Count number of times a value occurs within a group R-CodePudding

I have a sample of my data as follows:

id = c(1, 2, 3, 4, 5, 1, 4, 7, 8, 3)
date = c("2020-12-31", "2020-12-31", "2020-12-31", "2020-12-31",
          "2020-12-31", "01-01-2021", "01-01-2021", "01-01-2021", "01-01-2021",
          "01-01-2021")
total = c(1, 4, 4, 15, 0, 12, 1, 1, 1, 0)
data = data.frame(id, date, total)

I am trying to count how many times a "total" value occurs per date. So for example, for the date "2020-12-31" the value 4 occurs twice but the value 1 only occurs once as it does for 15 and 0 for this date. And then for the date "01-01-2021" the value 1 occurs three times and so on. Essentially I would like the out to result in:

day = c("2020-12-31", "01-01-2021")
one = c(1, 3)
two = c(0, 0)
three = c(0, 0)
four = c(2, 0)
five = c( 0, 0)
six = c(0, 0)
seven = c(0,0)
eight = c(0, 0)
nine = c(0,0)
ten = c(0,0)
eleven = c(0,0)
twelve = c(0,1)
thirteen = c(0,0)
fourteen = c(0,0)
fifteen = c(1,0)
df = data.frame(day, one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen,
                  fourteen, fifteen)

so one column for the date and then the next 15 columns represent the number I am counting. (there are more dates for my data i just have not put them all in my example)

I started by grouping the original columns by:

data %>%
group_by(date, total)

But I am not sure how to count the values per group and put it in the resulting dataframe. Thanks!

CodePudding user response：

library(tidyr)
library(dplyr)
data %>%
  count(date, total) %>%
  complete(date, total = 0:15, fill = list(n = 0)) %>%
  pivot_wider(id_cols = date, names_from = total, values_from = n, names_prefix = "total")
# # A tibble: 2 × 17
#   date   total0 total1 total2 total3 total4 total5 total6 total7 total8 total9 total10 total11 total12
#   <chr>   <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>   <dbl>   <dbl>   <dbl>
# 1 01-01…      1      3      0      0      0      0      0      0      0      0       0       0       1
# 2 2020-…      1      1      0      0      2      0      0      0      0      0       0       0       0
# # … with 3 more variables: total13 <dbl>, total14 <dbl>, total15 <dbl>

CodePudding user response：

`as.data.frame.table is the time-honored method:

as.data.frame( with(data, table(date, total)))
#------------------------
         date total Freq
1  01-01-2021     0    1
2  2020-12-31     0    1
3  01-01-2021     1    3
4  2020-12-31     1    1
5  01-01-2021     4    0
6  2020-12-31     4    2
7  01-01-2021    12    1
8  2020-12-31    12    0
9  01-01-2021    15    0
10 2020-12-31    15    1

If you wanted this in a "wide" format, which is really a b*tch to work with then leave it as a tble:

with(data, table(date, total))
            total
date         0 1 4 12 15
  01-01-2021 1 3 0  1  0
  2020-12-31 1 1 2  0  1