对日期匹配的列求和

Question

我有一个数据框 df1，其中包含列 ID 和日期（作为字符串“XYYYYMMDD”）

ID <- c(101,101,101,102,102)
date <- c("X20170101","X20170103","X20170106","X20170102","X20170104")
df1 <- data.table(ID,date)

ID      date
101 X20170101
101 X20170103
101 X20170106
102 X20170102
102 X20170104

和一个数据框 df2 以列 ID 和许多日期作为标题

ID <- c(100,101,102,103,104)
X20170101 <- c(1,NA,NA,2,1)
X20170102 <- c(NA,1,1,1,NA)
X20170103<-c(NA,1,NA,2,1)
X20170104 <- c(2,3,NA,2,1)
X20170105 <- c(1,1,NA,1,NA)
X20170106<-c(NA,1,NA,2,1)         
df2=data.table(ID,X20170101,X20170102,X20170103,X20170104,X20170105,X20170106)

ID X20170101 X20170102 X20170103 X20170104 X20170105 X20170106
100         1        NA        NA         2         1        NA
101        NA         1         1         3         1         1
102        NA         1        NA        NA        NA        NA
103         2         1         2         2         1         2
104         1        NA         1         1        NA         1

我想在 df1 中添加一列 count，其中包含以下内容：对于 df1，该日期（例如 X20170101）与 df1 中的连续单元格减去一天（例如 X20170102，而不是 X20170103）之间的 df2 中相应单元格的总和。也就是说，新的 df1 应该是这样的：

ID      date  count
101 X20170101     1
101 X20170103     5
101 X20170106     1
102 X20170102     1
102 X20170104    NA

感谢您的帮助。

Answer 1

你去！

library(data.table)
library(dplyr)
library(tidyr)

df2 %>% gather(date,val,-ID) %>%
  full_join(df1 %>% mutate(tag=1)) %>%
  arrange(ID) %>%
  replace_na(list(val=0,tag=0)) %>%
  group_by(ID) %>%
  mutate(grp=cumsum(tag)) %>%
  group_by(ID,grp) %>%
  summarize(count = sum(val),date=head(date,1)) %>%
  ungroup %>%
  mutate(count=ifelse(count== 0,NA,count)) %>%
  select(ID,date,count) %>%
  right_join(df1)

# # A tibble: 5 x 3
#      ID      date count
#   <dbl>     <chr> <dbl>
# 1   101 X20170101     1
# 2   101 X20170103     5
# 3   101 X20170106     1
# 4   102 X20170102     1
# 5   102 X20170104    NA

Answer 2

使用dplyr 包：

library(dplyr)
count <- aggregate(df1$date), by = list(df1$date), FUN = length)
df1 <- merge(df1, count, by = "date", all.x = TRUE)

让我知道这是否有效！