自定义函数无法正常运行~嘤嘤嘤QAQ

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我写了一个计算每日入院人数的code，(非常烂，可以么有办法)，但是这个代码如果在入院人数为0的时候就会出错，怎么改进才能正常运行啊，好难过(ಥ﹏ಥ)啊~~~

```

1. tsdata2 <- function(df){
   
2.   
   
3.   t.f <- as.data.frame(table(df$DATE_INHOSPITAL2)) %>% rename(whole =Freq)
   
4.   ## sex
   
5.   man.d <- df %>% filter(GENDER == 1)
   
6.   man.f <- as.data.frame(table(man.d$DATE_INHOSPITAL2)) %>% rename(man =Freq)
   
7.   
   
8.   woman.d <- df %>% filter(GENDER == 2)
   
9.   woman.f <- as.data.frame(table(woman.d$DATE_INHOSPITAL2)) %>% rename(woman =Freq)
   
10.   
    
11.   ## age 65
    
12.   agelo65.d <- df %>% filter(age_group65 == 1)
    
13.   agelo65.f <- as.data.frame(table(agelo65.d$DATE_INHOSPITAL2)) %>% rename(agelo65 =Freq)
    
14.   
    
15.   ageup65.d <- df %>% filter(age_group65 == 2)
    
16.   ageup65.f <- as.data.frame(table(ageup65.d$DATE_INHOSPITAL2)) %>% rename(ageupwith65 =Freq)
    
17.   
    
18.   ## age 10
    
19.   age10.1.d <- df %>% filter(age_group10 == 1)
    
20.   age10.1.d.f <- as.data.frame(table(age10.1.d$DATE_INHOSPITAL2)) %>% rename(agelo40 =Freq)
    
21.   
    
22.   age10.2.d <- df %>% filter(age_group10 == 2)
    
23.   age10.2.d.f <- as.data.frame(table(age10.2.d$DATE_INHOSPITAL2)) %>% rename(age41_50 =Freq)
    
24.   
    
25.   age10.3.d <- df %>% filter(age_group10 == 3)
    
26.   age10.3.d.f <- as.data.frame(table(age10.3.d$DATE_INHOSPITAL2)) %>% rename(age51_60 =Freq)
    
27.   
    
28.   age10.4.d <- df %>% filter(age_group10 == 4)
    
29.   age10.4.d.f <- as.data.frame(table(age10.4.d$DATE_INHOSPITAL2)) %>% rename(age61_70 =Freq)
    
30.   
    
31.   age10.5.d <- df %>% filter(age_group10 == 5)
    
32.   age10.5.d.f <- as.data.frame(table(age10.5.d$DATE_INHOSPITAL2)) %>% rename(age71_80 =Freq)
    
33.   
    
34.   age10.6.d <- df %>% filter(age_group10 == 6)
    
35.   age10.6.d.f <- as.data.frame(table(age10.6.d$DATE_INHOSPITAL2)) %>% rename(ageup80 =Freq)
    
36.   
    
37.   datebreaks<-seq(as.Date("2014-01-01"),as.Date("2018-12-31"),by="1 day")
    
38.   
    
39.   full <- data.frame(Var1 = as.character(datebreaks) )
    
40.   
    
41.   
    
42.   result <- full %>%
    
43.     left_join(t.f) %>%
    
44.     left_join(man.f) %>%
    
45.     left_join(woman.f) %>%
    
46.     left_join(agelo65.f) %>%
    
47.     left_join(ageup65.f) %>%
    
48.     left_join(age10.1.d.f) %>%
    
49.     left_join(age10.2.d.f) %>%
    
50.     left_join(age10.3.d.f) %>%
    
51.     left_join(age10.4.d.f) %>%
    
52.     left_join(age10.5.d.f) %>%
    
53.     left_join(age10.6.d.f) %>% replace(., is.na(.), 0)
    
54.   
    
55.   return(result)
    
56. }
    
57. 
    
58. 
    
59. list <- split(total,total$DISEASE_CODE1_2to3)
    
60. 
    
61. test <- map(list,tsdata2)

复制代码

运行结果是酱紫的。。

1. test <- map(list,tsdata2)
   
2. Joining, by = "Var1"
   
3. Joining, by = "Var1"
   
4. Joining, by = "Var1"
   
5. Joining, by = "Var1"
   
6. Joining, by = "Var1"
   
7. Joining, by = "Var1"
   
8. Error: `by` required, because the data sources have no common variables

复制代码

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关键词：自定义函数 自定义 replace Result RETURN

你这不就是个分组统计么，还用得着自定义函数？

Whig 发表于 2019-6-8 16:00
你这不就是个分组统计么，还用得着自定义函数？

我怎么能按照年龄分组和性别分组，分别分组统计啊，最后输出一个大的dataframe

data.table和dplyr你会用哪个？

Whig 发表于 2019-6-8 17:23
data.table和dplyr你会用哪个？

我一般用dplyr~~~

卑鄙的我lzw 发表于 2019-6-8 18:40
我一般用dplyr~~~

用dplyr里的分组统计方法group_by试一下吧