I've been on Stack Overflow for the past few days trying to get a solution to this issue I'm having.
I'm analyzing data received from the National Student Clearinghouse, specifically the graduations. So I have some dummy data
df <- data.frame(id=c('1', '1', '1'), grad_date=c('20160501', '20170524', '20180524'), order=c('1', '2', '3'), inst_name=c('community college 1', 'univ 1', 'univ 2'), inst_state=c('CA', 'CA', 'CA'), level=c('Associate of Applied Sciences', 'Bachelors of Applied Sciences', 'Masters of Applied Sciences'), deg_maj_1=c('NETWORK SECURITY', 'INFO ASSUR CYBR-SECURITY', 'CISCO CCNA PREPARATION'), deg_cip_1=c('111003', '520299', '111003'), deg_maj_2=c('NA', 'NA', 'NA'), deg_cip_2=c('NA', 'NA', 'NA'), deg_maj_3=c('NA', 'NA', 'NA'), deg_cip_3=c('NA', 'NA', 'NA'), deg_maj_4=c('NA', 'NA', 'NA'), deg_cip_4=c('NA', 'NA', 'NA'))
and I'm trying to get this data wide:
df_wide<- dcast(df, id ~ order, value.var = c("inst_name", "inst_state", "level", "deg_maj_1", "deg_cip_1", "deg_maj_2", "deg_cip_2", "deg_maj_3", "deg_cip_3", "deg_maj_4", "deg_cip_4"))
and I received this error:
Error in .subset2(x, i, exact = exact) : recursive indexing failed at level 2
I went here and here and got the same error
If this helps:
str(df)
'data.frame': 3 obs. of 14 variables:
$ id : Factor w/ 1 level "1": 1 1 1
$ grad_date : Factor w/ 3 levels "20160501","20170524",..: 1 2 3
$ order : Factor w/ 3 levels "1","2","3": 1 2 3
$ inst_name : Factor w/ 3 levels "community college 1",..: 1 2 3
$ inst_state: Factor w/ 1 level "CA": 1 1 1
$ level : Factor w/ 3 levels "Associate of Applied Sciences",..: 1 2 3
$ deg_maj_1 : Factor w/ 3 levels "CISCO CCNA PREPARATION",..: 3 2 1
$ deg_cip_1 : Factor w/ 2 levels "111003","520299": 1 2 1
$ deg_maj_2 : Factor w/ 1 level "NA": 1 1 1
$ deg_cip_2 : Factor w/ 1 level "NA": 1 1 1
$ deg_maj_3 : Factor w/ 1 level "NA": 1 1 1
$ deg_cip_3 : Factor w/ 1 level "NA": 1 1 1
$ deg_maj_4 : Factor w/ 1 level "NA": 1 1 1
$ deg_cip_4 : Factor w/ 1 level "NA": 1 1 1
Can anyone assist? I'm at my wits end
Edited to add: Desired Output (yes I know it's looooooooooong but it is needed)
df_wide <- data.frame(id=c('1'), grad_date=c('20160501'), inst_name_1=c('community college 1'), inst_state_1=c('CA'), level_1=c('Associate of Applied Sciences'), deg_maj_1_1=c('NETWORK SECURITY'), deg_cip_1_1=c('111003'), deg_maj_2_1=c('NA'), deg_cip_2_1=c('NA'), deg_maj_3_1=c('NA'), deg_cip_3_1=c('NA'), deg_maj_4_1=c('NA'), deg_cip_4_1=c('NA'), inst_name_2=c('univ 1'), inst_state_2=c('CA'), level_2=c('Bachelors of Applied Sciences'), deg_maj_1_2=c('INFO ASSUR CYBR-SECURITY'), deg_cip_1_2=c('520299'), deg_maj_2_2=c('NA'), deg_cip_2_2=c('NA'), deg_maj_3_2=c('NA'), deg_cip_3_2=c('NA'), deg_maj_4_2=c('NA'), deg_cip_4_2=c('NA'), inst_name_3=c('univ 2'), inst_state_3=c('CA'), level_3=c('Masters of Applied Sciences'), deg_maj_1_2=c('CISCO CCNA PREPARATION'), deg_cip_1_3=c('111003'), deg_maj_2_3=c('NA'), deg_cip_2_3=c('NA'), deg_maj_3_3=c('NA'), deg_cip_3_3=c('NA'), deg_maj_4_3=c('NA'), deg_cip_4_3=c('NA'))
If you don't rely on dcast(), base R's reshape() can get you there where you want.
reshape(df, idvar="id", timevar = "order", direction="wide")
Yielding
id grad_date.1 inst_name.1 inst_state.1 level.1
1 1 20160501 community college 1 CA Associate of Applied Sciences
deg_maj_1.1 deg_cip_1.1 deg_maj_2.1 deg_cip_2.1 deg_maj_3.1 deg_cip_3.1
1 NETWORK SECURITY 111003 NA NA NA NA
deg_maj_4.1 deg_cip_4.1 grad_date.2 inst_name.2 inst_state.2
1 NA NA 20170524 univ 1 CA
level.2 deg_maj_1.2 deg_cip_1.2 deg_maj_2.2
1 Bachelors of Applied Sciences INFO ASSUR CYBR-SECURITY 520299 NA
deg_cip_2.2 deg_maj_3.2 deg_cip_3.2 deg_maj_4.2 deg_cip_4.2 grad_date.3 inst_name.3
1 NA NA NA NA NA 20180524 univ 2
inst_state.3 level.3 deg_maj_1.3 deg_cip_1.3
1 CA Masters of Applied Sciences CISCO CCNA PREPARATION 111003
deg_maj_2.3 deg_cip_2.3 deg_maj_3.3 deg_cip_3.3 deg_maj_4.3 deg_cip_4.3
1 NA NA NA NA NA NA