baizer provides data processing functions frequently
used by the author.You can install the development version of baizer like
so:
devtools::install_github("william-swl/baizer")And load the package:
library(baizer)%nin% to get ‘not in’ logical value1 %nin% c(1, 2, 3)
#> [1] FALSE
1 %nin% c(2, 3)
#> [1] TRUE%neq% to get NA supported ‘not equal’
logical valueNA != 0
#> [1] NA
NA != NA
#> [1] NA
NA %neq% 0
#> [1] TRUE
NA %neq% NA
#> [1] FALSEcollapse_vector(c("A" = 2, "B" = 3, "C" = 4), front_name = TRUE, collapse = ";")
#> [1] "A(2);B(3);C(4)"
collapse_vector(c("A" = 2, "B" = 3, "C" = 4), front_name = FALSE, collapse = ",")
#> [1] "2(A),3(B),4(C)"# return all the indices by default
diff_index("ATTG", "ATAC")
#> [1] 3 4
diff_index("ATTG", "ATAC", nth = 1)
#> [1] 3
diff_index("ATTG", "ATAC", nth = 2)
#> [1] 4fix_to_regex("ABC|?(*)")
#> [1] "ABC\\|\\?\\(\\*\\)"detect_dup(c("a", "C_", "c -", "#A"))
#> [1] "a" "#A" "C_" "c -"round(2.1951, 2)
#> [1] 2.2
round_string(2.1951, 2)
#> [1] "2.20"
signif(2.1951, 3)
#> [1] 2.2
signif_string(2.1951, 3)
#> [1] "2.20"signif_round_string(20.526, 2, "short")
#> [1] "21"
signif_round_string(20.526, 2, "long")
#> [1] "20.53"
# but will keep the raw value if necessary
signif_round_string(0.000002, 3)
#> [1] "0.00000200"is.zero("0.000")
#> [1] TRUE
is.zero("0.0001")
#> [1] FALSEfloat_to_percent(0.123, digits = 1)
#> [1] "12.3%"
percent_to_float("123%", digits = 3)
#> [1] "1.230"number_fun_wrapper(">=2.134%", function(x) round(x, 2))
#> [1] ">=2.13%"head(mini_diamond)
#> id carat cut clarity price x y
#> 1 id-1 1.02 Fair SI1 3027 6.25 6.18
#> 2 id-2 1.51 Good VS2 11746 7.27 7.18
#> 3 id-3 0.52 Ideal VVS1 2029 5.15 5.18
#> 4 id-4 1.54 Ideal SI2 9452 7.43 7.45
#> 5 id-5 0.72 Ideal VS1 2498 5.73 5.77
#> 6 id-6 2.02 Fair SI2 14080 8.33 8.37dplyr::column_to_rownames and
dplyr::rownames_to_column
head(mini_diamond) %>% c2r("id")
#> carat cut clarity price x y
#> id-1 1.02 Fair SI1 3027 6.25 6.18
#> id-2 1.51 Good VS2 11746 7.27 7.18
#> id-3 0.52 Ideal VVS1 2029 5.15 5.18
#> id-4 1.54 Ideal SI2 9452 7.43 7.45
#> id-5 0.72 Ideal VS1 2498 5.73 5.77
#> id-6 2.02 Fair SI2 14080 8.33 8.37
head(mini_diamond) %>%
c2r("id") %>%
r2c("id")
#> # A tibble: 6 × 7
#> id carat cut clarity price x y
#> <chr> <dbl> <chr> <chr> <int> <dbl> <dbl>
#> 1 id-1 1.02 Fair SI1 3027 6.25 6.18
#> 2 id-2 1.51 Good VS2 11746 7.27 7.18
#> 3 id-3 0.52 Ideal VVS1 2029 5.15 5.18
#> 4 id-4 1.54 Ideal SI2 9452 7.43 7.45
#> 5 id-5 0.72 Ideal VS1 2498 5.73 5.77
#> 6 id-6 2.02 Fair SI2 14080 8.33 8.37
# sort by n (default)
fancy_count(mini_diamond, "cut", "clarity")
#> # A tibble: 3 × 4
#> cut n r clarity
#> <chr> <int> <dbl> <chr>
#> 1 Fair 35 0.35 I1(5),SI1(5),VS2(5),VVS1(5),IF(4),SI2(4),VVS2(4),VS1(3)
#> 2 Ideal 34 0.34 SI1(5),VS1(5),VVS1(5),VVS2(5),I1(4),IF(4),SI2(4),VS2(2)
#> 3 Good 31 0.31 I1(5),IF(5),SI1(4),SI2(4),VS2(4),VVS1(4),VVS2(3),VS1(2)
# sort by character order
fancy_count(mini_diamond, "cut", "clarity", sort = FALSE)
