|
||
|
||
plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],color=as.character(仪器序列号)))+
|
||
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
|
||
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
|
||
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
|
||
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
|
||
labs(
|
||
title = titleNames[1], # 主标题
|
||
x = titleNames[2], # X轴标签
|
||
y = titleNames[3], # Y轴标签
|
||
color = titleNames[4] # 图例标题
|
||
)+
|
||
# scale_x_date(
|
||
# date_labels = "%Y-%m-%d", # 格式符组合
|
||
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
|
||
# )+
|
||
scale_y_log10()+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 10,face = "bold"),
|
||
axis.title.y = element_text(size = 10,face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90),
|
||
legend.position = "right")
|
||
|
||
plot2
|
||
|
||
}
|
||
|
||
pointPlotfunction样本<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
|
||
|
||
plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],color=as.character(样本类型)))+
|
||
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
|
||
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
|
||
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
|
||
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
|
||
labs(
|
||
title = titleNames[1], # 主标题
|
||
x = titleNames[2], # X轴标签
|
||
y = titleNames[3], # Y轴标签
|
||
color = titleNames[4] # 图例标题
|
||
)+
|
||
# scale_x_date(
|
||
# date_labels = "%Y-%m-%d", # 格式符组合
|
||
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
|
||
# )+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 10,face = "bold"),
|
||
axis.title.y = element_text(size = 10,face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90),
|
||
legend.position = "right")
|
||
|
||
plot2
|
||
|
||
}
|
||
|
||
pointPlotfunction样本Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
|
||
|
||
plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],color=as.character(样本类型)))+
|
||
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
|
||
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
|
||
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
|
||
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
|
||
labs(
|
||
title = titleNames[1], # 主标题
|
||
x = titleNames[2], # X轴标签
|
||
y = titleNames[3], # Y轴标签
|
||
color = titleNames[4] # 图例标题
|
||
)+
|
||
# scale_x_date(
|
||
# date_labels = "%Y-%m-%d", # 格式符组合
|
||
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
|
||
# )+
|
||
scale_y_log10()+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 10,face = "bold"),
|
||
axis.title.y = element_text(size = 10,face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90),
|
||
legend.position = "right")
|
||
|
||
plot2
|
||
|
||
}
|
||
|
||
pointPlotfunction项目<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
|
||
|
||
plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],color=as.character(项目名称)))+
|
||
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
|
||
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
|
||
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
|
||
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
|
||
labs(
|
||
title = titleNames[1], # 主标题
|
||
x = titleNames[2], # X轴标签
|
||
y = titleNames[3], # Y轴标签
|
||
color = titleNames[4] # 图例标题
|
||
)+
|
||
# scale_x_date(
|
||
# date_labels = "%Y-%m-%d", # 格式符组合
|
||
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
|
||
# )+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 10,face = "bold"),
|
||
axis.title.y = element_text(size = 10,face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90),
|
||
legend.position = "right")
|
||
|
||
plot2
|
||
|
||
}
|
||
|
||
pointPlotfunction项目Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
|
||
|
||
plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],color=as.character(项目名称)))+
|
||
# geom_line(aes(testDay,浓度1移动均值),color="blue")+
|
||
# geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
|
||
# geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
|
||
# xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
|
||
labs(
|
||
title = titleNames[1], # 主标题
|
||
x = titleNames[2], # X轴标签
|
||
y = titleNames[3], # Y轴标签
|
||
color = titleNames[4] # 图例标题
|
||
)+
|
||
# scale_x_date(
|
||
# date_labels = "%Y-%m-%d", # 格式符组合
|
||
# date_breaks = "1 month" # 标签间隔（如 "2 weeks"）
|
||
# )+
|
||
scale_y_log10()+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 10,face = "bold"),
|
||
axis.title.y = element_text(size = 10,face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90),
|
||
legend.position = "right")
|
||
|
||
plot2
|
||
|
||
}
|
||
|
||
plotfunctionByDay<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
|
||
lth1<-length(dependentVariableNames)
|
||
dfData00<-data.frame()
|
||
for(i in 1:lth1){
|
||
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
|
||
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
|
||
dfData00<-rbind(dfData00,dfData0)
|
||
}
|
||
|
||
plot1<-ggplot(dfData00, aes(x = testDay, y = Count, 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","yellow")) + # 自定义颜色
|
||
geom_text(
|
||
aes(label = round(Count,2)), # 标签内容
|
||
position = position_dodge(width = 0.4), # 与柱子位置一致
|
||
vjust = -0.4, # 垂直位置（负值向上）
|
||
color = "black", # 标签颜色
|
||
