How to count the number of categories present in a column of a DataFrame

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1

Hello,

In a dataframe with columns :A, :B, :C where :B contains categorical data, I would like to count the number of categories present in the different subdataframes obtained through groupby(df,:A), and finally getting the list of codes in column :A where more than one category is present.

Thank you very much for any advice,
Philippe

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2

Welcome! Can you post a sample dataframe? It’ll be easier to help you then.

3

Here is an example:
Starting with the following data
df = DataFrame(A = [“a”,“a”,“a”,“b”,“b”,“b”,“c”,“c”],
B = [“X”,“Y”,“Z”,“Y”,“Y”,“Z”,“X”,“X”],
C = [2,3,5,2,10,7,5,1])
I would like to count for each value of the A column the number of different values in column B, the result would be something like:
a 3
b 2
c 1
could be tuples, arrays, a dictionary…

Hope this is clearer!
Thanks for your attention.

4

Try something like

julia> combine(groupby(df, :A), :B=>length∘unique)
3×2 DataFrame
│ Row │ A      │ B_function │
│     │ String │ Int64      │
├─────┼────────┼────────────┤
│ 1   │ a      │ 3          │
│ 2   │ b      │ 2          │
│ 3   │ c      │ 1          │
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5

edit - sorry was thinking of a different API

could also try a countmap(API · OnlineStats Docs), or if the data is small call “unique” on the requisite column and get the length

6

Thanks a lot, simple, elegant, efficient!

7

this is beautiful

8

Hi, what is the dot between length and unique? how to type it?
Thanks

9

Function composition, type it with \circ<tab>. You can always copy paste a unicode symbol into the REPL help mode to find out how to type it.

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