Pandas Series - nunique() function
The Pandas Series nunique() function returns number of unique elements in the Series.
Syntax
Series.nunique(dropna=True)
Parameters
dropna |
Optional. Specify False to include NaN in the counts. Default is True. |
Return Value
Returns number of unique elements in the Series.
Example: using nunique() on a Series
In the example below, the nunique() function is used to get the count of distinct elements in the series.
import pandas as pd import numpy as np x = pd.Series([10, 5, 5, 10, 5]) print("The Series contains:") print(x) #getting the count of distinct #elements in the series print("\nx.nunique() returns:") print(x.nunique())
The output of the above code will be:
The Series contains: 0 10 1 5 2 5 3 10 4 5 dtype: int64 x.nunique() returns: 2
Example: using nunique() on selected series in a DataFrame
Similarly, the nunique() function can be applied on selected series/column of a given DataFrame. Consider the following example.
import pandas as pd import numpy as np df = pd.DataFrame({ "x": [5, 5, 2, 2, 7], "y": [10, 5, 5, 10, 5], "z": [1, 1, 1, 1, 1]}, index= ["a", "b", "c", "d", "e"] ) print("The DataFrame is:") print(df) #count of distinct elements in 'x' series print("\ndf['x'].nunique() returns:") print(df["x"].nunique())
The output of the above code will be:
The DataFrame is: x y z a 5 10 1 b 5 5 1 c 2 5 1 d 2 10 1 e 7 5 1 df['x'].nunique() returns: 3
❮ Pandas Series - Functions