CODEWITHSUNDEEP
r
Joe Crozier
Joe Crozier

Reputation: 1036

Filter data frame based off two columns in other data frame

I'm sure the answer to this will be VERY similar to this question but I just can't quite put it together.

I have two data frames. One is the data frame I'm working on:

df <- structure(list(Username = c("hmaens", "pgcmann",
                                  "gsamse", "gsamse", 
                                  "gsamse", "gamse"),
                     Title = c("Pharmacy Resident PGY2",
                               "Associate Professor of Pediatrics", 
                               "Regulatory Coordinator",
                               "Regulatory Coordinator",
                               "Regulatory Coordinator", 
                               "Regulatory Coordinator"),
                     `User Role` = c("Investigational Pharmacist", 
                                     "Principal Investigator",
                                     "Calendar Build",
                                     "Protocol Management", 
                                     "Subject Management",
                                     "Regulatory")),
                row.names = c(NA, -6L), class = c("tbl_df", 
                                                  "tbl", "data.frame"))

and one is they key:

key <- structure(list(username = c("hmaens", "pgcmann",
                                   "gsamse", "gsamse", 
                                   "gsamse", "gsamse"),
                      training = c(0, 0, 1, 
                                   1, 1, 1)),
                 row.names = c(NA, -6L), 
                 class = c("tbl_df", "tbl", "data.frame"))

I want to split my "df" data frame based on the "training" column in key. I.e. my results would be a data frame called dfZero with the exact same columns from df that had everyone from key with a "0" in training. And a separate data frame called dfOne with the 1's from key$training.

Upvotes: 4

Views: 1242

Answers (2)

nogbad
nogbad

Reputation: 445

Using dplyr:

library(dplyr)

dflist <- merge(df, key, by.x = "Username", by.y = "username") %>%
  unique() %>%
  group_by(training) %>%
  group_split()

edit: You can extract the individual list elements like so:

dfzero <- dflist[[1]]
dfone <- dflist[[2]]

Upvotes: 0

Skaqqs
Skaqqs

Reputation: 4140

Using %in%

dfZero <- df[df$Username %in% key[key$training == 0, "username"],]
dfOne <- df[df$Username %in% key[key$training == 1, "username"],]

Using merge()

dfZero <- merge(df, key[key$training == 0,], by.x = "Username", by.y = "username")
dfOne <- merge(df, key[key$training == 1,], by.x = "Username", by.y = "username")

Upvotes: 3

Related Questions