R/01checkOn_Func.R
In takewiki/nshr_pkg:
Defines functions
checkOn_sum_byDay
checkOn_sum
checkOn_all
checkOn_PM
checkOn_AM
deal_CheckOn
Documented in
checkOn_all
checkOn_AM
checkOn_PM
checkOn_sum
checkOn_sum_byDay
deal_CheckOn
library(tsdo);
library(tsda);
#' 处理网商考勤数据
#'
#' @param file 考勤数据文件
#' @param morningStartTime 凌晨开始时点
#' @param moringEndTime 凌晨结束时点
#' @param AmStartTime 上午开始时间
#' @param AmCheckTime 上午打卡时间
#' @param AmEndTime 上午结束时间
#' @param pmStartTime 下午开始时间
#' @param pmCheckTime 下午打卡时间
#' @param pmEndTime 下午结束时间
#' @param nightStartTime 晚上开始时间
#' @param nightCheckTime 晚上结束时间
#'
#' @return 返回数据框
#' @import hms
#' @export
#'
#' @examples
#' deal_CheckOn();
deal_CheckOn <- function(file="data-raw/input/01-ns_kaoQin.xlsx",
morningStartTime ='0:00:00' ,
moringEndTime = '6:00:00',
AmStartTime = '8:00:00',
AmCheckTime = '9:00:00',
AmEndTime = '12:00:00',
pmStartTime ='12:00:00',
pmCheckTime="18:00:00",
pmEndTime ='18:30:00',
nightStartTime = '18:30:00',
nightCheckTime = '19:00:00'
) {
# 读取考勤数据，自动保存到df
data_CheckOn <- readExcelDf(file = file);
#针对列进行重命名
names(data_CheckOn) <-c('FDeptName','FEmpName','FCheckNum','FCheckOnDateTime','FMachineId',
'FIndex','FCheckStyle','FCardNumber');
#选择字段列名
fieldSel_checkon <- c('FDeptName','FEmpName','FCheckOnDateTime');
data_CheckOn <- data_CheckOn %>% df_selectCol(fieldSel_checkon);
datetime <- data_CheckOn$FCheckOnDateTime;
FDate <- left(datetime,10);
FTime <-substr(datetime,12,nchar(datetime));
FTime <- tsdo::round_time(FTime,'min');
FTime <-as.hms(FTime);
FIsMorning <- is.Morning(x = FTime,
morningStartTime = morningStartTime,
morningEndTime = moringEndTime );
# 判断是否为上午
FIsAm <- is.Am(FTime,AmStartTime =AmStartTime, AmEndTime = AmEndTime);
#判断是否为下午班
FIsPm <-is.Pm(FTime,startTime = pmStartTime,endTime = pmEndTime)
#判断是否加班
FIsNight <-is.Night(FTime,nightStartTime = nightStartTime);
#判断上午处理时间差
#以 上午9:00 作为标准
FAmDiff <- timeDiff(FTime,AmCheckTime,unit = 'm',digit = 1);
#处理下午的处理
FPmDiff <-timeDiff(FTime,pmCheckTime,unit = 'm',digit = 1);
#处理加班时间
FNightDiff <-timeDiff(FTime,nightCheckTime,unit = 'h',digit = 2);
#处理凌晨的加班时间处理
FMorningDiff <-timeDiff(FTime,morningStartTime,unit = 'h',digit = 2);
FDeptName <-data_CheckOn$FDeptName;
FEmpName <- data_CheckOn$FEmpName
data_CheckOn<-data.frame(FDeptName,FEmpName,FDate,FTime,FIsMorning,FMorningDiff,FIsAm,FAmDiff,FIsPm,FPmDiff,
FIsNight,FNightDiff,
stringsAsFactors = F);
#修复数据
data_CheckOn$FAmDiff[data_CheckOn$FIsAm == FALSE] <- 0
data_CheckOn$FAmDiff[data_CheckOn$FAmDiff > 0] <- 0
#修复下午的数据
data_CheckOn$FPmDiff[data_CheckOn$FIsPm == FALSE] <- 0;
data_CheckOn$FPmDiff[data_CheckOn$FPmDiff < 0] <- 0;
data_CheckOn$FPmDiff <- -data_CheckOn$FPmDiff;
#修复晚上数据
data_CheckOn$FNightDiff[data_CheckOn$FIsNight == FALSE] <- 0;
data_CheckOn$FNightDiff <- -data_CheckOn$FNightDiff
#修复凌晨数据
data_CheckOn$FMorningDiff[data_CheckOn$FIsMorning == FALSE] <- 0;
