Description Usage Arguments Details See Also Examples
find all unique non-numeric values
1 | unique_non_numerics(x, na.rm = TRUE)
|
x |
vector to check on |
na.rm |
remove existing na values before checking |
This function is especially useful for figuring out what
non-numeric unique values are in in a column that should be numeric
so one can easily replace them with another flag. This function can work well
with replace_char_flags
instead of using nested ifelse statements
replace_values
: to use to replace non-numeric values
in a dataframe.
1 2 3 4 5 6 7 8 | dv <- c(1, 2, 4, "88 (excluded)", "bql", "*")
unique_non_numerics(dv)
df <- tibble::data_frame(ID = 1:3, DV = c("BQL", 0.5, 9))
unique_non_numerics(df$DV)
#using dplyr
library(dplyr)
df %>% filter(!(DV %in% unique_non_numerics(DV)))
|
[1] "88 (excluded)" "bql" "*"
Warning message:
`data_frame()` is deprecated, use `tibble()`.
This warning is displayed once per session.
[1] "BQL"
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
# A tibble: 2 x 2
ID DV
<int> <chr>
1 2 0.5
2 3 9
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