#> # A tibble: 3 × 4
#> cut n r clarity
#> <chr> <int> <dbl> <chr>
#> 1 Fair 35 0.35 I1(5),IF(4),SI1(5),SI2(4),VS1(3),VS2(5),VVS1(5),VVS2(4)
#> 2 Good 31 0.31 I1(5),IF(5),SI1(4),SI2(4),VS1(2),VS2(4),VVS1(4),VVS2(3)
#> 3 Ideal 34 0.34 I1(4),IF(4),SI1(5),SI2(4),VS1(5),VS2(2),VVS1(5),VVS2(5)
fancy_count(mini_diamond, "cut", "clarity", fine_fmt = "ratio")
#> # A tibble: 3 × 4
#> cut n r clarity
#> <chr> <int> <dbl> <chr>
#> 1 Fair 35 0.35 I1(0.14),SI1(0.14),VS2(0.14),VVS1(0.14),IF(0.11),SI2(0.11),…
#> 2 Ideal 34 0.34 SI1(0.15),VS1(0.15),VVS1(0.15),VVS2(0.15),I1(0.12),IF(0.12)…
#> 3 Good 31 0.31 I1(0.16),IF(0.16),SI1(0.13),SI2(0.13),VS2(0.13),VVS1(0.13),…
fancy_count(mini_diamond, "cut", "clarity", fine_fmt = "clean")
#> # A tibble: 3 × 4
#> cut n r clarity
#> <chr> <int> <dbl> <chr>
#> 1 Fair 35 0.35 I1,SI1,VS2,VVS1,IF,SI2,VVS2,VS1
#> 2 Ideal 34 0.34 SI1,VS1,VVS1,VVS2,I1,IF,SI2,VS2
#> 3 Good 31 0.31 I1,IF,SI1,SI2,VS2,VVS1,VVS2,VS1ordered_slice(mini_diamond, "id", c("id-3", "id-2"))
#> # A tibble: 2 × 7
#> id carat cut clarity price x y
#> <chr> <dbl> <chr> <chr> <int> <dbl> <dbl>
#> 1 id-3 0.52 Ideal VVS1 2029 5.15 5.18
#> 2 id-2 1.51 Good VS2 11746 7.27 7.18
# support NA and known values in ordered vector
ordered_slice(mini_diamond, "id", c("id-3", "id-2", "unknown_id", "id-3", NA))
#> Warning in ordered_slice(mini_diamond, "id", c("id-3", "id-2", "unknown_id", : 2
#> NA values!
#> Warning in ordered_slice(mini_diamond, "id", c("id-3", "id-2", "unknown_id", : 2
#> duplicated values!
#> # A tibble: 5 × 7
#> id carat cut clarity price x y
#> <chr> <dbl> <chr> <chr> <int> <dbl> <dbl>
#> 1 id-3 0.52 Ideal VVS1 2029 5.15 5.18
#> 2 id-2 1.51 Good VS2 11746 7.27 7.18
#> 3 <NA> NA <NA> <NA> NA NA NA
#> 4 id-3 0.52 Ideal VVS1 2029 5.15 5.18
#> 5 <NA> NA <NA> <NA> NA NA NA
# remove NA
ordered_slice(mini_diamond, "id", c("id-3", "id-2", "unknown_id", "id-3", NA),
na.rm = TRUE
)
#> Warning in ordered_slice(mini_diamond, "id", c("id-3", "id-2", "unknown_id", : 2
#> NA values!
#> Warning in ordered_slice(mini_diamond, "id", c("id-3", "id-2", "unknown_id", : 2
#> duplicated values!
#> # A tibble: 3 × 7
#> id carat cut clarity price x y
#> <chr> <dbl> <chr> <chr> <int> <dbl> <dbl>
#> 1 id-3 0.52 Ideal VVS1 2029 5.15 5.18
#> 2 id-2 1.51 Good VS2 11746 7.27 7.18
#> 3 id-3 0.52 Ideal VVS1 2029 5.15 5.18
# remove duplication
ordered_slice(mini_diamond, "id", c("id-3", "id-2", "unknown_id", "id-3", NA),
dup.rm = TRUE
)
#> Warning in ordered_slice(mini_diamond, "id", c("id-3", "id-2", "unknown_id", : 2
#> NA values!
#> Warning in ordered_slice(mini_diamond, "id", c("id-3", "id-2", "unknown_id", : 2
#> duplicated values!
#> # A tibble: 3 × 7
#> id carat cut clarity price x y
#> <chr> <dbl> <chr> <chr> <int> <dbl> <dbl>
#> 1 id-3 0.52 Ideal VVS1 2029 5.15 5.18
#> 2 id-2 1.51 Good VS2 11746 7.27 7.18
#> 3 <NA> NA <NA> <NA> NA NA NAPlease note that the baizer project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.