Chấm công calendar

# my_folder <- 'P:/Nhansu/Du lieu cham cong - Theo doi ngay nghi/Du lieu cham cong/Hoi so/'
# files <- list.files(my_folder, pattern = "\\.xls$", full.names = T, recursive = T) # change here
# map_df(files, read_excel)->> cham_cong
cham_cong <- read_excel("D:/R/Rmarkdown/chamcong/chamcong.xlsx")

cham_cong <- cham_cong %>%
  set_names(c("day_name", "date", "time", "emp_code")) %>%
  mutate(date_time = paste(date, time) %>% dmy_hms(),
         date = date_time %>% as_date())  %>%
  group_by(emp_code, date) %>%
  summarise(max_time = max(date_time, na.rm = T),
         min_time = min(date_time, na.rm = T)) %>% 
  mutate(working_time = difftime(max_time, min_time, units = "hours") %>% as.numeric()) %>%
  ungroup()

#==============================================================================
# Tao bang calendar
#==============================================================================
df_date <- data.frame(date = ymd(20180101) %m+% days(1:303))

df_date %<>% mutate(day = day(date),
                   week_name = weekdays(date, abbreviate = T),
                   week_name = factor(week_name,
                                         levels = rev(c("Mon","Tue","Wed","Thu","Fri","Sat","Sun")),
                                         labels = rev(c("Mon","Tue","Wed","Thu","Fri","Sat","Sun"))),
                   week = week(date),
                   month = month(date),
                   month_name = month.abb[month],
                   month_name = factor(month_name,
                                          levels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"),
                                          labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"))) %>% 
  group_by(month_name) %>% 
  mutate(month_week = week - min(week) + 1) %>% 
  ungroup()

nnb_plot <- function(sb = 'SB11341'){
  df <- working_time %>% 
    filter(emp_code == sb) %>% 
    right_join(df_date, by = "date") %>% 
    mutate(pass_min_time = ymd_hms(paste(date, "08:15:00")),
           pass_max_time = case_when(week_name == "Sat" ~ ymd_hms(paste(date, "12:00:00")),
                                     TRUE ~ ymd_hms(paste(date, "17:00:00"))),
           pass_day = case_when(is.na(min_time) ~ "Absent",
                                min_time <= pass_min_time & max_time >= pass_max_time ~ "Ok",
                                TRUE ~ "Fail") %>% as.factor()) %>% 
    filter(week_name != "Sun")
  
  # df %>% mutate(pass_day = case_when(is.na(working_time) ~ "Absent",
  #                             week_name %in% "Sat" & working_time >= 4 ~ "Ok",
  #                             week_name != "Sat" & working_time >= 8 ~ "Ok",
  #                             TRUE ~ "Fail") %>% as.factor()) %>% 
  df %>% 
  ggplot(aes(x = month_week, y = week_name, fill = pass_day))+
  geom_tile() +
  scale_fill_manual(values = c("snow2", "brown3", "springgreen"))+
  facet_wrap(~month_name)+
  geom_text(aes(label = day))+
  labs(title = paste("Working hour by date of", sb),
       y = NULL,
       x = NULL)->> p
  
  p
  
}

1 Tổng số giờ làm việc theo ngày của tất cả cán bộ nhân viên hội sở

hoi_so %>% 
  ggplot(aes(x = month_week, y = week_name, fill = working_time))+
  geom_tile() +
  scale_fill_gradient(low = "white", high = "red") +
  facet_wrap(~month_name)+
  geom_text(aes(label = day))+
  labs(title = "Total working time of staff",
        y = NULL,
        x = NULL,
       caption = "Source: HR-SeABank",
       fill = "Working time")

2 Một số SB

2.1 SB11341

nnb_plot(sb = "SB11341")

2.2 SB10205

nnb_plot(sb = "SB10205")

2.3 SB10973

nnb_plot(sb = "SB10973")

2.4 SB10292

nnb_plot(sb = "SB10292")

2.5 SB10356

nnb_plot(sb = "SB10356")

2.6 SB10059

nnb_plot(sb = "SB10059")

2.7 SB11397

nnb_plot(sb = "SB11397")

2.8 SB11658

nnb_plot(sb = "SB11658")

2.9 SB11819

nnb_plot(sb = "SB11819")

2.10 BI

bi %>% 
  mutate(pass_min_time = ymd_hms(paste(date, "08:15:00")),
         pass_max_time = case_when(week_name == "Sat" ~ ymd_hms(paste(date, "12:00:00")),
                                   TRUE ~ ymd_hms(paste(date, "17:00:00"))),
         pass_day = case_when(is.na(min_time) ~ "Absent",
                              min_time <= pass_min_time & max_time >= pass_max_time ~ "Ok",
                              TRUE ~ "Fail") %>% as.factor()) %>% 
  filter(week_name != "Sun")%>% 
  filter(!is.na(emp_code)) %>% 
  ggplot(aes(x = month_week, y = week_name, fill = pass_day))+
  geom_tile() +
  scale_fill_manual(values = c("brown3", "springgreen"))+
  facet_wrap(~emp_name)+
  geom_text(aes(label = day))+
  labs(title = paste("Working hour by date of BI in", month.abb[month(first_date)]),
       y = NULL,
       x = NULL,
       fill = "Pass day")