Check for value(s) in the dataset
check_value.RdCheck for value(s) in the dataset
Usage
check_value(
dataset,
uuid_column = "uuid",
element_name = "checked_dataset",
values_to_look = c(99, 999, 999, 88, 888, 888)
)Examples
df <- data.frame(
X_uuid = paste0("uuid_", 1:100),
age = c(sample(18:80, replace = TRUE, size = 96), 99, 99, 98, 88),
gender = c("99", sample(c("male", "female"),
replace = TRUE, size = 95
), "98", "98", "88", "888")
)
check_value(
dataset = df, uuid_column = "X_uuid",
element_name = "checked_dataset",
values_to_look = c(99, 98, 88, 888)
)
#> $checked_dataset
#> X_uuid age gender
#> 1 uuid_1 80 99
#> 2 uuid_2 24 female
#> 3 uuid_3 24 female
#> 4 uuid_4 75 male
#> 5 uuid_5 23 female
#> 6 uuid_6 22 female
#> 7 uuid_7 29 male
#> 8 uuid_8 25 male
#> 9 uuid_9 28 male
#> 10 uuid_10 49 female
#> 11 uuid_11 33 female
#> 12 uuid_12 28 male
#> 13 uuid_13 51 female
#> 14 uuid_14 27 male
#> 15 uuid_15 28 female
#> 16 uuid_16 25 female
#> 17 uuid_17 35 female
#> 18 uuid_18 39 male
#> 19 uuid_19 71 female
#> 20 uuid_20 34 male
#> 21 uuid_21 22 female
#> 22 uuid_22 32 male
#> 23 uuid_23 22 female
#> 24 uuid_24 45 male
#> 25 uuid_25 29 male
#> 26 uuid_26 55 female
#> 27 uuid_27 42 male
#> 28 uuid_28 46 female
#> 29 uuid_29 64 male
#> 30 uuid_30 45 female
#> 31 uuid_31 34 female
#> 32 uuid_32 50 female
#> 33 uuid_33 58 female
#> 34 uuid_34 69 male
#> 35 uuid_35 35 male
#> 36 uuid_36 73 female
#> 37 uuid_37 65 male
#> 38 uuid_38 40 male
#> 39 uuid_39 79 male
#> 40 uuid_40 49 male
#> 41 uuid_41 40 male
#> 42 uuid_42 28 female
#> 43 uuid_43 43 female
#> 44 uuid_44 24 female
#> 45 uuid_45 23 male
#> 46 uuid_46 38 female
#> 47 uuid_47 59 male
#> 48 uuid_48 58 male
#> 49 uuid_49 71 male
#> 50 uuid_50 63 female
#> 51 uuid_51 78 male
#> 52 uuid_52 41 male
#> 53 uuid_53 79 female
#> 54 uuid_54 80 male
#> 55 uuid_55 52 female
#> 56 uuid_56 29 male
#> 57 uuid_57 27 male
#> 58 uuid_58 27 female
#> 59 uuid_59 77 male
#> 60 uuid_60 44 male
#> 61 uuid_61 51 female
#> 62 uuid_62 59 female
#> 63 uuid_63 24 male
#> 64 uuid_64 72 male
#> 65 uuid_65 69 female
#> 66 uuid_66 61 female
#> 67 uuid_67 30 female
#> 68 uuid_68 45 female
#> 69 uuid_69 65 male
#> 70 uuid_70 72 female
#> 71 uuid_71 43 male
#> 72 uuid_72 19 male
#> 73 uuid_73 26 male
#> 74 uuid_74 59 male
#> 75 uuid_75 29 male
#> 76 uuid_76 23 female
#> 77 uuid_77 62 male
#> 78 uuid_78 75 female
#> 79 uuid_79 51 female
#> 80 uuid_80 19 male
#> 81 uuid_81 58 female
#> 82 uuid_82 50 female
#> 83 uuid_83 34 female
#> 84 uuid_84 18 female
#> 85 uuid_85 45 male
#> 86 uuid_86 50 male
#> 87 uuid_87 74 female
#> 88 uuid_88 67 male
#> 89 uuid_89 52 male
#> 90 uuid_90 33 female
#> 91 uuid_91 48 female
#> 92 uuid_92 58 male
#> 93 uuid_93 29 male
#> 94 uuid_94 78 female
#> 95 uuid_95 30 male
#> 96 uuid_96 63 male
#> 97 uuid_97 99 98
#> 98 uuid_98 99 98
#> 99 uuid_99 98 88
#> 100 uuid_100 88 888
#>
#> $flaged_value
#> # A tibble: 9 × 4
#> uuid question old_value issue
#> <chr> <chr> <chr> <chr>
#> 1 uuid_1 gender 99 Possible value to be changed to NA
#> 2 uuid_97 age 99 Possible value to be changed to NA
#> 3 uuid_97 gender 98 Possible value to be changed to NA
#> 4 uuid_98 age 99 Possible value to be changed to NA
#> 5 uuid_98 gender 98 Possible value to be changed to NA
#> 6 uuid_99 age 98 Possible value to be changed to NA
#> 7 uuid_99 gender 88 Possible value to be changed to NA
#> 8 uuid_100 age 88 Possible value to be changed to NA
#> 9 uuid_100 gender 888 Possible value to be changed to NA
#>