Dear All,
I am trying to reshape the data with some conditions. A small part of the
data looks like below. Like this there will be more data with repeating ID.
Count id name type
117 335 sally A
19 335 sally A
167 335 sally B
18 340 susan A
56 340 susan A
22 340 susan B
53 340 susan B
135 351 lee A
114 351 lee A
84 351 lee A
80 351 lee A
19 351 lee A
8 351 lee A
21 351 lee A
88 351 lee B
111 351 lee B
46 351 lee B
108 351 lee B
>From the above data I am expecting an output like below.
id name type count_of_B Max of count B x y
335 sally B 167 167 117,19 NA
340 susan B 22,53 53 18 56
351 lee B 88,111,46,108 111 84,80,19,8,2 135,114
Where, the column x and column y are:
x = Count_A_less_than_max of (Count type B)
y = Count_A_higher_than_max of (Count type B).
*1)* I tried with dplyr with the following code for the initial step to get
the values for each column.
*2)* I thought to transpose the columns which has the unique ID alone.
I tried with the following code and I am struck with the intial step
itself. The code is executed but higher and lower value of A is not coming.
Expected_output= data %>%
group_by(id, Type) %>%
mutate(Count_of_B = paste(unlist(count[Type=="B"]), collapse = ","))%>%
mutate(Max_of_count_B = ifelse(Type == "B", max(count[Type ==
"B"]),max(count[Type == "A"]))) %>%
mutate(count_type_A_lesser = ifelse
(Type=="B",(paste(unlist(count[Type=="A"]) < Max_of_count_B[Type=="B"],
collapse = ",")), "NA"))%>%
mutate(count_type_A_higher =
ifelse(Type=="B",(paste(unlist(count[Type=="A"]) >
Max_of_count_B[Type=="B"], collapse = ",")), "NA"))
I hope I make my point clear. Please bare with the code, as I am new to
this.
Regards,
sri
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