size = 1.2 # 字体大小
|
||
) +
|
||
labs(
|
||
title = titleNames[1],
|
||
x = titleNames[2],
|
||
y = titleNames[3],
|
||
fill = titleNames[4]
|
||
) +
|
||
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 12, face = "bold"),
|
||
axis.title.y = element_text(size = 12, face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
|
||
legend.position = "right")
|
||
|
||
plot1
|
||
#return (list(plotdfDataNumber,b23,b33,b43,b53))
|
||
|
||
}
|
||
|
||
plotfunctionBy区域<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
|
||
lth1<-length(dependentVariableNames)
|
||
dfData00<-data.frame()
|
||
for(i in 1:lth1){
|
||
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
|
||
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
|
||
dfData00<-rbind(dfData00,dfData0)
|
||
}
|
||
|
||
plot1<-ggplot(dfData00, aes(x = 省编号, y = Count, 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","yellow")) + # 自定义颜色
|
||
geom_text(
|
||
aes(label = round(Count,2)), # 标签内容
|
||
position = position_dodge(width = 0.4), # 与柱子位置一致
|
||
vjust = -0.4, # 垂直位置（负值向上）
|
||
color = "black", # 标签颜色
|
||
size = 1.2 # 字体大小
|
||
) +
|
||
labs(
|
||
title = titleNames[1],
|
||
x = titleNames[2],
|
||
y = titleNames[3],
|
||
fill = titleNames[4]
|
||
) +
|
||
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 12, face = "bold"),
|
||
axis.title.y = element_text(size = 12, face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
|
||
legend.position = "right")
|
||
|
||
plot1
|
||
#return (list(plotdfDataNumber,b23,b33,b43,b53))
|
||
|
||
}
|
||
|
||
plotfunctionBy仪器<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
|
||
lth1<-length(dependentVariableNames)
|
||
dfData00<-data.frame()
|
||
for(i in 1:lth1){
|
||
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
|
||
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
|
||
dfData00<-rbind(dfData00,dfData0)
|
||
}
|
||
|
||
plot1<-ggplot(dfData00, aes(x = 仪器序列号, y = Count, 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","yellow")) + # 自定义颜色
|
||
geom_text(
|
||
aes(label = round(Count,2)), # 标签内容
|
||
position = position_dodge(width = 0.4), # 与柱子位置一致
|
||
vjust = -0.4, # 垂直位置（负值向上）
|
||
color = "black", # 标签颜色
|
||
size = 1.2 # 字体大小
|
||
) +
|
||
labs(
|
||
title = titleNames[1],
|
||
x = titleNames[2],
|
||
y = titleNames[3],
|
||
fill = titleNames[4]
|
||
) +
|
||
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 12, face = "bold"),
|
||
axis.title.y = element_text(size = 12, face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
|
||
legend.position = "right")
|
||
|
||
plot1
|
||
#return (list(plotdfDataNumber,b23,b33,b43,b53))
|
||
|
||
}
|
||
|
||
plotfunctionBy仪器Log<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
|
||
lth1<-length(dependentVariableNames)
|
||
dfData00<-data.frame()
|
||
for(i in 1:lth1){
|
||
dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
|
||
colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
|
||
dfData00<-rbind(dfData00,dfData0)
|
||
}
|
||
|
||
plot1<-ggplot(dfData00, aes(x = 仪器序列号, y = Count, 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","yellow")) + # 自定义颜色
|
||
geom_text(
|
||
aes(label = round(Count,2)), # 标签内容
|
||
position = position_dodge(width = 0.4), # 与柱子位置一致
|
||
vjust = -0.4, # 垂直位置（负值向上）
|
||
color = "black", # 标签颜色
|
||
size = 1.2 # 字体大小
|
||
) +
|
||
labs(
|
||
title = titleNames[1],
|
||
x = titleNames[2],
|
||
y = titleNames[3],
|
||
fill = titleNames[4]
|
||
) +
|
||
scale_fill_manual(values = c("red", "blue","green","yellow")) + # 自定义颜色
|
||
scale_y_log10()+
|
||
theme_minimal() + theme(
|
||
plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
|
||
axis.title.x = element_text(size = 12, face = "bold"),
|
||
axis.title.y = element_text(size = 12, face = "bold"),
|
||
axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
|
||
legend.position = "right")
|
||
|
||
plot1
|
||
#return (list(plotdfDataNumber,b23,b33,b43,b53))
|
||
|
||
}
|
||
|
||
running_avg <- function(x, window = 3) {
|
||
sapply(seq_along(x), function(i) {
|
||
start <- max(1, i - window + 1)
|
||
mean(x[start:i],na.rm=TRUE)
|
||
})
|
||
}
|
||
|
||
lumping_avg<- function(x,window = 100) {
|
||
sapply(seq_along(x), function(i) {
|
||
start <- max(1, i - window + 1)
|
||
mean(x[start:i],na.rm=TRUE)
|
||
})
|
||
}
|
||
|
||
lumping_sd<- function(x,window = 100) {
|
||
sapply(seq_along(x), function(i) {
|
||
start <- max(1, i - window + 1)
|
||
sd(x[start:i],na.rm=TRUE)
|
||
})
|
||
}
|
||
|
||
rep6<-rep(1,6)
|
||
rep50<-rep(1,50)
|
||
rep0<-rep6
|
||
for(i in 1:1000) rep0<-c(rep0,rep6+i)
|
||
rep00<-rep50
|
||
for(i in 1:100) rep00<-c(rep00,rep50+i)
|
||
|
||
if(FALSE){
|
||
csv_files <- list.files(pattern = "\\UTF.csv$")
|
||
|
||
df00<-data.frame()
|
||
|
||
for(i in 1:length(csv_files)) {
|
||
#guess_encoding("historyRecord20.csv") # [[1]]$encoding
|
||
#df2 <- fread("historyRecord20250604175205UTF.csv",encoding = "UTF-8",fill = TRUE)
|
||
# df22 <- read.csv(csv_files[i],encoding = "UTF-8",fill = TRUE)
|
||
# colnames(df22)
|
||
# summary(df22)
|
||
df2 <- read.csv(csv_files[i],encoding = "UTF-8",fill = TRUE)
|
||
df2$批次名称<-as.character(df2$批次名称)
|
||
df2<-df2[!is.na(df2$批次名称),]
|
||
|
||
df2$是否阳性<-df2$结论
|
||
df2$是否阳性[df2$是否阳性=="阳性"]<-1.0
|
||
df2$是否阳性[df2$是否阳性=="阴性"]<-0.0
|
||
df2$是否阳性[df2$是否阳性=="无效"]<-0.5
|
||
