pandas unique – Get Unique Values in Column of DataFrame

To get the unique values of a column in pandas, the simplest way is to use the pandas unique() function.

df["variable"].unique()

You can also use the pandas unique() function in the following way:

pd.unique(series)

When working with data as a data science or data analyst, it’s sometimes important to be able to easily find the unique values of your dataset.

To get the unique values in a DataFrame, we can use the pandas unique() function.

The following code will get you the unique values of a series in Python:

df["variable"].unique()

If you want to get the number of unique values of an entire DataFrame in pandas, you can call pandas nunique() function.

Getting the Unique Values in a Column Using Pandas

Let’s say I have the following pandas DataFrame:

     Name  Weight_Change Month
0     Jim         -16.20     1
1   Sally          12.81     1
2     Bob         -20.45     1
3     Sue          15.35     1
4    Jill         -12.43     1
5   Larry         -18.52     1
6     Jim          -6.10     2   
7   Sally          -2.81     2  
8     Bob          12.45     2
9     Sue          -0.32     2
10   Jill          -1.23     2
11  Larry          -8.52     2
12    Jim           5.20     3 
13  Sally          12.81     3  
14    Bob          -2.45     3
15    Sue           5.35     3
16   Jill          -2.43     3
17  Larry          -1.85     3

We can call the unique() function on “Name” column to find the unique values for that column.

print(df["Name"].unique())

array(['Jim', 'Sally', 'Bob', 'Sue', 'Jill', 'Larry'], dtype=object)

We can also find the unique values in the “Name” column in the following way:

print(pd.unique(df["Name"]))

array(['Jim', 'Sally', 'Bob', 'Sue', 'Jill', 'Larry'], dtype=object)

You can see that this returns the same array as above.

Hopefully this article has been useful for you to find the number of unique values in a pandas DataFrame using Python.