CODEWITHSUNDEEP
rdplyrdata-manipulationtidyr
HNSKD
HNSKD

Reputation: 1644

Manipulate Values of a Column Based on Another Column

I have a dataframe that looks as follows:

df <- read.table(header = TRUE, text = 
          "STUD_ID       MEAS  VALUE
                 1  LVEF(M-M)    69
                 1   LVEF(2D)    66
                 2   LVEF(2D)    36
                 2   LVEF(2D)    72
                 2       IVSD    63
                 3  LVEF(M-M)    50
                 4   LVEF(2D)    71
                 4       PASP    55", stringsAsFactors = FALSE)

I want to focus on MEAS that are either LVEF(M-M) or LVEF(2D).

  1. If a STUD_ID has VALUEs that correspond to both LVEF(M-M) and LVEF(2D), then we only filter for the latter i.e. LVEF(2D).
  2. If a STUD_ID has 2 VALUEs that correspond to LVEF(2D), then we take the mean.

My desired output is:

# STUD_ID       MEAS  VALUE
#       1   LVEF(2D)    66
#       2   LVEF(2D)    54
#       2       IVSD    63
#       3  LVEF(M-M)    50
#       4   LVEF(2D)    71
#       4       PASP    55

I tried the following but it gave me an error:

df %>% 
  filter(MEAS == "LVEF(M-M)" | MEAS == "LVEF(2D)") %>%
  arrange(STUD_ID, MEAS) %>%
  group_by(STUD_ID, MEAS) %>%
  mutate(n = n()) %>%
  group_by(STUD_ID) %>% 
  mutate(nd = n_distinct(MEAS)) %>%
  mutate(VALUE = 
           case_when(nd == 2 ~ VALUE[which(MEAS == "LVEF(2D)")],
                     nd == 1 & n > 1 ~ mean(VALUE),
                     TRUE ~ VALUE)) %>%
  bind_rows(
    df %>% filter(MEAS != "LVEF(M-M)" & MEAS != "LVEF(2D)")
  )

My dataframe contains other variables apart from this 3 variables and I wish to retain them.

Upvotes: 0

Views: 80

Answers (1)

Andrew Gustar
Andrew Gustar

Reputation: 18425

This does what you are looking for...

df2 <- df %>% group_by(STUD_ID,MEAS) %>% 
  summarise(VALUE=mean(VALUE)) %>% 
  group_by(STUD_ID) %>% mutate(TEMP2D=("LVEF(2D)" %in% MEAS)) %>% 
  filter(!(MEAS=="LVEF(M-M)" & TEMP2D)) %>% 
  select(-TEMP2D)

df2
# A tibble: 6 x 3
# Groups:   STUD_ID [4]
  STUD_ID      MEAS VALUE
    <int>     <chr> <dbl>
1       1  LVEF(2D)    66
2       2      IVSD    63
3       2  LVEF(2D)    54
4       3 LVEF(M-M)    50
5       4  LVEF(2D)    71
6       4      PASP    55

Upvotes: 1

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