SQLDF R: Counting unique values in a data frame

Question

I have a data frame with one column. There are 10 rows.

(4.0 * 3.0)
(4.0 * 3.0)
(2.0 * (1.0 * (1.0 * 6.0)))
(4.0 * (3.0 * 1.0))
(6.0 * 2.0)
(6.0 * 2.0)
(2.0 * 6.0)
(2.0 * 6.0)
(2.0 * 6.0)
(6.0 * 2.0)

I need to extract the unique values in the column and the number of times it occurs. Using sqldf package I was able to get the unique values. But not the count.

Query:

sqldf("SELECT V1, COUNT(DISTINCT V1) as DinctC from dataset GROUP BY V1")

Output:

                           V1 DinctC
1 (2.0 * (1.0 * (1.0 * 6.0)))      1
2                 (2.0 * 6.0)      1
3         (4.0 * (3.0 * 1.0))      1
4                 (4.0 * 3.0)      1
5                 (6.0 * 2.0)      1

What I want is:

                           V1 DinctC
1 (2.0 * (1.0 * (1.0 * 6.0)))      1
2                 (2.0 * 6.0)      3
3         (4.0 * (3.0 * 1.0))      1
4                 (4.0 * 3.0)      2
5                 (6.0 * 2.0)      3

Edit : As Tim Biegeleisen pointed out "Distinct" is not a function therefore no need of the brackets. So updating DISTINCT(V1) to DISTINCT V1

Answer 1

We do not need the distinct keyword as we are using the GROUP BY clause.

sqldf("SELECT V1, COUNT(V1) as DinctC from dataset GROUP BY V1")

Result:

                           V1 DinctC
1 (2.0 * (1.0 * (1.0 * 6.0)))      1
2                 (2.0 * 6.0)      3
3         (4.0 * (3.0 * 1.0))      1
4                 (4.0 * 3.0)      2
5                 (6.0 * 2.0)      3

Answer 2

We can use count

library(dplyr)
count(df, V1)
# A tibble: 5 x 2
#                          V1     n
#                       <chr> <int>
#1 (2.0 * (1.0 * (1.0 * 6.0)))     1
#2                 (2.0 * 6.0)     3
#3         (4.0 * (3.0 * 1.0))     1
#4                 (4.0 * 3.0)     2
#5                 (6.0 * 2.0)     3

---

Or table from base R

table(df$V1)