library(tidyverse)
test_data <-
tibble(
Group = sample(c("Apple", "Pear"), size = 10, replace = TRUE),
A = sample(c(NA_integer_, 1:3), size = 10, replace = TRUE),
B = sample(c(NA_integer_, 4:6), size = 10, replace = TRUE),
C = sample(c(NA_real_, seq(from = 6.01, to = 6.09, by = 0.01)), size = 10, replace = TRUE),
D = sample(c(NA, TRUE, FALSE), size = 10, replace = TRUE)
) %>%
dplyr::mutate(E = B)
test_data2 <- dplyr::bind_rows(test_data[1:5,],
tibble(
Group = sample(c("Apple", "Pear"), size = 5, replace = TRUE),
A = sample(c(NA_integer_, 1:3), size = 5, replace = TRUE),
B = sample(c(NA_integer_, 4:6), size = 5, replace = TRUE),
C = sample(c(NA_real_, seq(from = 6.01, to = 6.09, by = 0.01)), size = 5, replace = TRUE),
D = sample(c(NA, TRUE, FALSE), size = 5, replace = TRUE)
) %>%
dplyr::mutate(E = B))
# Rows difference
setdiff_nrow(x = test_data,
y = test_data2)
setdiff_nrow(x = test_data2,
y = test_data)
# Setdiff with a Column Match
setdiff_col_match(x = test_data,
y = test_data2 %>%
dplyr::mutate(F = 1:10) %>%
dplyr::mutate(G = 11:20))
setdiff_col_match(x = test_data2 %>%
dplyr::mutate(F = 1:10) %>%
dplyr::mutate(G = 11:20),
y = test_data)
setdiff_col_match(x = test_data,
y = test_data2 %>%
rename(F = E))
setdiff_col_match(y = test_data,
x = test_data2 %>%
rename(F = E))
# Compare Columns
compare_cols(x = test_data,
y = test_data2)
compare_cols(x = test_data,
y = test_data2 %>%
dplyr::mutate(F = 1:10) %>%
dplyr::mutate(G = 11:20))
compare_cols(x = test_data2 %>%
dplyr::mutate(F = 1:10) %>%
dplyr::mutate(G = 11:20),
y = test_data)
compare_cols(x = test_data,
y = test_data2 %>%
rename(F = E))
compare_cols(y = test_data,
x = test_data2 %>%
rename(F = E))
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