df2$是否阳性<-as.numeric(df2$是否阳性)
|
||
df2$是否阳性[is.na(df2$是否阳性)]<-0.5
|
||
|
||
df2$结论[df2$结论=="阳性"]<-1.0
|
||
df2$结论[df2$结论=="阴性"]<-0.0
|
||
df2$结论<-as.numeric(df2$结论)
|
||
|
||
df2$是否有效<-1
|
||
df2$是否有效[df2$是否阳性==0.5]<-0
|
||
|
||
df00<-rbind(df00,df2)
|
||
}
|
||
write_excel_csv(df00,file="history06092025.csv")
|
||
|
||
df2<-df00
|
||
|
||
}
|
||
if(FALSE){
|
||
series<-read.csv("荧光层析设备1.csv",encoding = "UTF-8",fill = TRUE)
|
||
series1<-read.csv("FIC-Q100N.csv",encoding = "UTF-8",fill = TRUE)
|
||
series0<-series$仪器序列号[series$仪器序列号 %in% 仪器号List$仪器序列号]
|
||
series00<-series$仪器编号[series$仪器编号 %in% series1$仪器编号]
|
||
colnames(series[,1:13])
|
||
colnames(series1[,3:11])
|
||
仪器编号和序列号<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=FALSE)
|
||
#仪器编号和序列号all<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=TRUE)
|
||
colnames(仪器编号和序列号)
|
||
仪器编号和序列号$SIM卡号<- gsub("\t", " ", 仪器编号和序列号$SIM卡号)
|
||
仪器编号和序列号$返利表序号<- gsub("\n", "_", 仪器编号和序列号$返利表序号)
|
||
#仪器编号和序列号all$SIM卡号<- gsub("\t", " ", 仪器编号和序列号all$SIM卡号)
|
||
#仪器编号和序列号all$返利表序号<- gsub("\n", "_", 仪器编号和序列号all$返利表序号)
|
||
#仪器编号和序列号[仪器编号和序列号$仪器序列号=="781be43bb68f05bb",]
|
||
|
||
cname0<-c("仪器编号" , "仪器序列号" ,
|
||
"SIM卡号" , "发货时间" , "仪器类型" ,
|
||
"总测试量" , "最后一次开机时间" ,"时间差" ,
|
||
"开机地点" , "网络类型" , "ip地址" ,
|
||
"用户" , "用户CRM" , "返利表序号" ,
|
||
"申请日期" , "区域" , "客户编码" ,
|
||
"代理商名称" , "用户名称" , "规格" ,
|
||
"状态")
|
||
#write_excel_csv(仪器编号和序列号all[,cname0],file="仪器编号和序列号all.csv")
|
||
write_excel_csv(仪器编号和序列号[,cname0],file="仪器编号和序列号.csv")
|
||
}
|
||
|
||
mydb = dbConnect(MySQL(), user='root', password='My9521$$', dbname='和迈', host='192.168.11.223')
|
||
dbListTables(mydb)
|
||
#dbListFields(mydb, '测试数据')
|
||
|
||
#仪器编号和序列号all<-read.csv("仪器编号和序列号all.csv",encoding = "UTF-8",fill = TRUE)
|
||
|
||
#仪器编号和序列号<-read.csv("仪器编号和序列号.csv",encoding = "UTF-8",fill = TRUE)
|
||
rs = dbSendQuery(mydb, "select * from 和迈.仪器编号和序列号 ")
|
||
仪器编号和序列号 = fetch(rs, n=-1)
|
||
colnames(仪器编号和序列号)
|
||
#仪器编号和序列号<-distinct(仪器编号和序列号[,2:22])
|
||
#仪器编号和序列号<-read.csv("仪器编号和序列号.csv",encoding = "UTF-8",fill = TRUE)
|
||
|
||
rs = dbSendQuery(mydb, "select * from 和迈.和迈测试数据 ")
|
||
df2 = fetch(rs, n=-1)
|
||
dbDisconnect(mydb)
|
||
|
||
#df2 = fetch(rs, n=-1)
|
||
#df2 <- read.csv("history06092025.csv",encoding = "UTF-8",fill = TRUE)
|
||
colnames(df2)
|
||
cname00<-c( "序号" , "项目号" , "批次号" , "样品编号" ,
|
||
"项目名称" , "批次名称" , "测试时间" , "浓度1" ,
|
||
"结论" , "C值" , "T值" , "浓度2" ,
|
||
"浓度3" , "结论2" , "结论3" , "样本类型" ,
|
||
"省市编号" , "仪器序列号" , "T2值" , "T3值" ,
|
||
"仪器备注名称", "仪器投放区域", "详细地址")
|
||
df2<-distinct(df2[,cname00])
|
||
df2$批次名称<-as.character(df2$批次名称)
|
||
df2<-df2[!is.na(df2$批次名称),]
|
||
|
||
df2$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
|
||
df2$省编号<-(df2$省市编号 %/% 10000)*10000
|
||
df2$省名<-str_sub(df2$详细地址,1,3)
|
||
df2$省名[str_length(df2$省名)<3]<-NA
|
||
|
||
Numberof项目号<-length(unique(df2$项目号))
|
||
Numberof批次号<-length(unique(df2$批次号))
|
||
Numberof样品编号<-length(unique(df2$样品编号))
|
||
Numberof项目名称<-length(unique(df2$项目名称))
|
||
Numberof批次名称<-length(unique(df2$批次名称))
|
||
Numberof省编号<-length(unique(df2$省编号))
|
||
Numberof省名<-length(unique(df2$省名))
|
||
Numberof省市编号<-length(unique(df2$省市编号))
|
||
Numberof仪器序列号<-length(unique(df2$仪器序列号))
|
||
Numberof详细地址<-length(unique(df2$详细地址))
|
||
Numberof仪器备注名称<-length(unique(df2$仪器备注名称))
|
||
Numberof仪器投放区域<-length(unique(df2$仪器投放区域))
|
||
Numberof样本类型<-length(unique(df2$样本类型))
|
||
|
||
省编号and省名<-cbind(df2$省编号,df2$省名)
|
||
省编号and省名<-省编号and省名[!duplicated(省编号and省名),]
|
||
|
||
summaryTable<-stri_join("Numberof测试: ",as.character(nrow(df2)),
|
||
"\nNumberof项目名称: ", as.character(Numberof项目名称),
|
||
"\nNumberof批次号: ",as.character(Numberof批次号), " \n",
|
||
"Numberof样品编号： ",as.character(Numberof样品编号)," \n",
|
||
"Numberof批次名称: ",as.character(Numberof批次名称)," \n",
|
||
"Numberof省编号: ",as.character(Numberof省编号)," \n",
|
||
"Numberof省市编号: ",as.character(Numberof省市编号)," \n",
|
||
"Numberof仪器序列号: ",as.character(Numberof仪器序列号)," \n",
|
||
"Numberof详细地址: ",as.character(Numberof详细地址)," \n",
|
||
"Numberof样本类型: ",as.character(Numberof样本类型)," \n",sep="")
|
||
|
||
|
||
|
||
summary(df2$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$批次名称)
|
||
|
||
|
||
colnames(df2)
|
||
#colnames(df00)
|
||
#df200<-df20
|
||
summary(df2$仪器序列号)
|
||
summary(df2$批次名称)
|
||
|
||
|
||
df20<-df2 #[,c(1:11,16,17,20)]
|
||
df20$省编号<-str_c("省编号: ",df20$省编号)
|
||
df20<-df20[complete.cases(df20$测试时间), ]
|
||
|
||
colnames(df20)
|
||
|
||
df20$浓度1<-as.numeric(df20$浓度1)
|
||
df20$C值<-as.numeric(df20$C值)
|
||
df20$T值<-as.numeric(df20$T值)
|
||
df20$ToverC值<-df20$T值/df20$C值
|
||
df20$ToverC值[df20$是否有效==0]<-NA
|
||
|
||
summary(as.numeric(df20$结论))
|
||
summary(df20$浓度1)
|
||
summary(df20$ToverC值)
|
||
|
||
summary(df20$testTimeFromeBegining)
|
||
colnames(df20)
|
||
|
||
|
||
df20$testMonth<-str_sub(df20$测试时间,1,7)
|
||
|
||
#df20$testMonthinNumber<-as.numeric(str_c(str_sub(df20$测试时间,1,4),str_sub(df20$测试时间,6,7)))
|
||
|
||
df20$testDay<-as.Date(str_sub(df20$测试时间,1,10))
|
||
df20<-df20[df20$testDay<=Sys.Date(), ]
|
||
|
||
df20<-df20[complete.cases(df20$testDay), ]
|
||
|
||
summary(df20$testDay)
|
||
|
||
df20$testTime<-as.datetime(str_sub(df20$测试时间,1,19),format='%Y-%m-%d %H:%M:%S')
|
||
|
||
duration<-(max(df20$testTime,na.rm = TRUE)-min(df20$testTime,na.rm = TRUE))/(60.*60.*24.)
