Question

我想在df1（包括df1$id，df1$datetime_interval，df1$datetime_event和df1$event）中放入df2中的数据（根据以下条件包括df2$id，df2$datetime_event）

如果 df1$id和df2$id匹配

和，如果df2$datetime_event在df1$datetime_interval内，

胜于我希望将df2$datetime_event的数据复制到df1$datetime_event，和df1列中> df1$event中的字符串（例如“ yes”）。

如果不满足条件，我不希望有任何结果（NA）

所以：

df1 ID datetime_interval datetime_event event 1 2019-04-19 21:50:00 UTC--2019-04-20 21:31:00 UTC NA NA 1 2019-07-02 04:23:00 UTC--2019-07-02 08:51:00 UTC NA NA 2 2019-07-04 19:45:00 UTC--2019-07-05 00:30:00 UTC NA NA 3 2019-06-07 08:55:00 UTC--2019-06-07 14:43:00 UTC NA NA 3 2019-05-06 17:18:00 UTC--2019-05-06 23:18:00 UTC NA NA 6 2019-08-02 22:00:00 UTC--2019-08-04 03:10:00 UTC NA NA

df2 ID datetime_event 1 2019-04-19 21:55:00 3 2019-05-06 21:23:00 5 2019-07-04 19:45:00 6 2019-05-06 17:18:00 6 2019-08-03 10:10:00

我已经尝试了一些方法，但是却没有像我想要的那样成功。我仍然缺少一些步骤，我不知道如何继续进行下去。这是我到目前为止所拥有的：

for(i in seq_along(df1$id)){ for(j in seq_along(df2$id)){ ifelse(df2$id[j] == df1$id[i]) { ifelse(df2$datetime_event[j] %within% df1$datetime_interval[i] == TRUE){ df1$datetime_event <- df2$datetime_ic_corr[j] } } } }

我想要的结果是这样

df1 ID datetime_event datetime_event event 1 2019-04-19 21:50:00 UTC--2019-04-20 21:31:00 UTC 2019-04-19 21:55:00 yes 1 2019-07-02 04:23:00 UTC--2019-07-02 08:51:00 UTC NA NA 2 2019-07-04 19:45:00 UTC--2019-07-05 00:30:00 UTC NA NA 3 2019-06-07 08:55:00 UTC--2019-06-07 14:43:00 UTC NA NA 3 2019-05-06 17:18:00 UTC--2019-05-06 23:18:00 UTC 2019-05-06 21:23:00 yes 6 2019-08-02 22:00:00 UTC--2019-08-04 03:10:00 UTC 2019-08-03 10:10:00 yes

在此先感谢您提供所有新输入！因为我被卡住了...

dput(df1) structure(list(ID = c(1, 1, 2, 3, 3, 6), datetime_interval = c("2019-04-19 21:50:00 UTC--2019-04-20 21:31:00 UTC", "2019-07-02 04:23:00 UTC--2019-07-02 08:51:00 UTC", "2019-07-04 19:45:00 UTC--2019-07-05 00:30:00 UTC", "2019-06-07 08:55:00 UTC--2019-06-07 14:43:00 UTC", "2019-05-06 17:18:00 UTC--2019-05-06 23:18:00 UTC", "2019-08-02 22:00:00 UTC--2019-08-04 03:10:00 UTC"), datetime_event = c("NA", "NA", "NA", "NA", "NA", "NA"), event = c("NA", "NA", "NA", "NA", "NA", "NA")), row.names = c(NA, -6L), class = c("tbl_df", "tbl", "data.frame")) dput(df2) structure(list(ID = c(1, 3, 5, 6, 6), datetime_event = c("2019-04-19 21:55:00 UTC", "2019-05-06 21:23:00 UTC", "2019-07-04 19:45:00 UTC", "2019-05-06 17:18:00 UTC", "2019-08-03 10:10:00 UTC")), row.names = c(NA, -5L), class = c("tbl_df", "tbl", "data.frame"))

Answer 1

棘手的问题。我认为这可行：

library(dplyr)
library(tidyr)

# convert datetime_interval to datetime class start and end columns
# and add row IDs
df1 = df1 %>% 
  separate(datetime_interval, into = c("start", "end"), sep = "--") %>%
  mutate_at(vars(start, end), as.POSIXct) %>%
  select(-datetime_event, -event) %>%
  mutate(row_id = row_number())

# convert datetime event to datetime class
df2 = df2 %>%
  mutate(datetime_event = as.POSIXct(datetime_event))

# join and filter
df1 %>% left_join(df2, by = "ID") %>%
  mutate(
    datetime_event = ifelse(datetime_event >= start & datetime_event <= end, datetime_event, NA),
    event = ifelse(is.na(datetime_event), NA, "yes")
  ) %>%
  arrange(row_id, datetime_event) %>%
  group_by(row_id) %>%
  slice(1)
# # A tibble: 6 x 6
# # Groups:   row_id [6]
#      ID start               end                 row_id datetime_event event
#   <dbl> <dttm>              <dttm>               <int>          <dbl> <chr>
# 1     1 2019-04-19 21:50:00 2019-04-20 21:31:00      1     1555725300 yes  
# 2     1 2019-07-02 04:23:00 2019-07-02 08:51:00      2             NA NA   
# 3     2 2019-07-04 19:45:00 2019-07-05 00:30:00      3             NA NA   
# 4     3 2019-06-07 08:55:00 2019-06-07 14:43:00      4             NA NA   
# 5     3 2019-05-06 17:18:00 2019-05-06 23:18:00      5     1557192180 yes  
# 6     6 2019-08-02 22:00:00 2019-08-04 03:10:00      6     1564841400 yes

如何根据多种条件将数据从一个数据帧复制到另一个数据帧

1 个答案: