R：如何使用多个过滤器绘制折线图。（R-Shining/flexdashboard）

R：如何使用多个过滤器绘制折线图。（R-Shining/flexdashboard）

我想用员工参加的活动总数的平均现值绘制折线图

Exmp: 2019年1月员工A的总事件数为4，其中员工A仅在1中出现，则应显示该月25%的结果。（（1/4）*100）%

这是样本数据，但实际上有100多名员工， 因此，结果应按员工姓名要求作为行颜色代码

数据集，如：

Employee        Status          Month_Yr
A               PRESENT         01/2019
C               PRESENT         01/2019
B               PRESENT         01/2019
C               PRESENT         02/2019
D               PRESENT         03/2019
A               PRESENT         01/2019
B               PRESENT         03/2019
C               PRESENT         01/2019
B               ABSENT          01/2019
D               ABSENT          01/2019
A               ABSENT          01/2019
C               PRESENT         02/2019
B               PRESENT         01/2019
A               PRESENT         02/2019
A               ABSENT          02/2019
D               ABSENT          03/2019
C               PRESENT         01/2019
C               ABSENT          01/2019
C               ABSENT          01/2019
A               ABSENT          02/2019
C               ABSENT          04/2019
B               ABSENT          01/2019

我试过的代码：

sub_data5 <-mutate(sub_data5, ontime = ifelse(sub_data5$Status=="PRESENT","Y","N"))


sub_data5 <- sub_data5 %>% 
    count(year_month, Employee, ontime,year,Month) %>% 
    group_by(year_month, Employee,year,Month) %>% 
    mutate(Prop = (n/sum(n))*100)

sub_data5$`Prop`  <- as.integer(sub_data5$`Prop`)

ggplot(sub_data5, aes(x=year_month, y=Prop, group=Employee, color=Employee)) +
  geom_line()

sub_数据5%
分组依据（年、月、员工、年、月）%>%
变异（Prop=（n/和（n））*100）
sub_data5$`Prop`从这段代码中我得到了结果

# Calculate total count of status and add new column for its percentage value.
sub_data5 <- sub_data5 %>% 
    count(Month_yr, Employee, Status) %>% 
    group_by(Month_yr, Employee) %>% 
    mutate(Percent = (n/sum(n))*100)

# Convert Percentage decimal to string 
sub_data5$`Percent `  <- (as.integer(sub_data5$`Percent`)+" %")

# Drop row values with ABSENT
sub_data5<-sub_data5[!(sub_data5$Status=="ABSENT"),]

#Employee can't use in plot because it's used as grouping so convert DF in to new DF
sub_data10 <- as.data.frame(sub_data5)

# Plot line chart.
plo <- ggplot(data=sub_data10, aes(x=Month_yr, y=Precent, group=Employee, colour=Employee)) +
    geom_line() +
    geom_point()

fig <- ggplotly(plo)

fig

#计算状态的总计数并为其百分比值添加新列。
次级单位数据5%
计数（月、年、员工、状态）%>%
分组依据（月/年，员工）%>%
变异（百分比=（n/和（n））*100）
#将百分比小数转换为字符串
sub_data5$`Percent`从这段代码中我得到了我的结果

# Calculate total count of status and add new column for its percentage value.
sub_data5 <- sub_data5 %>% 
    count(Month_yr, Employee, Status) %>% 
    group_by(Month_yr, Employee) %>% 
    mutate(Percent = (n/sum(n))*100)

# Convert Percentage decimal to string 
sub_data5$`Percent `  <- (as.integer(sub_data5$`Percent`)+" %")

# Drop row values with ABSENT
sub_data5<-sub_data5[!(sub_data5$Status=="ABSENT"),]

#Employee can't use in plot because it's used as grouping so convert DF in to new DF
sub_data10 <- as.data.frame(sub_data5)

# Plot line chart.
plo <- ggplot(data=sub_data10, aes(x=Month_yr, y=Precent, group=Employee, colour=Employee)) +
    geom_line() +
    geom_point()

fig <- ggplotly(plo)

fig

#计算状态的总计数并为其百分比值添加新列。
次级单位数据5%
计数（月、年、员工、状态）%>%
分组依据（月/年，员工）%>%
变异（百分比=（n/和（n））*100）
#将百分比小数转换为字符串
sub_data5$`Percent`但未获取所需筛选器但未获取所需筛选器