data_CheckOn$FMorningDiff <- -data_CheckOn$FMorningDiff;
return(data_CheckOn);
}
#' 提供数据中的早上数据
#'
#' @param data_CheckOn 考勤数据
#' @param AmCheckTime 上班打卡时间
#' @param AmLateMins 迟到分钟数
#'
#' @return 返回值
#' @import hms
#' @import dplyr
#' @export
#'
#' @examples
#' checkOn_AM()
checkOn_AM <- function(data_CheckOn,AmCheckTime="9:00:00",AmLateMins=5) {
am_fields <- c("FDeptName","FEmpName","FDate","FTime")
res<-data_CheckOn[data_CheckOn$FIsAm == TRUE, am_fields];
#针对早上打卡数据进行去重，取最小值；
res <- res %>% group_by(FDeptName,FEmpName,FDate) %>% summarise(FCheckTime = min(FTime))
res$FCheckTime <- as.hms(res$FCheckTime)
res$FMinDiff <- timeDiff(res$FCheckTime,AmCheckTime,unit = 'm',digit = 1);
res$FErrCount <-0 ;
#计算迟到次数
res$FErrCount[res$FMinDiff < -AmLateMins] = 1
#针对没有迟到的数据进行清空处理
res$FMinDiff[res$FMinDiff >=0 ] <- 0;
res$FType <-"上班打卡"
return(res);
}
#' 处理下午的时间
#'
#' @param data_CheckOn 考勤数据
#' @param PmCheckTime 下午打卡时间
#' @param PmLeakMins 提前时间
#'
#' @return 返回值
#' @export
#'
#' @examples
#' checkOn_PM();
checkOn_PM <- function(data_CheckOn,PmCheckTime="18:00:00",PmLeakMins=5) {
pm_fields <- c("FDeptName","FEmpName","FDate","FTime")
res<-data_CheckOn[data_CheckOn$FIsPm == TRUE, pm_fields];
#针对早上打卡数据进行去重，取最小值；
res <- res %>% group_by(FDeptName,FEmpName,FDate) %>% summarise(FCheckTime = max(FTime))
res$FCheckTime <- as.hms(res$FCheckTime)
res$FMinDiff <- -timeDiff(res$FCheckTime,PmCheckTime,unit = 'm',digit = 1);
res$FErrCount <-0 ;
#计算迟到次数
res$FErrCount[res$FMinDiff < -PmLeakMins] = 1
#针对没有迟到的数据进行清空处理
res$FMinDiff[res$FMinDiff >=0 ] <- 0;
res$FType <- "下班打卡";
return(res);
}
#' 考勤数据入口函数
#'
#' @param file 文件名
#' @param morningStartTime 凌晨开始时间
#' @param moringEndTime 凌晨结束时间
#' @param AmStartTime 上午开始
#' @param AmCheckTime 上午打卡
#' @param AmEndTime 上午结束
#' @param AmLateMins 上午偏置
#' @param pmStartTime 下午开始
#' @param pmCheckTime 下午打卡
#' @param pmEndTime 下午结束
#' @param PmLeakMins 下午偏置
#' @param nightStartTime 晚上开始
#' @param nightCheckTime 晚上打卡
#'
#' @return 返回值
#' @import tsdo
#' @export
#'
#' @examples
#' CheckOn_all();
checkOn_all <- function(file="data-raw/input/01-ns_kaoQin.xlsx",
morningStartTime ='0:00:00' ,
moringEndTime = '6:00:00',
AmStartTime = '8:00:00',
AmCheckTime = '9:00:00',
AmEndTime = '12:00:00',
AmLateMins=0,
pmStartTime ='12:00:00',
pmCheckTime="18:00:00",
pmEndTime ='18:30:00',
PmLeakMins=0,
nightStartTime = '18:30:00',
nightCheckTime = '19:00:00'
){
res <-deal_CheckOn(file=file,
morningStartTime = morningStartTime,
moringEndTime = moringEndTime,
AmStartTime = AmStartTime,
AmCheckTime = AmCheckTime ,
AmEndTime = AmEndTime,
pmStartTime = pmStartTime,
pmCheckTime = pmCheckTime,
pmEndTime = pmEndTime,
nightStartTime = nightStartTime,
nightCheckTime = nightCheckTime);
res_am <- checkOn_AM(data_CheckOn = res,
AmCheckTime = AmCheckTime,
AmLateMins = AmLateMins);
res_pm <- checkOn_PM(data_CheckOn = res,
PmCheckTime = pmCheckTime,
