How to copy rows by POSIXct interval and past it on top of the same dataframe?

Question

My dataframe looks like this:

 dput(head(sAUR,50))
structure(list(date = structure(c(1475315922, 1475660422, 1475920222, 
1476179992, 1476524422, 1476784232, 1477044062, 1477388482, 1477648302, 
1477911722, 1478256142, 1478515962, 1478775782, 1479120192, 1479380002, 
1479639822, 1479984232, 1480244042, 1480503862, 1480848262, 1481108072, 
1481367882, 1481712272, 1481972082, 1482231892, 1482576282, 1482836082, 
1483095882, 1483440272, 1484304241, 1484564041, 1484823831, 1485428001, 
1485687791, 1486032161, 1486291941, 1486551731, 1486896101, 1487155881, 
1487415671, 1487760031, 1488019821, 1488279601, 1488624021, 1488883821, 
1489143521, 1489488011, 1489747821, 1490007451, 1490352021), class = c("POSIXct", 
"POSIXt"), tzone = ""), layer = c("AUR", "AUR", "AUR", "AUR", 
"AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", 
"AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", 
"AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", 
"AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", 
"AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", 
"AUR")), row.names = c(NA, 50L), class = "data.frame")

I want to copy the rows from 2017-02-18 11:01:11 (1487415671) until 2017-03-20 10:57:31 (1490007451) and paste them to the top of the dataframe while keeping the original data, in other words, I want to add this chunk of rows on top of the original dataframe.

(if there's a solution using the index I would consider it as well)

Any help will be much appreciated.

score 3 · Accepted Answer · answered Jul 06 '22 at 12:00

Option using rbind:

sAUR_copy <- subset(sAUR, date %in% 1487415671:1490007451)
rbind(sAUR_copy, sAUR)
#>                    date layer
#> 40  2017-02-18 12:01:11   AUR
#> 41  2017-02-22 11:40:31   AUR
#> 42  2017-02-25 11:50:21   AUR
#> 43  2017-02-28 12:00:01   AUR
#> 44  2017-03-04 11:40:21   AUR
#> 45  2017-03-07 11:50:21   AUR
#> 46  2017-03-10 11:58:41   AUR
#> 47  2017-03-14 11:40:11   AUR
#> 48  2017-03-17 11:50:21   AUR
#> 49  2017-03-20 11:57:31   AUR
#> 1   2016-10-01 11:58:42   AUR
#> 2   2016-10-05 11:40:22   AUR
#> 3   2016-10-08 11:50:22   AUR
#> 4   2016-10-11 11:59:52   AUR
#> 5   2016-10-15 11:40:22   AUR
#> 6   2016-10-18 11:50:32   AUR
#> 7   2016-10-21 12:01:02   AUR
#> 8   2016-10-25 11:41:22   AUR
#> 9   2016-10-28 11:51:42   AUR
#> 10  2016-10-31 12:02:02   AUR
#> 11  2016-11-04 11:42:22   AUR
#> 12  2016-11-07 11:52:42   AUR
#> 13  2016-11-10 12:03:02   AUR
#> 14  2016-11-14 11:43:12   AUR
#> 15  2016-11-17 11:53:22   AUR
#> 16  2016-11-20 12:03:42   AUR
#> 17  2016-11-24 11:43:52   AUR
#> 18  2016-11-27 11:54:02   AUR
#> 19  2016-11-30 12:04:22   AUR
#> 20  2016-12-04 11:44:22   AUR
#> 21  2016-12-07 11:54:32   AUR
#> 22  2016-12-10 12:04:42   AUR
#> 23  2016-12-14 11:44:32   AUR
#> 24  2016-12-17 11:54:42   AUR
#> 25  2016-12-20 12:04:52   AUR
#> 26  2016-12-24 11:44:42   AUR
#> 27  2016-12-27 11:54:42   AUR
#> 28  2016-12-30 12:04:42   AUR
#> 29  2017-01-03 11:44:32   AUR
#> 30  2017-01-13 11:44:01   AUR
#> 31  2017-01-16 11:54:01   AUR
#> 32  2017-01-19 12:03:51   AUR
#> 33  2017-01-26 11:53:21   AUR
#> 34  2017-01-29 12:03:11   AUR
#> 35  2017-02-02 11:42:41   AUR
#> 36  2017-02-05 11:52:21   AUR
#> 37  2017-02-08 12:02:11   AUR
#> 38  2017-02-12 11:41:41   AUR
#> 39  2017-02-15 11:51:21   AUR
#> 401 2017-02-18 12:01:11   AUR
#> 411 2017-02-22 11:40:31   AUR
#> 421 2017-02-25 11:50:21   AUR
#> 431 2017-02-28 12:00:01   AUR
#> 441 2017-03-04 11:40:21   AUR
#> 451 2017-03-07 11:50:21   AUR
#> 461 2017-03-10 11:58:41   AUR
#> 471 2017-03-14 11:40:11   AUR
#> 481 2017-03-17 11:50:21   AUR
#> 491 2017-03-20 11:57:31   AUR
#> 50  2017-03-24 11:40:21   AUR

