DataFrame function[].unic () of pandas

You can use the function unique() For the Python Pandas data to determine the unique values ​​in a column. This effectively gets an overview of the different values ​​within a set of data.

The syntax of the function DataFrame[].unique() pandas

Basic syntax for the use of pandas unique() is simple, because the function takes no parameter:

DataFrame['nom_colonne'].unique()

Note that for the dataframes of pandas, unique() can only apply to A specific column. You must therefore specify it beforehand. The function unique() send you a numpy table with unique values ​​in the order of appearance; There is no sorting of values.

Function application unique() pandas

On pandas data, you can use unique() By first specifying the column in which you want to search for unique values.

In the following example, we consider a dataframe containing information on different people.

import pandas as pd
# Créer un exemple de DataFrame
data = {
    'Nom' : ['Alice', 'Bob', 'Charlie', 'David', 'Edward'],
    'Âge' : [24, 27, 22, 32, 29],
    'Ville' : ['New York', 'Los Angeles', 'New York', 'Chicago', 'Los Angeles']
}
df = pd.DataFrame(data)
print(df)

Dataframa then presents itself as follows:

Nom   Âge        Ville
0   Alice   24    New York
1     Bob   27 Los Angeles
2 Charlie   22    New York
3   David   32     Chicago
4  Edward   29 Los Angeles

It is now a question of determining the cities in which these people live. For that, Each city should only be listed once. The function unique() de Pandas is applied to the DataFrame column which contains the cities:

# Trouver les villes uniques dans la colonne « Ville »
unique_cities = df['Ville'].unique()
print(unique_cities)

The result is a NUMPY table which contains each city once. This shows that people come from three different cities: New York, Los Angeles and Chicago.

['New York' 'Los Angeles' 'Chicago']