|
||
|
||
df20$testTimeFromeToday<-(max(df20$testTime,na.rm = TRUE)-df20$testTime)/(60.*60.*24.)+1.
|
||
#max0<-max(df20$testTime,na.rm=TRUE)
|
||
#min0<-min(df20$testTime,na.rm=TRUE)
|
||
|
||
#unique(dfBy样本$样本类型)
|
||
#max0-min0
|
||
|
||
#max(df20$testDay,na.rm=TRUE)
|
||
#min(df20$testDay,na.rm=TRUE)
|
||
|
||
|
||
|
||
summary(df20$testTimeFromeToday)
|
||
dayMax<-max(df20$testTimeFromeToday,na.rm = TRUE)
|
||
df2000<-df20
|
||
df20<-df20[df20$testTimeFromeToday<=730,]
|
||
#df20<-df20[complete.cases(df20$测试时间), ]
|
||
lastDay<-max(df20$testDay,na.rm = TRUE)
|
||
df20dayLast21<-df20[lastDay-df20$testDay<21,]
|
||
|
||
dfByDay <- df2000 %>% group_by(testMonth,testDay) %>% summarise(
|
||
测试数 = n(),
|
||
阳性数=sum(结论,na.rm = TRUE),
|
||
有效数=sum(是否有效,na.rm = TRUE),
|
||
样本数=length(unique(样本类型)),
|
||
项目数=length(unique(项目名称)),
|
||
仪器数=length(unique(仪器序列号)),
|
||
批次数=length(unique(批次名称)),
|
||
市数=length(unique(省市编号)),
|
||
省数=length(unique(省编号))
|
||
)
|
||
dfByDay$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$有效数)
|
||
dfByDay$省数<-as.integer(dfByDay$省数)
|
||
dfByDay <- dfByDay[order(dfByDay$testDay),]
|
||
#dfByDay<-dfByDay[lastDay-dfByDay$testDay<=21,]
|
||
|
||
write_excel_csv(dfByDay,file="按日统计0.csv")
|
||
|
||
dfByMonth <- df2000 %>% group_by(testMonth) %>% summarise(
|
||
测试数 = n(),
|
||
阳性数=sum(结论,na.rm = TRUE),
|
||
有效数=sum(是否有效,na.rm = TRUE),
|
||
样本数=length(unique(样本类型)),
|
||
项目数=length(unique(项目名称)),
|
||
仪器数=length(unique(仪器序列号)),
|
||
批次数=length(unique(批次名称)),
|
||
市数=length(unique(省市编号)),
|
||
省数=length(unique(省编号))
|
||
)
|
||
dfByMonth$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$有效数)
|
||
dfByMonth$省数<-as.integer(dfByMonth$省数)
|
||
dfByMonth <- dfByMonth[order(dfByMonth$testMonth),]
|
||
dfByMonth <- dfByMonth[nrow(dfByMonth):1,]
|
||
|
||
write_excel_csv(dfByMonth,file="按月统计0.csv")
|
||
|
||
dfBy项目 <- df2000 %>% group_by(项目名称) %>% summarise(
|
||
仪器数=length(unique(仪器序列号)),
|
||
批次数=length(unique(批次名称)),
|
||
样本数=length(unique(样本类型)),
|
||
省数=length(unique(省编号)),
|
||
市数=length(unique(省市编号)),
|
||
测试数 = n(),
|
||
阳性数=sum(结论,na.rm = TRUE),
|
||
有效数=sum(是否有效,na.rm = TRUE),
|
||
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
|
||
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
|
||
)
|
||
dfBy项目$阳性率<-dfBy项目$阳性数/dfBy项目$有效数
|
||
dfBy项目$有效率<-dfBy项目$有效数/dfBy项目$测试数
|
||
dfBy项目$阳性数<-as.integer(dfBy项目$阳性数)
|
||
dfBy项目$测试数<-as.integer(dfBy项目$测试数)
|
||
dfBy项目$有效数<-as.integer(dfBy项目$有效数)
|
||
dfBy项目 <- dfBy项目[order(-dfBy项目$测试数),]
|
||
write_excel_csv(dfBy项目,file="按项目统计0.csv")
|
||
|
||
dfBy样本 <- df2000 %>% group_by(样本类型) %>% summarise(
|
||
仪器数=length(unique(仪器序列号)),
|
||
批次数=length(unique(批次名称)),
|
||
项目数=length(unique(项目名称)),
|
||
省数=length(unique(省编号)),
|
||
市数=length(unique(省市编号)),
|
||
测试数 = n(),
|
||
阳性数=sum(结论,na.rm = TRUE),
|
||
有效数=sum(是否有效,na.rm = TRUE),
|
||
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
|
||
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
|
||
)
|
||
dfBy样本$阳性率<-dfBy样本$阳性数/dfBy样本$有效数
|
||
dfBy样本$有效率<-dfBy样本$有效数/dfBy样本$测试数
|
||
dfBy样本$阳性数<-as.integer(dfBy样本$阳性数)
|
||
dfBy样本$测试数<-as.integer(dfBy样本$测试数)
|
||
dfBy样本$有效数<-as.integer(dfBy样本$有效数)
|
||
dfBy样本 <- dfBy样本[order(-dfBy样本$测试数),]
|
||
write_excel_csv(dfBy样本,file="按样本统计0.csv")
|
||
|
||
dfBy区域 <- df2000 %>% group_by(省编号) %>% summarise(
|
||
仪器数=length(unique(仪器序列号)),
|
||
批次数=length(unique(批次名称)),
|
||
样本数=length(unique(样本类型)),
|
||
项目数=length(unique(项目名称)),
|
||
市数=length(unique(省市编号)),
|
||
测试数 = n(),
|
||
阳性数=sum(结论,na.rm = TRUE),
|
||
有效数=sum(是否有效,na.rm = TRUE),
|
||
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
|
||
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
|
||
)
|
||
dfBy区域$阳性率<-dfBy区域$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区域 <- dfBy区域[order(-dfBy区域$测试数),]
|
||
write_excel_csv(dfBy区域,file="按区域统计0.csv")
|
||
|
||
dfBy批次 <- df2000 %>% group_by(批次名称) %>% summarise(
|
||
仪器数=length(unique(仪器序列号)),
|
||
测试数 = n(),
|
||
省数=length(unique(省编号)),
|
||
市数=length(unique(省市编号)),
|
||
样本数=length(unique(样本类型)),
|
||
项目数=length(unique(项目名称)),
|
||
阳性数=sum(结论,na.rm = TRUE),
|
||
有效数=sum(是否有效,na.rm = TRUE),
|
||
最早测试=min(testDay,na.rm = TRUE),
|
||
最近测试=max(testDay,na.rm = TRUE),
|
||
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
|
||
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
|
||
)
|
||
dfBy批次$阳性率<-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$有效数)
|
||
dfBy批次$省数<-as.integer(dfBy批次$省数)
|
||
dfBy批次 <- dfBy批次[order(-dfBy批次$测试数),]
|
||
write_excel_csv(dfBy批次,file="按批次统计0.csv")
|
||
|
||
df20001<-cbind(df2000,IDIndex=1:nrow(df2000))