PmLeakMins = PmLeakMins);
res <- rbind(res_am,res_pm);
res <- res[order(res$FDeptName,res$FEmpName,res$FDate,res$FType),]
return(res);
}
#' 针对数据进行汇总处理
#'
#' @param checkOn_all_data 考勤数据
#' @param startDate 月度开始
#' @param EndDate 月度结束
#' @param ErrorOnly 是否只统计异常数据
#'
#' @return 返回值
#' @export
#'
#' @examples
#' checkOn_sum();
checkOn_sum <- function(checkOn_all_data,
startDate='2019-06-01',
EndDate='2019-06-30',
ErrorOnly=FALSE) {
data <-checkOn_all_data;
#只显示异常数据
if (ErrorOnly == TRUE){
data <- data[data$FErrCount == 1, ];
}
#只显示过滤时间范围内数据
data <- data[data$FDate >= startDate & data$FDate <= EndDate, ];
data$FType <-'迟到'
#针对数据进行汇总
res <- data %>% group_by(FDeptName,FEmpName,FType) %>% summarise(FTotalValue = sum(FMinDiff))
return(res);
}
#' 按天计算汇总数据
#'
#' @param checkOn_all_data 考勤数据
#' @param startDate 开始日期
#' @param EndDate 结束日期
#' @param ErrorOnly 是否只包含错误
#'
#' @return 返回值
#' @export
#'
#' @examples
#' checkOn_sum_byDay();
checkOn_sum_byDay <- function(checkOn_all_data,
startDate='2019-06-01',
EndDate='2019-06-30',
ErrorOnly=FALSE) {
data <-checkOn_all_data;
#只显示异常数据
if (ErrorOnly == TRUE){
data <- data[data$FErrCount == 1, ];
}
#只显示过滤时间范围内数据
data <- data[data$FDate >= startDate & data$FDate <= EndDate, ];
data$FType <-'迟到'
#针对数据进行汇总
res <- data %>% group_by(FDeptName,FEmpName,FType,FDate) %>% summarise(FTotalValue = sum(FMinDiff))
return(res);
}
takewiki/nshr_pkg documentation built on Oct. 6, 2020, 12:12 p.m.
R Package Documentation
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Defines functions checkOn_sum_byDay checkOn_sum checkOn_all checkOn_PM checkOn_AM deal_CheckOn
Documented in checkOn_all checkOn_AM checkOn_PM checkOn_sum checkOn_sum_byDay deal_CheckOn
library(tsdo);
library(tsda);
#' 处理网商考勤数据
#'
#' @param file 考勤数据文件
#' @param morningStartTime 凌晨开始时点
#' @param moringEndTime 凌晨结束时点
#' @param AmStartTime 上午开始时间
#' @param AmCheckTime 上午打卡时间
#' @param AmEndTime 上午结束时间
#' @param pmStartTime 下午开始时间
#' @param pmCheckTime 下午打卡时间
#' @param pmEndTime 下午结束时间
#' @param nightStartTime 晚上开始时间
#' @param nightCheckTime 晚上结束时间
#'
#' @return 返回数据框
#' @import hms
#' @export
#'
#' @examples
#' deal_CheckOn();
deal_CheckOn <- function(file="data-raw/input/01-ns_kaoQin.xlsx",
morningStartTime ='0:00:00' ,
moringEndTime = '6:00:00',
AmStartTime = '8:00:00',
AmCheckTime = '9:00:00',
AmEndTime = '12:00:00',
pmStartTime ='12:00:00',
pmCheckTime="18:00:00",
pmEndTime ='18:30:00',
nightStartTime = '18:30:00',
nightCheckTime = '19:00:00'
) {
# 读取考勤数据，自动保存到df
data_CheckOn <- readExcelDf(file = file);
#针对列进行重命名
names(data_CheckOn) <-c('FDeptName','FEmpName','FCheckNum','FCheckOnDateTime','FMachineId',
'FIndex','FCheckStyle','FCardNumber');
#选择字段列名
fieldSel_checkon <- c('FDeptName','FEmpName','FCheckOnDateTime');
data_CheckOn <- data_CheckOn %>% df_selectCol(fieldSel_checkon);
datetime <- data_CheckOn$FCheckOnDateTime;
FDate <- left(datetime,10);
