Hey guys,
I do have the following dataframe
with 45 million observations:
year month variable
1992 1 0
1992 1 1
1992 1 1
1992 2 0
1992 2 1
1992 2 0
My goal is to count the frequency of the variable for each month of a year.
I was already able to generate these sums with cps_data
as my dataframe
and SKILL_1
as my variable
.
cps_data %>%
group_by(YEAR, MONTH) %>%
summarise_at(vars(SKILL_1),
list(name = sum))
Logically, I obtained 348 different rows as a tibble. Now, I struggle to create a new table with these values. My new table should look similar to my tibble. How can I do that? Is there even a way? I've already tried to read in an excel file with a date range from 01/1992 - 01/2021 in order to obtain exactly 349 rows and then merge it with the rows of the tibble, but it did not work..
# A tibble: 349 x 3
# Groups: YEAR [30]
YEAR MONTH name
<dbl> <int+lbl> <dbl>
1 1992 1 [January] 499
2 1992 2 [February] 482
3 1992 3 [March] 485
4 1992 4 [April] 457
5 1992 5 [May] 434
6 1992 6 [June] 470
7 1992 7 [July] 450
8 1992 8 [August] 438
9 1992 9 [September] 442
10 1992 10 [October] 427
# ... with 339 more rows
many thanks in advance!!