Created
October 22, 2019 12:38
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Different types of dplyr joins
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library(dplyr) | |
# Create two example data frames: | |
dfA <- tibble( | |
ID = c(76, 79, 9), | |
age = c(21, 23, 24) | |
) | |
dfB <- tibble( | |
ID = c(79, 76, 11), | |
state = c("MA", "OR", "DE") | |
) | |
# 1. This matches to ID's in "left" data frame i.e. dfA: | |
dfA %>% | |
left_join(dfB, by = "ID") | |
# 2. This matches to ID's in "right" data frame i.e. dfB: | |
dfA %>% | |
right_join(dfB, by = "ID") | |
# 3. This matches to ID's that exist in both data frames: | |
dfA %>% | |
inner_join(dfB, by = "ID") | |
# 4. This matches to ID's that exist either data frame: | |
dfA %>% | |
full_join(dfB, by = "ID") | |
# 5. This matches to ID's that exist in "left" data frame, but not "right" data frame: | |
dfA %>% | |
anti_join(dfB, by = "ID") |
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