|
||
dfBy仪器 <- df20001 %>% group_by(仪器序列号) %>% summarise(
|
||
批次数=length(unique(批次名称)),
|
||
测试数 = n(),
|
||
样本数=length(unique(样本类型)),
|
||
项目数=length(unique(项目名称)),
|
||
阳性数=sum(结论,na.rm = TRUE),
|
||
有效数=sum(是否有效,na.rm = TRUE),
|
||
earliestIndex=min(IDIndex),
|
||
medianIndex=median(IDIndex),
|
||
latestIndex=max(IDIndex),
|
||
最早测试=min(testDay,na.rm = TRUE),
|
||
最近测试=max(testDay,na.rm = TRUE),
|
||
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
|
||
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
|
||
)
|
||
dfBy仪器$阳性率<-dfBy仪器$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$最早测试地点<-df2000$详细地址[dfBy仪器$earliestIndex]
|
||
dfBy仪器$中期测试地点<-df2000$详细地址[dfBy仪器$medianIndex]
|
||
dfBy仪器$最后测试地点<-df2000$详细地址[dfBy仪器$latestIndex]
|
||
dfBy仪器 <- dfBy仪器[order(-dfBy仪器$测试数),]
|
||
write_excel_csv(dfBy仪器,file="按仪器统计0.csv")
|
||
|
||
cname0<-c( "仪器序列号" ,"仪器编号" ,"最早测试地点","中期测试地点", "最后测试地点",
|
||
"开机地点" , "批次数" , "测试数" , "样本数" , "项目数" ,
|
||
"阳性数", "有效数" , "最早测试" , "最近测试" , "测试开始" ,
|
||
"测试截止", "阳性率" , "有效率",
|
||
"SIM卡号" , "发货时间" , "仪器类型" ,
|
||
"总测试量" , "最后一次开机时间" ,"时间差" ,
|
||
"网络类型" , "ip地址" ,
|
||
"用户" , "用户CRM" , "返利表序号" ,
|
||
"申请日期" , "区域" , "客户编码" ,
|
||
"代理商名称" , "用户名称" , "规格" ,
|
||
"状态")
|
||
colnames(dfBy仪器)
|
||
dfBy仪器andInf<-merge(dfBy仪器,仪器编号和序列号,by="仪器序列号",all.x=TRUE,all.y=FALSE)
|
||
colnames(dfBy仪器andInf)
|
||
dfBy仪器andInf <- dfBy仪器andInf[order(-dfBy仪器andInf$测试截止),][,cname0]
|
||
#dfBy仪器andInf0<-distinct(dfBy仪器andInf)
|
||
write_excel_csv(dfBy仪器andInf,file="仪器统计andInf.csv")
|
||
dfBy仪器andInfall<-merge(dfBy仪器,仪器编号和序列号,by="仪器序列号",all.x=TRUE,all.y=TRUE)
|
||
dfBy仪器andInfall <- dfBy仪器andInfall[order(-dfBy仪器andInfall$测试截止),][,cname0]
|
||
#dfBy仪器andInfall0<-distinct(dfBy仪器andInfall)
|
||
write_excel_csv(dfBy仪器andInfall,file="仪器统计andInfall.csv")
|
||
colnames(仪器编号和序列号)
|
||
notFound<-仪器编号和序列号[!(仪器编号和序列号$仪器序列号 %in% dfBy仪器$仪器序列号),]
|
||
|
||
colnames(notFound)
|
||
|
||
cname1<-c( "仪器序列号" ,"仪器编号" ,
|
||
"开机地点" ,
|
||
"SIM卡号" , "发货时间" , "仪器类型" ,
|
||
"总测试量" , "最后一次开机时间" ,"时间差" ,
|
||
"网络类型" , "ip地址" ,
|
||
"用户" , "用户CRM" , "返利表序号" ,
|
||
"申请日期" , "区域" , "客户编码" ,
|
||
"代理商名称" , "用户名称" , "规格" ,
|
||
"状态")
|
||
#notFound[,cname1]
|
||
#notFound0<-distinct(notFound)
|
||
write_excel_csv(notFound[,cname1],file="仪器统计Notfound.csv")
|
||
|
||
if(FALSE) {
|
||
CRMNotFound <- read.csv("CRMNotFound.csv",encoding = "UTF-8",fill = TRUE)
|
||
NoTestSince05012025 <- read.csv("NoTestSince05012025.csv",encoding = "UTF-8",fill = TRUE)
|
||
colnames(CRMNotFound)[c(3,4,5)]<-c("销售申请时间NoCRM","销售申请区域NoCRM","销售申请时代理商名称NoCRM")
|
||
colnames(NoTestSince05012025) [9]<-"备注NoTest"
|
||
|
||
feedbackData<-merge(CRMNotFound,NoTestSince05012025,by="仪器编号",all.x=TRUE,all.y=TRUE)
|
||
colnames(feedbackData)
|
||
colnames(feedbackData)[10]<-"用户onCRM"
|
||
|
||
write_excel_csv(feedbackData,file="feedbackData07042025.csv")
|
||
仪器编号和序列号feedbackData<-merge(仪器编号和序列号,feedbackData,by="仪器编号",all.x=TRUE,all.y=TRUE)
|
||
colnames(仪器编号和序列号feedbackData)
|
||
|
||
dfBy仪器feedbackDataandInf<-merge(dfBy仪器,仪器编号和序列号feedbackData,by="仪器序列号",all.x=TRUE,all.y=FALSE)
|
||
colnames(dfBy仪器feedbackDataandInf)
|
||
cname0<-c( "仪器序列号" ,"仪器编号" ,"最早测试地点","中期测试地点", "最后测试地点",
|
||
"开机地点" , "批次数" , "测试数" , "样本数" , "项目数" ,
|
||
"阳性数", "有效数" , "最早测试" , "最近测试" , "测试开始" ,
|
||
"测试截止", "阳性率" , "有效率",
|
||
"SIM卡号" , "发货时间" , "仪器类型" ,
|
||
"总测试量" , "最后一次开机时间" ,"时间差" ,
|
||
"网络类型" , "ip地址" ,
|
||
"用户" , "用户CRM" , "返利表序号" ,
|
||
"申请日期" , "区域" , "客户编码" ,
|
||
"代理商名称" , "用户名称" , "规格" ,
|
||
"状态","销售申请时间" , "销售申请时间NoCRM" ,
|
||
"销售申请区域NoCRM" , "销售申请时代理商名称NoCRM",
|
||
"是否装机" , "未装机原因" ,
|
||
"备注" , "最后测试时间" ,
|
||
"用户onCRM" , "销售申请日期" ,
|
||
"销售申请区域" , "销售申请时代理商名称" ,
|
||
"销售申请时用户名称" , "无测试原因" ,
|
||
"备注NoTest" )
|
||
dfBy仪器feedbackDataandInf <- dfBy仪器feedbackDataandInf[order(-dfBy仪器feedbackDataandInf$测试截止),][,cname0]
|
||
write_excel_csv(dfBy仪器feedbackDataandInf,file="仪器统计feedbackandInf.csv")
|
||
dfBy仪器feedbackDataandInfall<-merge(dfBy仪器,仪器编号和序列号feedbackData,by="仪器序列号",all.x=TRUE,all.y=TRUE)
|
||
dfBy仪器feedbackDataandInfall <- dfBy仪器feedbackDataandInfall[order(-dfBy仪器feedbackDataandInfall$测试截止),][,cname0]
|
||
write_excel_csv(dfBy仪器feedbackDataandInfall,file="仪器统计feedbackandInfall.csv")
|
||
colnames(仪器编号和序列号feedbackData)
|
||
notFoundfeedBack<-仪器编号和序列号feedbackData[!(仪器编号和序列号feedbackData$仪器序列号 %in% dfBy仪器$仪器序列号),]
|
||
|
||
cname1<-c( "仪器序列号" ,"仪器编号" ,
|
||
"开机地点" ,
|
||
"SIM卡号" , "发货时间" , "仪器类型" ,
|
||
"总测试量" , "最后一次开机时间" ,"时间差" ,
|
||
"网络类型" , "ip地址" ,
|
||
"用户" , "用户CRM" , "返利表序号" ,
|
||
"申请日期" , "区域" , "客户编码" ,
|
||
"代理商名称" , "用户名称" , "规格" ,
|
