Determine number of unique values of one column for each value of another column

user_4976352 0
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I have:

df = pd.DataFrame({"A": [1,2,3,4,5,6,7,8], "B": [1,1,2,2,3,3,4,4], "C": [1,1,1,1,2,3,2,2] })

    A   B   C
0   1   1   1
1   2   1   1
2   3   2   1
3   4   2   1
4   5   3   2
5   6   3   3
6   7   4   2
7   8   4   2

I would like to know, for each value b of column B, how many unique values c of column C there that are in rows where B=b.

So I'd like a series that tells me something like {1:1, 2:2, 3:2, 4:1} meaning that, for example, when B=3, there are two unique values of C (namely 2 and 3).

How do I do this?

pandas dataframe python
2 Answers

Try this:

df.groupby("B")["C"].nunique()

> B
  1    1
  2    1
  3    2
  4    1
  Name: C, dtype: int64
user_181896220 
df.groupby("B")["C"].nunique().to_dict()

output:

{1: 1, 2: 1, 3: 2, 4: 1}

how does it work?

  1. every time you want to calculate something in one column based on values in another, groupby is coming... so use it and pass all values grouped.
  2. what do you want? number of unique values in C... so use ["C"].nunique() that return number of unique values.
  3. and at last, you want dict, so convert your result to_dict()
user_186944000
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