setdiff_col_match: Set Difference between Overlapping Columns
In meerapatelmd/rubix: rubix Package
Description
Usage
Arguments
See Also
Examples
Description
Preemptively select for columns that overlap between 2 dataframes before calling the 'setdiff()' function.
Compare column names and positions for 2 dataframes.
Usage
1
2
3
setdiff_col_match(x, y)
compare_cols(x, y)
Arguments
x
A dataframe or tibble.
y
A dataframe or tibble.
See Also
Other diff functions:
setdiff_nrow()
Other diff functions:
setdiff_nrow()
Examples
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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))
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))
meerapatelmd/rubix documentation built on Sept. 5, 2021, 8:30 p.m.
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Description Usage Arguments See Also Examples
Description
Preemptively select for columns that overlap between 2 dataframes before calling the 'setdiff()' function.
Compare column names and positions for 2 dataframes.
Usage
1 2 3 | setdiff_col_match(x, y)
compare_cols(x, y)
|
Arguments
x |
A dataframe or tibble. |
y |
A dataframe or tibble. |
See Also
Other diff functions:
setdiff_nrow()
Other diff functions:
setdiff_nrow()
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 | 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))
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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