||
"状态","销售申请时间" , "销售申请时间NoCRM" ,
|
||
"销售申请区域NoCRM" , "销售申请时代理商名称NoCRM",
|
||
"是否装机" , "未装机原因" ,
|
||
"备注" , "最后测试时间" ,
|
||
"用户onCRM" , "销售申请日期" ,
|
||
"销售申请区域" , "销售申请时代理商名称" ,
|
||
"销售申请时用户名称" , "无测试原因" ,
|
||
"备注NoTest" )
|
||
|
||
colnames(notFoundfeedBack)
|
||
|
||
write_excel_csv(notFoundfeedBack[,cname1],file="仪器统计NotfoundfeedBack.csv")
|
||
}
|
||
|
||
dfByDayAndLocation <- df2000 %>% group_by(testDay,testMonth,省编号) %>% summarise(
|
||
测试数 = n(),
|
||
阳性数=sum(结论,na.rm = TRUE),
|
||
有效数=sum(是否有效,na.rm = TRUE),
|
||
样本数=length(unique(样本类型)),
|
||
项目数=length(unique(项目名称)),
|
||
仪器数=length(unique(仪器序列号)),
|
||
批次数=length(unique(批次名称)),
|
||
市数=length(unique(省市编号)),
|
||
省数=length(unique(省编号))
|
||
)
|
||
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$testDay),]
|
||
|
||
dfByMonthAndLocation <- df20 %>% group_by(testMonth,省编号) %>% summarise(
|
||
测试数 = n(),
|
||
阳性数=sum(结论,na.rm = TRUE),
|
||
有效数=sum(是否有效,na.rm = TRUE),
|
||
样本数=length(unique(样本类型)),
|
||
项目数=length(unique(项目名称)),
|
||
仪器数=length(unique(仪器序列号)),
|
||
批次数=length(unique(批次名称)),
|
||
市数=length(unique(省市编号))
|
||
)
|
||
dfByMonthAndLocation$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),]
|
||
|
||
cairo_pdf(paste("和迈dataAnalytics07072025",".pdf",sep=""), width = 8, height = 6,family = "SimHei" )
|
||
|
||
plotSummaryTable<-ggplot() +geom_text(aes(x = 100, y = 40,
|
||
label = summaryTable),
|
||
stat = "unique",
|
||
fontface = "bold",
|
||
color = "black", # 标签颜色
|
||
size = 5.0 )+ # 字体大小
|
||
xlim(0,200)+ylim(0,100)+
|
||
theme_minimal() + theme(axis.text = element_blank(),
|
||
axis.ticks = element_blank(),
|
||
axis.title = element_blank())
|
||
|
||
plotSummaryTable
|
||
|
||
dfByDay1<-dfByDay[lastDay-dfByDay$testDay<42,]
|
||
plotfunction(dfData=dfByDay1,independentVariableName="testDay",
|
||
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
|
||
plotfunction(dfData=dfByDay1,independentVariableName="testDay",
|
||
dependentVariableNames=c("有效率","阳性率"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
|
||
plotfunction(dfData=dfByDay1,independentVariableName="testDay",
|
||
dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
|
||
plotfunction(dfData=dfByDay1,independentVariableName="testDay",
|
||
dependentVariableNames=c("样本数","市数","省数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
|
||
|
||
dfByDayAndLocation1<-dfByDayAndLocation[lastDay-dfByDayAndLocation$testDay<42,]
|
||
|
||
panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=dfBy区域$省编号[1:6],independentVariableName="testDay",panelName="省编号",
|
||
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
|
||
panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=dfBy区域$省编号[1:6],independentVariableName="testDay",panelName="省编号",
|
||
dependentVariableNames=c("有效率","阳性率"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
|
||
panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=dfBy区域$省编号[1:6],independentVariableName="testDay",panelName="省编号",
|
||
dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
|
||
panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=dfBy区域$省编号[1:6],independentVariableName="testDay",panelName="省编号",
|
||
dependentVariableNames=c("样本数","市数","省数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
|
||
|
||
dfByMonth1<-dfByMonth[1:30,]
|
||
|
||
plotfunction(dfData=dfByMonth1,independentVariableName="testMonth",
|
||
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月测试统计","测试时间","统计数值",""))
|
||
plotfunction(dfData=dfByMonth1,independentVariableName="testMonth",
|
||
dependentVariableNames=c("有效率","阳性率"),titleNames=c("按月测试统计","测试时间","统计数值",""))
|
||
plotfunction(dfData=dfByMonth1,independentVariableName="testMonth",
|
||
dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按月测试统计","测试时间","统计数值",""))
|
||
plotfunction(dfData=dfByMonth1,independentVariableName="testMonth",
|
||
dependentVariableNames=c("样本数","市数","省数"),titleNames=c("按月测试统计","测试时间","统计数值",""))
|
||
|
||
panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=dfBy区域$省编号[1:6],independentVariableName="testMonth",panelName="省编号",
|
||
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
|
||
panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=dfBy区域$省编号[1:6],independentVariableName="testMonth",panelName="省编号",
|
||
dependentVariableNames=c("有效率","阳性率"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
|
||
panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=dfBy区域$省编号[1:6],independentVariableName="testMonth",panelName="省编号",
|
||
dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
|
||
panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=dfBy区域$省编号[1:6],independentVariableName="testMonth",panelName="省编号",
|
||
dependentVariableNames=c("样本数","市数"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
|
||
|
||
plotfunction(dfData=dfBy区域,independentVariableName="省编号",
|
||
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按省测试统计","省编号","统计数值",""))
|
||
plotfunction(dfData=dfBy区域,independentVariableName="省编号",
|
||
dependentVariableNames=c("有效率","阳性率"),titleNames=c("按省测试统计","省编号","统计数值",""))
|
||
plotfunction(dfData=dfBy区域,independentVariableName="省编号",
|
||
dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按省测试统计","省编号","统计数值",""))
|
||
plotfunction(dfData=dfBy区域,independentVariableName="省编号",
|
||
dependentVariableNames=c("样本数","市数"),titleNames=c("按省测试统计","省编号","统计数值",""))
|
||
plotfunctionLog(dfData=dfBy区域,independentVariableName="省编号",
|
||
dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按省测试统计","省编号","多少天之前",""))
|
||
|
||
仪器号List0<-cbind(dfBy仪器,GroupID=rep00[1:length(dfBy仪器$仪器序列号)])
|
||
仪器号List<-仪器号List0[,c(1,ncol(仪器号List0))]
|
||
dfBy仪器$仪器序列号<-factor(dfBy仪器$仪器序列号,levels = 仪器号List[,1])
|
||
|
||
plotfunctionVector仪器序列号(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号",
|
||
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按仪器测试统计","仪器序列号","统计数值",""))
|
||
plotfunctionVector仪器序列号(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号",
|
||
dependentVariableNames=c("项目数","样本数","批次数"),titleNames=c("按仪器测试统计","仪器序列号","统计数值",""))
|
||
plotfunctionVector仪器序列号(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号",
|
||
dependentVariableNames=c("有效率","阳性率"),titleNames=c("按仪器测试统计","仪器序列号","统计数值",""))
|
||
plotfunctionVector仪器序列号Log(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号",
|
||
dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按仪器测试统计","仪器序列号","多少天之前",""))
|
||
|
||
|
||
if(FALSE) {
|
||
dfBy仪器00 <- df2000 %>% group_by(仪器序列号,省市编号,详细地址,仪器备注名称,仪器投放区域) %>% summarise(
|
||
批次数=length(unique(批次名称)),
|
||
测试数 = n(),
|
||
样本数=length(unique(样本类型)),
|
||
项目数=length(unique(项目名称)),
|
||
阳性数=sum(结论,na.rm = TRUE),
|
||
有效数=sum(是否有效,na.rm = TRUE),
|
||
earliestIndex=min(IDIndex),
|
||
medianIndex=median(IDIndex),
|
||
latestIndex=max(IDIndex),
|
||
最早测试=min(testDay,na.rm = TRUE),
|
||
最近测试=max(testDay,na.rm = TRUE),
|
||
测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
|
||
测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
|
||
)
|
||
dfBy仪器00$阳性率<-dfBy仪器00$阳性数/dfBy仪器00$有效数
|
||
dfBy仪器00$有效率<-dfBy仪器00$有效数/dfBy仪器00$测试数
|
||
dfBy仪器00$阳性数<-as.integer(dfBy仪器00$阳性数)
|
||
dfBy仪器00$测试数<-as.integer(dfBy仪器00$测试数)
|
||
dfBy仪器00$有效数<-as.integer(dfBy仪器00$有效数)
|
||
|
||
|
||
|
||
dfBy仪器1<-merge(dfBy仪器00[,1:5],dfBy仪器,by="仪器序列号",all=FALSE)
|
||
write_excel_csv(dfBy仪器1,file="仪器统计1.csv")
|
||
#仪器号MissedFromTwoYearsAgo<-仪器号[!(仪器号 %in% 仪器号00)]
|
||
}
|
||
|
||
#样本号List<-unique(dfBy样本$样本类型)
|
||
plotfunction(dfData=dfBy样本,independentVariableName="样本类型",
|
||
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按样本类型测试统计","样本类型","统计数值",""))
|
||
plotfunction(dfData=dfBy样本,independentVariableName="样本类型",
|
||
dependentVariableNames=c("项目数","批次数","省数"),titleNames=c("按样本类型测试统计","样本类型","统计数值",""))
|
||
plotfunction(dfData=dfBy样本,independentVariableName="样本类型",
|
||
dependentVariableNames=c("有效率","阳性率"),titleNames=c("按样本类型测试统计","样本类型","统计数值",""))
|
||
plotfunctionLog(dfData=dfBy样本,independentVariableName="样本类型",
|
||
dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按样本类型测试统计","样本类型","多少天之前",""))
|
||
|
||
|
||
批次号List0<-cbind(dfBy批次,GroupID=rep00[1:length(dfBy批次$批次名称)])
|
||
批次号List<-批次号List0[,c(1,ncol(批次号List0))]
|
||
dfBy批次$批次名称<-factor(dfBy批次$批次名称,levels = 批次号List[,1])
|
||
|
||
plotfunctionVector批次名称(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称",
|
||
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按批次测试统计","批次名称","统计数值",""))
|
||
plotfunctionVector批次名称(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称",
|
||
dependentVariableNames=c("项目数","样本数","省数"),titleNames=c("按试剂批次测试统计","批次名称","统计数值",""))
|
||
plotfunctionVector批次名称(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称",
|
||
dependentVariableNames=c("有效率","阳性率"),titleNames=c("按试剂批次测试统计","批次名称","统计数值",""))
|
||
plotfunctionVector批次名称Log(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称",
|
||
dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按试剂批次测试统计","批次名称","多少天之前",""))
|
||
|
||
项目号List0<-cbind(dfBy项目,GroupID=rep00[1:length(dfBy项目$项目名称)])
|
||
项目号List<-项目号List0[,c(1,ncol(项目号List0))]
|
||
dfBy项目$项目名称<-factor(dfBy项目$项目名称,levels = 项目号List[,1])
|
||
|
||
