Using `map()` in nested data frame

Question

I am having some problems using the map() function along with the nest() function.

I have some data set up like the following:

counter

    counter           date_time total
1  06032013 2013-06-03 16:00:00   476
2  06032013 2013-06-03 17:00:00   578
3  06032013 2013-06-03 18:00:00   406
4  06032013 2013-06-03 19:00:00   272
5  06032013 2013-06-03 20:00:00   240
6  06032013 2013-06-03 21:00:00    96
7  06032013 2013-06-03 22:00:00    67
8  06032013 2013-06-03 23:00:00    37
9  06032013 2013-06-04 00:00:00    10
10 06032013 2013-06-04 01:00:00    11
11 06032013 2013-06-04 02:00:00     8
12 06032013 2013-06-04 03:00:00     9
13 06032013 2013-06-04 04:00:00    23
14 06032013 2013-06-04 05:00:00    83
15 06032013 2013-06-04 06:00:00   291
16 06032013 2013-06-04 07:00:00   532
17 06032013 2013-06-04 08:00:00   434
18 06032013 2013-06-04 09:00:00   326
19 06032013 2013-06-04 10:00:00   310
20 06032013 2013-06-04 11:00:00   292

I then nested these data based on the counter field. Such as:

y <- counters %>% nest(-counter)

y 

# A tibble: 140 × 2
    counter               data
      <chr>             <list>
1  06032013  <tibble [91 × 2]>
2  62295051 <tibble [310 × 2]>
3  81295014 <tibble [301 × 2]>
4  81295015 <tibble [294 × 2]>
5  81295091 <tibble [303 × 2]>
6  81295092 <tibble [306 × 2]>
7  81313062 <tibble [142 × 2]>
8  81313063 <tibble [142 × 2]>
9  82295046 <tibble [139 × 2]>
10 82295050 <tibble [141 × 2]>

What I want to do is map over each nested data frame and construct an xts matrix in my nested data frame. I tried many variations of the following code:

y %>% mutate(stuff = map(xts(data$total, order.by = data$date_time)))

I am greeted with Error in data$date_time : object of type 'closure' is not subsettable.

Any thoughts would be great!

Wrong syntax. Try this: y %>% mutate(stuff = map(data, ~ xts(.x$total, order.by = .x$date_time))) — Michael Griffiths
– Michael Griffiths, Commented Dec 20, 2016 at 4:23
If you find purrr's formula notation confusing, compare it with standard anonymous function notation: y %>% mutate(stuff = map(data, function(x){xts(x$total, order.by = x$date_time)})). Make sure you pass data, the name of the list column you want it to iterate over, and then refer to the data within each element of data via the variable you're passing the function (.x by default in purrr). — alistaire
– alistaire, Commented Dec 20, 2016 at 4:47

thus__ · Accepted Answer · 2016-12-20 15:38:19Z

7

@Michael-Griffiths thank you for your help! The following code worked for me:

y %>% mutate(stuff = map(data, ~xts(order.by = .x$date_time)))

# A tibble: 140 × 3
    counter               data     stuff
     <fctr>             <list>    <list>
1  06032013  <tibble [91 × 2]> <S3: xts>
2  62295051 <tibble [310 × 2]> <S3: xts>
3  81295014 <tibble [301 × 2]> <S3: xts>
4  81295015 <tibble [294 × 2]> <S3: xts>
5  81295091 <tibble [303 × 2]> <S3: xts>
6  81295092 <tibble [306 × 2]> <S3: xts>
7  81313062 <tibble [142 × 2]> <S3: xts>
8  81313063 <tibble [142 × 2]> <S3: xts>
9  82295046 <tibble [139 × 2]> <S3: xts>
10 82295050 <tibble [141 × 2]> <S3: xts>
# ... with 130 more rows

Still not 100% sure as to why. But hey, it worked.

answered Dec 20, 2016 at 15:38

thus__

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