FTime <-substr(datetime,12,nchar(datetime));
FTime <- tsdo::round_time(FTime,'min');
FTime <-as.hms(FTime);
FIsMorning <- is.Morning(x = FTime,
morningStartTime = morningStartTime,
morningEndTime = moringEndTime );
# 判断是否为上午
FIsAm <- is.Am(FTime,AmStartTime =AmStartTime, AmEndTime = AmEndTime);
#判断是否为下午班
FIsPm <-is.Pm(FTime,startTime = pmStartTime,endTime = pmEndTime)
#判断是否加班
FIsNight <-is.Night(FTime,nightStartTime = nightStartTime);
#判断上午处理时间差
#以 上午9:00 作为标准
FAmDiff <- timeDiff(FTime,AmCheckTime,unit = 'm',digit = 1);
#处理下午的处理
FPmDiff <-timeDiff(FTime,pmCheckTime,unit = 'm',digit = 1);
#处理加班时间
FNightDiff <-timeDiff(FTime,nightCheckTime,unit = 'h',digit = 2);
#处理凌晨的加班时间处理
FMorningDiff <-timeDiff(FTime,morningStartTime,unit = 'h',digit = 2);
FDeptName <-data_CheckOn$FDeptName;
FEmpName <- data_CheckOn$FEmpName
data_CheckOn<-data.frame(FDeptName,FEmpName,FDate,FTime,FIsMorning,FMorningDiff,FIsAm,FAmDiff,FIsPm,FPmDiff,
FIsNight,FNightDiff,
stringsAsFactors = F);
#修复数据
data_CheckOn$FAmDiff[data_CheckOn$FIsAm == FALSE] <- 0
data_CheckOn$FAmDiff[data_CheckOn$FAmDiff > 0] <- 0
#修复下午的数据
data_CheckOn$FPmDiff[data_CheckOn$FIsPm == FALSE] <- 0;
data_CheckOn$FPmDiff[data_CheckOn$FPmDiff < 0] <- 0;
data_CheckOn$FPmDiff <- -data_CheckOn$FPmDiff;
#修复晚上数据
data_CheckOn$FNightDiff[data_CheckOn$FIsNight == FALSE] <- 0;
data_CheckOn$FNightDiff <- -data_CheckOn$FNightDiff
#修复凌晨数据
data_CheckOn$FMorningDiff[data_CheckOn$FIsMorning == FALSE] <- 0;
data_CheckOn$FMorningDiff <- -data_CheckOn$FMorningDiff;
return(data_CheckOn);
}
#' 提供数据中的早上数据
#'
#' @param data_CheckOn 考勤数据
#' @param AmCheckTime 上班打卡时间
#' @param AmLateMins 迟到分钟数
#'
#' @return 返回值
#' @import hms
#' @import dplyr
#' @export
#'
#' @examples
#' checkOn_AM()
checkOn_AM <- function(data_CheckOn,AmCheckTime="9:00:00",AmLateMins=5) {
am_fields <- c("FDeptName","FEmpName","FDate","FTime")
res<-data_CheckOn[data_CheckOn$FIsAm == TRUE, am_fields];
#针对早上打卡数据进行去重，取最小值；
res <- res %>% group_by(FDeptName,FEmpName,FDate) %>% summarise(FCheckTime = min(FTime))
res$FCheckTime <- as.hms(res$FCheckTime)
res$FMinDiff <- timeDiff(res$FCheckTime,AmCheckTime,unit = 'm',digit = 1);
res$FErrCount <-0 ;
#计算迟到次数
res$FErrCount[res$FMinDiff < -AmLateMins] = 1
#针对没有迟到的数据进行清空处理
res$FMinDiff[res$FMinDiff >=0 ] <- 0;
res$FType <-"上班打卡"
return(res);
}
#' 处理下午的时间
#'
#' @param data_CheckOn 考勤数据
#' @param PmCheckTime 下午打卡时间
#' @param PmLeakMins 提前时间
#'
#' @return 返回值
#' @export
#'
#' @examples
#' checkOn_PM();
checkOn_PM <- function(data_CheckOn,PmCheckTime="18:00:00",PmLeakMins=5) {
pm_fields <- c("FDeptName","FEmpName","FDate","FTime")
res<-data_CheckOn[data_CheckOn$FIsPm == TRUE, pm_fields];
#针对早上打卡数据进行去重，取最小值；
res <- res %>% group_by(FDeptName,FEmpName,FDate) %>% summarise(FCheckTime = max(FTime))
res$FCheckTime <- as.hms(res$FCheckTime)
res$FMinDiff <- -timeDiff(res$FCheckTime,PmCheckTime,unit = 'm',digit = 1);