plotfunctionVector项目名称(ik=1,independentVariableList=项目号List,dfData=dfBy项目,independentVariableName="项目名称",
|
||
dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按项目测试统计","项目名称","统计数值",""))
|
||
plotfunctionVector项目名称(ik=1,independentVariableList=项目号List,dfData=dfBy项目,independentVariableName="项目名称",
|
||
dependentVariableNames=c("批次数","样本数","省数"),titleNames=c("按试剂项目测试统计","项目名称","统计数值",""))
|
||
plotfunctionVector项目名称(ik=1,independentVariableList=项目号List,dfData=dfBy项目,independentVariableName="项目名称",
|
||
dependentVariableNames=c("有效率","阳性率"),titleNames=c("按试剂项目测试统计","项目名称","统计数值",""))
|
||
plotfunctionVector项目名称Log(ik=1,independentVariableList=项目号List,dfData=dfBy项目,independentVariableName="项目名称",
|
||
dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按试剂项目测试统计","项目名称","多少天之前",""))
|
||
|
||
|
||
dev.off()
|
||
|
||
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$testTimeFromeToday)
|
||
colnames(df20)
|
||
|
||
#df201<-df20
|
||
|
||
# for(i in 1:5){
|
||
|
||
cairo_pdf(paste("和迈dataAnalyticsForRandD","_a07072025.pdf",sep=""), width = 8, height = 6,family = "SimHei" )
|
||
|
||
plotSummaryTable
|
||
|
||
# df20<-df201[(df201$项目名称 %in% dfBy项目top4[i]),]
|
||
# plot项目名称Title<-ggplot() +geom_text(aes(x = 100, y = 60,
|
||
# label = paste("项目名称： ",dfBy项目名称top5[i],sep="")),
|
||
# stat = "unique",
|
||
# fontface = "bold",
|
||
# color = "black", # 标签颜色
|
||
# size = 8.0 )+ # 字体大小
|
||
# xlim(0,200)+ylim(0,100)+
|
||
# theme_minimal() + theme(axis.text = element_blank(),
|
||
# axis.ticks = element_blank(),
|
||
# axis.title = element_blank())
|
||
#
|
||
# plot项目名称Title
|
||
|
||
df20 <- df20[order(-df20$testTimeFromeToday),]
|
||
|
||
df20 <- df20 %>% group_by(批次名称) %>% transform(
|
||
浓度1移动均值 = running_avg(浓度1,20),
|
||
C值移动均值 = running_avg(C值,20),
|
||
T值移动均值 = running_avg(T值,20),
|
||
ToverC值移动均值 = running_avg(ToverC值,20),
|
||
结论移动均值 = running_avg(结论,20)
|
||
)
|
||
|
||
# df20$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$结论累计均值)
|
||
df200<-df20
|
||
df20<-df200[df200$项目名称 %in% 项目号List[1,1], ]
|
||
#df20Ploted<-df20[df20$批次名称 %in% 批次号List$批次名称[批次号List[,2]==1],]
|
||
df20Ploted<-df20[df20$批次名称 %in% 批次号List$批次名称[1:5],]
|
||
|
||
pointPlotfunction批次(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="浓度1",titleNames=c("浓度","测试日期","浓度1",""))
|
||
pointPlotfunction批次Log(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="C值",titleNames=c("C值","测试日期","C值",""))
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pointPlotfunction批次Log(dfData=df20Ploted,independentVariableName="testDay",
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dependentVariableName="T值",titleNames=c("T值","测试日期","T值",""))
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pointPlotfunction批次(dfData=df20Ploted,independentVariableName="testDay",
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dependentVariableName="ToverC值",titleNames=c("T/C值","测试日期","T/C值",""))
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pointPlotfunction批次(dfData=df20Ploted,independentVariableName="testDay",
|
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dependentVariableName="结论移动均值",titleNames=c("结论/阳性率","测试日期","结论/阳性率",""))
|
||
|
||
df20Ploted<-df20[df20$仪器序列号 %in% 仪器号List$仪器序列号[1:5],]
|
||
|
||
pointPlotfunction仪器(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="浓度1",titleNames=c("浓度","测试日期","浓度1",""))
|
||
pointPlotfunction仪器Log(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="C值",titleNames=c("C值","测试日期","C值",""))
|
||
pointPlotfunction仪器Log(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="T值",titleNames=c("T值","测试日期","T值",""))
|
||
pointPlotfunction仪器(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="ToverC值",titleNames=c("T/C值","测试日期","T/C值",""))
|
||
pointPlotfunction仪器(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="结论移动均值",titleNames=c("结论/阳性率","测试日期","结论/阳性率",""))
|
||
|
||
|
||
df20Ploted<-df20[df20$样本类型 %in% unique(df20$样本类型)[1:2],]
|
||
|
||
pointPlotfunction样本(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="浓度1",titleNames=c("浓度","测试日期","浓度1",""))
|
||
pointPlotfunction样本Log(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="C值",titleNames=c("C值","测试日期","C值",""))
|
||
pointPlotfunction样本Log(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="T值",titleNames=c("T值","测试日期","T值",""))
|
||
pointPlotfunction样本(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="ToverC值",titleNames=c("T/C值","测试日期","T/C值",""))
|
||
pointPlotfunction样本(dfData=df20Ploted,independentVariableName="testDay",
|
||
dependentVariableName="结论移动均值",titleNames=c("结论/阳性率","测试日期","结论/阳性率",""))
|
||
|
||
|
||
dev.off()
|
||
|
||
|