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## Ordered Factor

# Note the names of the wind direction variables.

ds %>%
select(contains("_dir")) %>%
names() %T>%
print() ->
vnames
 ```## [1] "wind_gust_dir" "wind_dir_9am" "wind_dir_3pm" ```

# Convert these variables from character to factor.

ds[vnames] %<>%
lapply(factor, levels=compass, ordered=TRUE) %>%
data.frame() %>%
as_tibble()
# Confirm they are now factors.

ds[vnames] %>% sapply(class)
 ```## wind_gust_dir wind_dir_9am wind_dir_3pm ## [1,] "ordered" "ordered" "ordered" ## [2,] "factor" "factor" "factor" ```

We can again obtain a distribution of the variables to confirm that all we have changed is the data type.

# Verify the distribution has not changed.

ds %>%
select(contains("_dir")) %>%
sapply(table)
 ```## wind_gust_dir wind_dir_9am wind_dir_3pm ## N 10989 13978 10475 ## NNE 7937 9782 8002 ## NE 8715 9335 10092 ## ENE 9965 9592 9605 ## E 11071 11237 10123 ## ESE 9055 9536 10290 ## SE 11331 11398 12919 ## SSE 10946 10954 11089 ## S 11043 10519 11788 ## SSW 10809 9272 9902 ## SW 10793 10135 11166 .... ```