Consider the following example
> library(forcats)
> library(dplyr)
>
>
> dataframe <- data_frame(var = c(1,1,1,2,3,4),
+
To understand fct_reoder, I created a similar but modified data frame.
> dataframe <- data_frame(var = as.factor(c(1,2,3,2,3,1,4,1,2,3,4)),var2 = c(1,5,4,2,6,2,9,8,7,6,3))
> str(dataframe)
Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 11 obs. of 2 variables:
$ var : Factor w/ 4 levels "1","2","3","4": 1 2 3 2 3 1 4 1 2 3 ...
$ var2: num 1 5 4 2 6 2 9 8 7 6 ...
here we could see that there are 2 columns, having column 1(var) as a factor variable with levels c(1,2,3,4).
Now, if one wants to reorder the factors on the basis of the sum of their respective values(var2), one can use the fct_reorder function as below.
In order to get the difference b/w with and without fct_reorder.
At first, we would sum up the var2 on the basis of their factors(var) without using fct_reorder:
> dataframe %>% group_by(var) %>% summarise(var2=sum(var2))
# A tibble: 4 x 2
var var2
1 1 11
2 2 14
3 3 16
4 4 12
Here we could see that the result is not ordered on the basis of the sum of var2.
Now, we would use fct_order to show the difference.
> dataframe %>% mutate(var=fct_reorder(var,var2,sum)) %>%
+ group_by(var) %>% summarise(var2=sum(var2))
# A tibble: 4 x 2
var var2
1 1 11
2 4 12
3 2 14
4 3 16
This shows that summation is now ordered.
Likewise, fct_reorder can be used to plot the graphs(boxplot or histogram etc.) in an ordered way