R weird output to dataframe

Question

I am very new to R, and come from more of a python background. I am working on a project that requires using R and am nearly finished with the results, but have stumbled on this final issue.

I wrote a function in R that gave me the output I was looking for, but in an absolutely abysmal way.

I would like to put this into an R dataframe, with comp_count, variance, execution_time, and accuracy as columns. I would need to drop the null values as well. Any advice?

Edit: output of dput(results) asked for.

    list(NULL, list(comp_count = 2L, variance = 32.6, execution_time = 2.15086028575897, 
    accuracy = 0.782779827798278), list(comp_count = 3L, variance = 43.3, 
    execution_time = 2.671033902963, accuracy = 0.832069775243207), 
    list(comp_count = 4L, variance = 52, execution_time = 3.50883383353551, 
        accuracy = 0.839405121323941), list(comp_count = 5L, 
        variance = 58.6, execution_time = 3.92320603132248, accuracy = 0.842938611204294), 
    list(comp_count = 6L, variance = 64.3, execution_time = 4.39138143459956, 
        accuracy = 0.843139885944314), list(comp_count = 7L, 
        variance = 69.2, execution_time = 5.430861667792, accuracy = 0.843609527004361), 
    list(comp_count = 8L, variance = 73.7, execution_time = 6.1574295481046, 
        accuracy = 0.844459353684446), list(comp_count = 9L, 
        variance = 77.1, execution_time = 6.21873023509979, accuracy = 0.845219724924522), 
    list(comp_count = 10L, variance = 80.5, execution_time = 7.65496598482132, 
        accuracy = 0.846069551604607), list(comp_count = 11L, 
        variance = 83.8, execution_time = 6.71301571528117, accuracy = 0.846024823884602), 
    list(comp_count = 12L, variance = 87, execution_time = 8.45073886712392, 
        accuracy = 0.846740467404674), list(comp_count = 13L, 
        variance = 89.9, execution_time = 9.64280251661936, accuracy = 0.846293190204629), 
    list(comp_count = 14L, variance = 92.5, execution_time = 9.80074710051219, 
        accuracy = 0.846382645644638), list(comp_count = 15L, 
        variance = 94.7, execution_time = 10.3888318975766, accuracy = 0.846091915464609), 
    NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, 
    NULL, NULL, NULL, NULL, list(comp_count = 30L, variance = 100, 
        execution_time = 20.8339449683825, accuracy = 0.8589958626859))

I can access separate components by this:

results[[2]]

$comp_count
[1] 2

$variance
[1] 32.6

$execution_time
[1] 2.15086

$accuracy
[1] 0.7827798

What is the best way to go about this? All help is greatly appreciated!

Answer 1

Unfortunately you don't provide sample data in an easily copy&paste-able format; for future posts it's better to use dput , especially when the data structure is a critical component of your problem description.

I will generate some (hopefully) representative and minimal sample data

lst <- list(
    NULL,
    list(comp_count = 2, variance = 32.6, execution_time = 2.15, accuracy = 0.78),
    list(comp_count = 3, variance = 43.3, execution_time = 2.67, accuracy = 0.83)
)

Then you can use

do.call(rbind.data.frame, lst)
#   comp_count variance execution_time accuracy
#2           2     32.6           2.15     0.78
#21          3     43.3           2.67     0.83

to row-bind list elements into a data.frame .

Note that this requires all (non- NULL ) list elements to have the same number of elements.

Another option is to use dplyr::bind_rows

library(dplyr)
bind_rows(lst)
## A tibble: 2 x 4
#  comp_count variance execution_time accuracy
#       <dbl>    <dbl>          <dbl>    <dbl>
#1          2     32.6           2.15     0.78
#2          3     43.3           2.67     0.83

---

With your updated sample data

do.call(rbind.data.frame, lst)
#   comp_count variance execution_time  accuracy
#2           2     32.6       2.150860 0.7827798
#21          3     43.3       2.671034 0.8320698
#3           4     52.0       3.508834 0.8394051
#4           5     58.6       3.923206 0.8429386
#5           6     64.3       4.391381 0.8431399
#6           7     69.2       5.430862 0.8436095
#7           8     73.7       6.157430 0.8444594
#8           9     77.1       6.218730 0.8452197
#9          10     80.5       7.654966 0.8460696
#10         11     83.8       6.713016 0.8460248
#11         12     87.0       8.450739 0.8467405
#12         13     89.9       9.642803 0.8462932
#13         14     92.5       9.800747 0.8463826
#14         15     94.7      10.388832 0.8460919
#15         30    100.0      20.833945 0.8589959

---

Sample data

lst <- list(NULL, list(comp_count = 2L, variance = 32.6, execution_time = 2.15086028575897,
    accuracy = 0.782779827798278), list(comp_count = 3L, variance = 43.3,
    execution_time = 2.671033902963, accuracy = 0.832069775243207),
    list(comp_count = 4L, variance = 52, execution_time = 3.50883383353551,
        accuracy = 0.839405121323941), list(comp_count = 5L,
        variance = 58.6, execution_time = 3.92320603132248, accuracy = 0.842938611204294),
    list(comp_count = 6L, variance = 64.3, execution_time = 4.39138143459956,
        accuracy = 0.843139885944314), list(comp_count = 7L,
        variance = 69.2, execution_time = 5.430861667792, accuracy = 0.843609527004361),
    list(comp_count = 8L, variance = 73.7, execution_time = 6.1574295481046,
        accuracy = 0.844459353684446), list(comp_count = 9L,
        variance = 77.1, execution_time = 6.21873023509979, accuracy = 0.845219724924522),
    list(comp_count = 10L, variance = 80.5, execution_time = 7.65496598482132,
        accuracy = 0.846069551604607), list(comp_count = 11L,
        variance = 83.8, execution_time = 6.71301571528117, accuracy = 0.846024823884602),
    list(comp_count = 12L, variance = 87, execution_time = 8.45073886712392,
        accuracy = 0.846740467404674), list(comp_count = 13L,
        variance = 89.9, execution_time = 9.64280251661936, accuracy = 0.846293190204629),
    list(comp_count = 14L, variance = 92.5, execution_time = 9.80074710051219,
        accuracy = 0.846382645644638), list(comp_count = 15L,
        variance = 94.7, execution_time = 10.3888318975766, accuracy = 0.846091915464609),
    NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL,
    NULL, NULL, NULL, NULL, list(comp_count = 30L, variance = 100,
        execution_time = 20.8339449683825, accuracy = 0.8589958626859))