Select groups with more than one distinct value per group [duplicate]

Question

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Select groups with more than one distinct value (3 answers)

Closed 4 years ago.

I have data like below:

ID  category class
1   a        m  
1   a        s
1   b        s
2   a        m
3   b        s
4   c        s
5   d        s

I want to subset the data by only including those "ID" which have several (> 1) different categories.

My expected output:

ID  category class
1   a        m
1   a        s
1   b        s

Is there a way to doing so?

I tried

library(dplyr)
df %>% 
  group_by(ID) %>%
  filter(n_distinct(category, class) > 1)

But it gave me an error:

# Error: expecting a single value

Answer 1

Using data.table

library(data.table) #see: https://github.com/Rdatatable/data.table/wiki for more
setDT(data) #convert to native 'data.table' type by reference
data[ , if(uniqueN(category) > 1) .SD, by = ID]

uniqueN is data.table's (fast) native mask for length(unique()), and .SD is just the whole data.table (in more general cases, it can represent a subset of columns, e.g. when the .SDcols argument is activated). So basically the middle statement (j, the column selection argument) says to return all columns and rows associated with an ID for which there are at least two distinct values of category.

Use the by argument to extend to a case involving counts ok multiple columns.