Here is my dataset:
X Totally.Disagree Disagree Agree Totally.agree
0 2 9 111 122
1 2 30 124 88
2 4 31 119 90
3 10 43 138 53
4 33 54 85 72
5 43 79 89 33
6 48 83 94 19
7 51 98 80 15
8 50 102 75 17
9 51 96 80 17
Where X (thus each line) is a question and the values are the number of people who choose this answer to the question. I would like to compute the mode (the most chosen answer) for each question.
This is what I tried:
df <- gather(df,Answer, count, Totally.Disagree:Totally.agree )
df %>%
group_by(X, Answer) %>%
summarise(sum = count)%>%
summarise(mode = df$Answer[which(df$count== max(df$count))])
But it doesn't work because max(df$count) refers to the whole dataset and not just one question.
I do not now if the way I tried is correct. If one of you could help me resolve this, I would be very grateful.
A different approach could be:
df %>%
mutate(mode = max.col(.[2:length(.)])+1) %>%
rowwise() %>%
mutate(mode = names(.)[[mode]]) %>%
select(X, mode)
X mode
<int> <chr>
1 0 Totally.agree
2 1 Agree
3 2 Agree
4 3 Agree
5 4 Agree
6 5 Agree
7 6 Agree
8 7 Disagree
9 8 Disagree
10 9 Disagree
Here it, first, identifies the index of the column with the greatest count and then assigns the name of the column based on the column index.
And if you want to include also the numbers, you can try:
df %>%
mutate(mode = max.col(.[2:length(.)])+1) %>%
rowwise() %>%
mutate(mode_names = names(.)[[mode]],
mode_numbers = max(!!! rlang::syms(names(.)[2:length(.)]))) %>%
select(X, mode_names, mode_numbers)
X mode_names mode_numbers
<int> <chr> <dbl>
1 0 Totally.agree 122.
2 1 Agree 124.
3 2 Agree 119.
4 3 Agree 138.
5 4 Agree 85.
6 5 Agree 89.
7 6 Agree 94.
8 7 Disagree 98.
9 8 Disagree 102.
10 9 Disagree 96.
Or following your original logic:
df %>%
gather(mode_names, mode_numbers, -X) %>%
group_by(X) %>%
filter(mode_numbers == max(mode_numbers)) %>%
arrange(X)
X mode_names mode_numbers
<int> <chr> <int>
1 0 Totally.agree 122
2 1 Agree 124
3 2 Agree 119
4 3 Agree 138
5 4 Agree 85
6 5 Agree 89
7 6 Agree 94
8 7 Disagree 98
9 8 Disagree 102
10 9 Disagree 96