R：一种有效的方式来对一列中的值进行排序/选择，这些值对应于同一数据帧中另一列中的特定值

Question

I am working with a dataframe called Student_Majr2 with about 60K rows and two relevant columns: one is for an anonymized student ID number, the other is for the date/term the student declared their major (the first two below). Problem is that a large number of the students change their major, so for each student ID there may be more than one associated date. There are about 30,000 unique student IDs. My goal is to create a new dataframe that only has the most recent major declaration date (ie their final choice of major) for each student ID. Here is the structure of the data frame:

'data.frame':   59749 obs. of  5 variables:
 $ studentID               : int  1 2 2 2 4 4 5 6 8 8 ...
 $ SGBSTDN_TERM_CODE_EFF   : int  199920 199920 200040 200320 200130 200220 200140 200020 200430 200540 ...
 $ SGBSTDN_MAJR_CODE_1     : chr  "720" "966" "996" "906" ...
 $ SGBSTDN_MAJR_CODE_CONC_1: chr  "" "" "" "" ...
 $ SGBSTDN_LEVL_CODE       : chr  "UG" "UG" "UG" "UG" ...

I have created the below script to accomplish this goal, and it is effective. However, it is also very inefficient and took several hours to run on a PC with corei5 processor running Windows 8.1, using R-Studio and R version 3.1.1. (I'm actually not sure how long it took, I went to bed after a couple hours and it was finished by morning seven hours later).

I am convinced there is a more efficient way to perform this operation so I don't have to keep running scripts like these while I sleep, but I can't figure out what it is. I would greatly appreciate any advice and assistance.

library(dplyr)
final_majr <- data.frame() # the final dataframe with final major per student ID
tbl_df(final_majr)
students <- unique(Student_Majr2$studentID) #students gets vector with all unique student ids
for (i in students) { #loop through all student id numbers
        temp_majr <- data.frame() #set up temporary dataframe for each unique student id and major
        tbl_df(temp_majr)

                for (q in 1:nrow(Student_Majr2)) { #loop through all row numbers from student_major df
                        if (Student_Majr2$studentID[q] == i){ #identify rows for each student ID from top loop 
                                temp_majr <- rbind(temp_majr, Student_Majr2[q, ]) #and add to temp_majr df
                        }
                }
        temp_majr <- arrange(temp_majr, SGBSTDN_TERM_CODE_EFF) #order the rows using dplyr package
        m <- nrow(temp_majr) # m gets the total number of rows in temp_majr
        final_majr <- rbind(final_majr, temp_majr[m, ]) #and here we add the bottom row to final_majr
}

Many thanks for any and all help with this script. I regularly consult stackoverflow for help with programming and this is my first question/post. Thanks for any feedback on how I can make my questions easier to understand and answer.

Answer 1

A base R solution. You can order the data and then use duplicated to select the rows that you want.

# some data
dat <- data.frame(studentID = c(1, 2, 2, 2, 4, 4, 5, 6, 8, 8),
                  SGBSTDN_TERM_CODE_EFF = c(199920, 199920, 200040, 200320, 200130, 200220, 200140, 200020, 200430, 200540),
                  SGBSTDN_MAJR_CODE_1 = letters[1:10])

# order data by id and latest date first
dat <- with(dat, dat[order(studentID, -SGBSTDN_TERM_CODE_EFF), ])

# select first observation
with(dat, dat[!duplicated(studentID), ])
# studentID SGBSTDN_TERM_CODE_EFF SGBSTDN_MAJR_CODE_1
# 1          1                199920                   a
# 4          2                200320                   d
# 6          4                200220                   f
# 7          5                200140                   g
# 8          6                200020                   h
# 10         8                200540                   j

Answer 2

If you want to select for each studentID , the row that has the highest SGBSTDN_TERM_CODE_EFF you could do, using dplyr :

library(dplyr)
df %>% group_by(studentID) %>%  arrange(SGBSTDN_TERM_CODE_EFF) %>%slice(n())