Getting Unique values from a column in Pandas dataframe (original) (raw)

Last Updated : 15 Jan, 2019

Let’s see how can we retrieve the unique values from pandas dataframe.

Let’s create a dataframe from CSV file. We are using the past data of GDP from different countries. You can get the dataset from here.

import pandas as pd

record = pd.read_csv(gapminder_csv_url)

record.head()

Method #1: Select the continent column from the record and apply the unique function to get the values as we want.

import pandas as pd

record = pd.read_csv(gapminder_csv_url)

print (record[ 'continent' ].unique())

Output:

['Asia' 'Europe' 'Africa' 'Americas' 'Oceania']

Method #2: Select unique values from the _country_column.

import pandas as pd

record = pd.read_csv(gapminder_csv_url)

print (record.country.unique())

Output:

['Afghanistan' 'Albania' 'Algeria' 'Angola' 'Argentina' 'Australia' 'Austria' 'Bahrain' 'Bangladesh' 'Belgium' 'Benin' 'Bolivia' 'Bosnia and Herzegovina' 'Botswana' 'Brazil' 'Bulgaria' 'Burkina Faso' 'Burundi' 'Cambodia' 'Cameroon' 'Canada' 'Central African Republic' 'Chad' 'Chile' 'China' 'Colombia' 'Comoros' 'Congo Dem. Rep.' 'Congo Rep.' 'Costa Rica' "Cote d'Ivoire" 'Croatia' 'Cuba' 'Czech Republic' 'Denmark' 'Djibouti' 'Dominican Republic' 'Ecuador' 'Egypt' 'El Salvador' 'Equatorial Guinea' 'Eritrea' 'Ethiopia' 'Finland' 'France' 'Gabon' 'Gambia' 'Germany' 'Ghana' 'Greece' 'Guatemala' 'Guinea' 'Guinea-Bissau' 'Haiti' 'Honduras' 'Hong Kong China' 'Hungary' 'Iceland' 'India' 'Indonesia' 'Iran' 'Iraq' 'Ireland' 'Israel' 'Italy' 'Jamaica' 'Japan' 'Jordan' 'Kenya' 'Korea Dem. Rep.' 'Korea Rep.' 'Kuwait' 'Lebanon' 'Lesotho' 'Liberia' 'Libya' 'Madagascar' 'Malawi' 'Malaysia' 'Mali' 'Mauritania' 'Mauritius' 'Mexico' 'Mongolia' 'Montenegro' 'Morocco' 'Mozambique' 'Myanmar' 'Namibia' 'Nepal' 'Netherlands' 'New Zealand' 'Nicaragua' 'Niger' 'Nigeria' 'Norway' 'Oman' 'Pakistan' 'Panama' 'Paraguay' 'Peru' 'Philippines' 'Poland' 'Portugal' 'Puerto Rico' 'Reunion' 'Romania' 'Rwanda' 'Sao Tome and Principe' 'Saudi Arabia' 'Senegal' 'Serbia' 'Sierra Leone' 'Singapore' 'Slovak Republic' 'Slovenia' 'Somalia' 'South Africa' 'Spain' 'Sri Lanka' 'Sudan' 'Swaziland' 'Sweden' 'Switzerland' 'Syria' 'Taiwan' 'Tanzania' 'Thailand' 'Togo' 'Trinidad and Tobago' 'Tunisia' 'Turkey' 'Uganda' 'United Kingdom' 'United States' 'Uruguay' 'Venezuela' 'Vietnam' 'West Bank and Gaza' 'Yemen Rep.' 'Zambia' 'Zimbabwe']

Method #3:

In this method you can see that we use the dataframe inside the unique function as parameter although we select the same column as above so we get the same output.

import pandas as pd

record = pd.read_csv(gapminder_csv_url)

print (pd.unique(record[ 'continent' ]))

Output:

['Asia' 'Europe' 'Africa' 'Americas' 'Oceania']

Similar Reads

Pandas DataFrame Practice Exercises



















Pandas Dataframe Rows Practice Exercise

















Pandas Dataframe Columns Practice Exercise



























Pandas Series Practice Exercise






Pandas Date and Time Practice Exercise




DataFrame String Manipulation




Accessing and Manipulating Data in DataFrame






DataFrame Visualization and Exporting