res$FErrCount <-0 ;
#计算迟到次数
res$FErrCount[res$FMinDiff < -PmLeakMins] = 1
#针对没有迟到的数据进行清空处理
res$FMinDiff[res$FMinDiff >=0 ] <- 0;
res$FType <- "下班打卡";
return(res);
}
#' 考勤数据入口函数
#'
#' @param file 文件名
#' @param morningStartTime 凌晨开始时间
#' @param moringEndTime 凌晨结束时间
#' @param AmStartTime 上午开始
#' @param AmCheckTime 上午打卡
#' @param AmEndTime 上午结束
#' @param AmLateMins 上午偏置
#' @param pmStartTime 下午开始
#' @param pmCheckTime 下午打卡
#' @param pmEndTime 下午结束
#' @param PmLeakMins 下午偏置
#' @param nightStartTime 晚上开始
#' @param nightCheckTime 晚上打卡
#'
#' @return 返回值
#' @import tsdo
#' @export
#'
#' @examples
#' CheckOn_all();
checkOn_all <- function(file="data-raw/input/01-ns_kaoQin.xlsx",
morningStartTime ='0:00:00' ,
moringEndTime = '6:00:00',
AmStartTime = '8:00:00',
AmCheckTime = '9:00:00',
AmEndTime = '12:00:00',
AmLateMins=0,
pmStartTime ='12:00:00',
pmCheckTime="18:00:00",
pmEndTime ='18:30:00',
PmLeakMins=0,
nightStartTime = '18:30:00',
nightCheckTime = '19:00:00'
){
res <-deal_CheckOn(file=file,
morningStartTime = morningStartTime,
moringEndTime = moringEndTime,
AmStartTime = AmStartTime,
AmCheckTime = AmCheckTime ,
AmEndTime = AmEndTime,
pmStartTime = pmStartTime,
pmCheckTime = pmCheckTime,
pmEndTime = pmEndTime,
nightStartTime = nightStartTime,
nightCheckTime = nightCheckTime);
res_am <- checkOn_AM(data_CheckOn = res,
AmCheckTime = AmCheckTime,
AmLateMins = AmLateMins);
res_pm <- checkOn_PM(data_CheckOn = res,
PmCheckTime = pmCheckTime,
PmLeakMins = PmLeakMins);
res <- rbind(res_am,res_pm);
res <- res[order(res$FDeptName,res$FEmpName,res$FDate,res$FType),]
return(res);
}
#' 针对数据进行汇总处理
#'
#' @param checkOn_all_data 考勤数据
#' @param startDate 月度开始
#' @param EndDate 月度结束
#' @param ErrorOnly 是否只统计异常数据
#'
#' @return 返回值
#' @export
#'
#' @examples
#' checkOn_sum();
checkOn_sum <- function(checkOn_all_data,
startDate='2019-06-01',
EndDate='2019-06-30',
ErrorOnly=FALSE) {
data <-checkOn_all_data;
#只显示异常数据
if (ErrorOnly == TRUE){
data <- data[data$FErrCount == 1, ];
}
#只显示过滤时间范围内数据
data <- data[data$FDate >= startDate & data$FDate <= EndDate, ];
data$FType <-'迟到'
#针对数据进行汇总
res <- data %>% group_by(FDeptName,FEmpName,FType) %>% summarise(FTotalValue = sum(FMinDiff))
return(res);
}
#' 按天计算汇总数据
#'
#' @param checkOn_all_data 考勤数据
#' @param startDate 开始日期
#' @param EndDate 结束日期
#' @param ErrorOnly 是否只包含错误
#'
#' @return 返回值
#' @export
#'
#' @examples
#' checkOn_sum_byDay();
checkOn_sum_byDay <- function(checkOn_all_data,
startDate='2019-06-01',
EndDate='2019-06-30',
ErrorOnly=FALSE) {
data <-checkOn_all_data;
#只显示异常数据
if (ErrorOnly == TRUE){
data <- data[data$FErrCount == 1, ];
}
#只显示过滤时间范围内数据
data <- data[data$FDate >= startDate & data$FDate <= EndDate, ];
data$FType <-'迟到'
#针对数据进行汇总
res <- data %>% group_by(FDeptName,FEmpName,FType,FDate) %>% summarise(FTotalValue = sum(FMinDiff))
return(res);
}
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