^{Created on 2022-07-06 by the reprex package (v2.0.1)}

score 1 · Answer 2 · answered Jul 06 '22 at 12:00

Tidyverse approach:


library(tibble)
library(dplyr)

df <- structure(list(
  date = structure(
    c(1475315922, 1475660422, 1475920222, 
      1476179992, 1476524422, 1476784232, 1477044062, 1477388482, 1477648302, 
      1477911722, 1478256142, 1478515962, 1478775782, 1479120192, 1479380002, 
      1479639822, 1479984232, 1480244042, 1480503862, 1480848262, 1481108072, 
      1481367882, 1481712272, 1481972082, 1482231892, 1482576282, 1482836082, 
      1483095882, 1483440272, 1484304241, 1484564041, 1484823831, 1485428001, 
      1485687791, 1486032161, 1486291941, 1486551731, 1486896101, 1487155881, 
      1487415671, 1487760031, 1488019821, 1488279601, 1488624021, 1488883821, 
      1489143521, 1489488011, 1489747821, 1490007451, 1490352021), 
    class = c("POSIXct", "POSIXt"), tzone = ""), 
    layer = c("AUR", "AUR", "AUR", "AUR", 
             "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", 
             "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", 
             "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", 
             "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", 
             "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", "AUR", 
             "AUR")), 
    row.names = c(NA, 50L), 
    class = "data.frame"
)

new_df <- df %>% 
  as_tibble() %>% 
  filter(between(date, 1487415671, 1490007451)) %>% 
  bind_rows(df)

new_df

#> # A tibble: 60 × 2
#>    date                layer
#>    <dttm>              <chr>
#>  1 2017-02-18 17:01:11 AUR  
#>  2 2017-02-22 16:40:31 AUR  
#>  3 2017-02-25 16:50:21 AUR  
#>  4 2017-02-28 17:00:01 AUR  
#>  5 2017-03-04 16:40:21 AUR  
#>  6 2017-03-07 16:50:21 AUR  
#>  7 2017-03-10 16:58:41 AUR  
#>  8 2017-03-14 16:40:11 AUR  
#>  9 2017-03-17 16:50:21 AUR  
#> 10 2017-03-20 16:57:31 AUR  
#> # … with 50 more rows

Created on 2022-07-06 by the reprex package (v2.0.1)

score 0 · Answer 3 · answered Jul 06 '22 at 11:50

0

You could create a new dataframe of the rows you'd like to have at top, lets call it df1:

library(dplyr)
df1 = df %>% filter(date>1487415671, date<1490007451)

Assuming df is your original dataset. And removing thoes rows from your df:

df = df%>% filter(!(date>1487415671, date<1490007451))

And then bind them together again:

df = bind_rows(df1,df)

answered Jul 06 '22 at 11:50

Pedro

150
10

I don't need to remove those dates I want to copy. – Cláudio Siva Jul 06 '22 at 12:49
I understand, You are removing them temporary, then you're taking them back but at the top as you desired. – Pedro Jul 06 '22 at 14:13
In this case no. I'm manipulating the dates to have an exact data repetition on top of the dataframe. – Cláudio Siva Jul 06 '22 at 14:15

score 0 · Answer 4 · answered Jul 06 '22 at 11:57

0

You can do in base R:

rg <- c(as.POSIXct("2017-02-18 11:01:11"), as.POSIXct("2017-03-20 10:57:31"))
pos <- df$date >= rg[1] & df$date <= rg[2]
rbind.data.frame(df[pos, ], df[!pos, ])

Please take care of timezone argument in as.POSIXct

answered Jul 06 '22 at 11:57

Clemsang

5,053
3
23
41

How to copy rows by POSIXct interval and past it on top of the same dataframe?

4 Answers4