Adding vectors to an already populated dataframe

Question

Infrequent R user here, I have a set of CSV files that are already populated with data from another program. There is a requirement to insert a new set of values into this dataframe (calendar_dates) via R.

Screencap of data

I'm trying to insert a new service_id, date, and exception_type. My understanding is that R doesn't much care what the data type is, but just to be clear, I have other files that need the same fix, but they require text fields.

I've tried searching on the internet, but all the answers I come across seem to require a much deeper understanding of R than I have. I'm hoping someone can provide an example I can learn from. Tutorial recommendations gratefully accepted. My new entry will simply be HD,1,1,1,1,1,1,1,20210906,20220102

Here is a sample file generated via dput():

dput(TL_calendar_dates)
structure(list(service_id = c(1L, 1L, 1L, 101L, 101L, 101L, 101L, 
101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 
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20211231L), exception_type = c(2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
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1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L)), class = "data.frame", row.names = c(NA, 
-950L))

I am struggling to understand what you want to add to the CSV file, joining columns in R can be as easy as just using cbind(), but it depends on what you want to join and how. It might help to post a reproducible example too: https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example — Giulio Centorame, Nov 26 '21 at 16:03
Sorry, I thought the screen capture illustrated it. I'm not looking to join columns, just enter new data into an existing structure. Here's a text emaple: service_id,monday,tuesday,wednesday,thursday,friday,saturday,sunday,start_date,end_date 1,1,1,1,1,1,0,0,20210906,20220102 101,0,0,0,0,0,0,0,20210906,20220102 1101,0,0,0,0,0,0,0,20210906,20220102 and I want to add a new entry like, 1201,0,0,0,0,0,0,0,0,20210906,20220102 — kill9all, Nov 26 '21 at 16:11
It might be easier if you use dput(), so we can reproduce it on our machine too. E.g. if you stored your table in `obj_name`, it would be `dput(obj_name)`. You can then copy and paste the output here — Giulio Centorame, Nov 26 '21 at 16:15
Thanks, as I mentioned new and infrequent R user with an inherited solution: dput(TL_calendar_dates) structure(list(service_id = c(1L, 1L, 1L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, 101L, — kill9all, Nov 26 '21 at 16:36
No problem! Hmm, it gets truncated by the comment length, it might be better if you edit your original question with it — Giulio Centorame, Nov 26 '21 at 17:13

score 1 · Accepted Answer · answered Nov 27 '21 at 16:33

It sounds like you just want to add a row of data to an already created data.frame, is that correct?

If so, there are several ways to do this.

Based on your data, I created a simple data.frame:

TL_calendar_dates <- data.frame(
  service_id = c(1,1,1,101,101,101),
  date = c(20210906, 20211011, 20211111, 20210907, 20210908, 20210909),
  exception_type = c(2,2,2,1,1,1)
)

TL_calendar_dates

service_id     date exception_type
1          1 20210906              2
2          1 20211011              2
3          1 20211111              2
4        101 20210907              1
5        101 20210908              1
6        101 20210909              1

Say you have a vector containing data to add to this data.frame:

vec <- c(101, 20210916, 3)

You can combine them (adding vec at the bottom) using rbind:

rbind(TL_calendar_dates, vec)

  service_id     date exception_type
1          1 20210906              2
2          1 20211011              2
3          1 20211111              2
4        101 20210907              1
5        101 20210908              1
6        101 20210909              1
7        101 20210916              3

If you are learning tidyverse, there are a couple of additional options.

One, you can use add_row from tibble and explicitly describe what values go into what columns:

library(tidyverse)

add_row(TL_calendar_dates, 
        service_id = 2,
        date = 20210920,
        exception_type = 4)

  service_id     date exception_type
1          1 20210906              2
2          1 20211011              2
3          1 20211111              2
4        101 20210907              1
5        101 20210908              1
6        101 20210909              1
7          2 20210920              4

Or you can use bind_rows from dplyr in a similar way:

bind_rows(TL_calendar_dates, 
          c(service_id = 3, date = 20210921, exception_type = 5))

  service_id     date exception_type
1          1 20210906              2
2          1 20211011              2
3          1 20211111              2
4        101 20210907              1
5        101 20210908              1
6        101 20210909              1
7          3 20210921              5

Note that for all these examples, you will notice that the rows added are not cumulative. You will need to make sure to assign the result to either the same data.frame or a new data.frame, such as:

TL_calendar_dates_NEW <- rbind(TL_calendar_dates, vec)

In that way, your result will be stored in the new TL_calendar_dates_NEW data.frame.

Thanks for your time, patience, and mostly, thoroughness. In the end the vector (rbind) solution worked fine for me. I tried the others out as well, but the vector one doesn't require additional libraries so it will be easier for the next person to support (I hope!) — kill9all, Nov 30 '21 at 15:27

Adding vectors to an already populated dataframe

1 Answers1