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I have this:

df = DataFrame(dict(person= ['andy', 'rubin', 'ciara', 'jack'], 

     item = ['a', 'b', 'a', 'c'], 

     group= ['c1', 'c2', 'c3', 'c1'], 

     age= [23, 24, 19, 49]))


    age group item person

0   23  c1    a    andy

1   24  c2    b    rubin

2   19  c3    a    ciara

3   49  c1    c    jack

what I want to do, is to get the length of unique items in each column. Now I know I can do something like:


for every column.

Is there a way to do this in one go for all columns?

I tried to do:

for column in df.columns:


but I know this is not right.

How can I accomplish this?

1 Answer

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by (41.4k points)

To get the length of unique items in each column in one go for all columns, you can use pd.Series.nunique.


age       4

group     3

item      3

person    4

dtype: int64

If you wish to learn about Pandas visit this Pandas Tutorial.

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