对于具有来自R中数据帧的多个参数的循环
我想知道是否有可能在R中构建一个FOR循环，它将在每次运行时更改多个参数 我有参数dataframe[df_params]，如下所示：对于具有来自R中数据帧的多个参数的循环,r,dataframe,date,lubridate,R,Dataframe,Date,Lubridate,我想知道是否有可能在R中构建一个FOR循环，它将在每次运行时更改多个参数 我有参数dataframe[df_params]，如下所示： group person date_from date_to 1 Mike 2020-10-01 12:00:00 2020-10-01 13:00:00 2 Mike 2020-10-04 09:00:00 2020-10-07 17:00:00 3 Dave
group person date_from date_to
1 Mike 2020-10-01 12:00:00 2020-10-01 13:00:00
2 Mike 2020-10-04 09:00:00 2020-10-07 17:00:00
3 Dave 2020-10-07 12:00:00 2020-10-07 13:00:00
4 Dave 2020-10-09 09:00:00 2020-10-11 17:00:00
person datetime books tasks done
Mike 2020-10-01 12:15:00 5 7 2
Mike 2020-10-01 12:17:00 5 7 3
Mike 2020-10-01 18:00:00 5 7 4
Mike 2020-10-02 12:00:00 5 5 0
Mike 2020-10-04 09:08:00 5 3 3
Mike 2020-10-09 12:00:00 5 7 1
Dave 2020-10-07 12:22:00 7 5 1
Dave 2020-10-08 02:34:00 7 5 2
Dave 2020-10-09 07:00:00 7 3 3
Dave 2020-10-09 08:00:00 7 8 5
Dave 2020-10-09 09:48:00 7 7 2
Nick 2020-10-01 13:00:00 3 7 3
Nick 2020-10-02 12:58:00 3 3 2
Nick 2020-10-03 10:02:00 3 7 1
person datetime books tasks done group
Mike 2020-10-01 12:15:00 5 7 2 1
Mike 2020-10-01 12:17:00 5 7 3 1
Mike 2020-10-04 09:08:00 5 3 3 2
Dave 2020-10-07 12:22:00 7 5 1 3
Dave 2020-10-09 09:48:00 7 7 2 4
group person date_from date_to
1 Mike 2020-10-01 12:00:00 2020-10-01 13:00:00
2 Mike 2020-10-04 09:00:00 2020-10-07 17:00:00
3 Dave 2020-10-07 12:00:00 2020-10-07 13:00:00
4 Dave 2020-10-09 09:00:00 2020-10-11 17:00:00
person datetime books tasks done
Mike 2020-10-01 12:15:00 5 7 2
Mike 2020-10-01 12:17:00 5 7 3
Mike 2020-10-01 18:00:00 5 7 4
Mike 2020-10-02 12:00:00 5 5 0
Mike 2020-10-04 09:08:00 5 3 3
Mike 2020-10-09 12:00:00 5 7 1
Dave 2020-10-07 12:22:00 7 5 1
Dave 2020-10-08 02:34:00 7 5 2
Dave 2020-10-09 07:00:00 7 3 3
Dave 2020-10-09 08:00:00 7 8 5
Dave 2020-10-09 09:48:00 7 7 2
Nick 2020-10-01 13:00:00 3 7 3
Nick 2020-10-02 12:58:00 3 3 2
Nick 2020-10-03 10:02:00 3 7 1
person datetime books tasks done group
Mike 2020-10-01 12:15:00 5 7 2 1
Mike 2020-10-01 12:17:00 5 7 3 1
Mike 2020-10-04 09:08:00 5 3 3 2
Dave 2020-10-07 12:22:00 7 5 1 3
Dave 2020-10-09 09:48:00 7 7 2 4
group person date_from date_to
1 Mike 2020-10-01 12:00:00 2020-10-01 13:00:00
2 Mike 2020-10-04 09:00:00 2020-10-07 17:00:00
3 Dave 2020-10-07 12:00:00 2020-10-07 13:00:00
4 Dave 2020-10-09 09:00:00 2020-10-11 17:00:00
person datetime books tasks done
Mike 2020-10-01 12:15:00 5 7 2
Mike 2020-10-01 12:17:00 5 7 3
Mike 2020-10-01 18:00:00 5 7 4
Mike 2020-10-02 12:00:00 5 5 0
Mike 2020-10-04 09:08:00 5 3 3
Mike 2020-10-09 12:00:00 5 7 1
Dave 2020-10-07 12:22:00 7 5 1
Dave 2020-10-08 02:34:00 7 5 2
Dave 2020-10-09 07:00:00 7 3 3
Dave 2020-10-09 08:00:00 7 8 5
Dave 2020-10-09 09:48:00 7 7 2
Nick 2020-10-01 13:00:00 3 7 3
Nick 2020-10-02 12:58:00 3 3 2
Nick 2020-10-03 10:02:00 3 7 1
person datetime books tasks done group
Mike 2020-10-01 12:15:00 5 7 2 1
Mike 2020-10-01 12:17:00 5 7 3 1
Mike 2020-10-04 09:08:00 5 3 3 2
Dave 2020-10-07 12:22:00 7 5 1 3
Dave 2020-10-09 09:48:00 7 7 2 4
非常感谢您的建议。如果您的数据集非常大，这可能是一个稍微昂贵的解决方案，但它会输出所需的结果 我不知道你的日期变量是否已经是日期格式；在下面，我用lubridate包转换它们，以防它们不是 此外，我还创建了变量
date\u intervallibrary(dplyr)
library(lubridate)
# convert to date format
df_params <- df_params %>%
mutate(
date_from = ymd_hms(date_from),
date_to = ymd_hms(date_to),
# create interval
date_interval = interval(date_from, date_to)
)
df <- df %>%
mutate(datetime = ymd_hms(datetime))
开始数据
df_params <- read.table(text="
group person date_from date_to
1 Mike 2020-10-01T12:00:00 2020-10-01T13:00:00
2 Mike 2020-10-04T09:00:00 2020-10-07T17:00:00
3 Dave 2020-10-07T12:00:00 2020-10-07T13:00:00
4 Dave 2020-10-09T09:00:00 2020-10-11T17:00:00", header=T)
df <- read.table(text="
person datetime books tasks done
Mike 2020-10-01T12:15:00 5 7 2
Mike 2020-10-01T12:17:00 5 7 3
Mike 2020-10-01T18:00:00 5 7 4
Mike 2020-10-02T12:00:00 5 5 0
Mike 2020-10-04T09:08:00 5 3 3
Mike 2020-10-09T12:00:00 5 7 1
Dave 2020-10-07T12:22:00 7 5 1
Dave 2020-10-08T02:34:00 7 5 2
Dave 2020-10-09T07:00:00 7 3 3
Dave 2020-10-09T08:00:00 7 8 5
Dave 2020-10-09T09:48:00 7 7 2
Nick 2020-10-01T13:00:00 3 7 3
Nick 2020-10-02T12:58:00 3 3 2
Nick 2020-10-03T10:02:00 3 7 1 ", header=T)
df_参数是您可以获得与参数中特定条件匹配的单独行。您是否需要根据个人的特定值在df中创建一个新列？您好，我需要创建一个只包含选定行的新数据框。好的，是的。听起来您想执行merge（）
或union（）
这是一种数据库类型的函数，您可以在其中获取两个数据集，并根据匹配条件将它们连接起来。您需要在行上匹配哪些标准？然后你告诉函数你希望它如何匹配，谢谢。它工作得很好！