从Pandas数据框架的某一列获取唯一值

让我们看看如何从pandas数据框架中检索出唯一的值。

让我们从CSV文件中创建一个数据框架。我们使用的是不同国家过去的GDP数据。你可以从这里获得数据集。

# import pandas as pd
import pandas as pd
  
gapminder_csv_url ='http://bit.ly/2cLzoxH'
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
  
record.head()

方法一：从记录中选择大陆列，并应用唯一函数来获得我们想要的值。

# import pandas as pd
import pandas as pd
  
gapminder_csv_url ='http://bit.ly/2cLzoxH'
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
  
print(record['continent'].unique())

输出:

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

方法二：从国家列中选择唯一的值。

# import pandas as pd
import pandas as pd
  
gapminder_csv_url ='http://bit.ly/2cLzoxH'
  
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
  
print(record.country.unique())

输出:

['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:

在这个方法中，你可以看到我们使用唯一函数中的数据框架作为参数，尽管我们选择了与上面相同的列，所以我们得到了相同的输出。

# Write Python3 code here
# import pandas as pd
import pandas as pd
  
gapminder_csv_url ='http://bit.ly/2cLzoxH'
  
# load the data with pd.read_csv
record = pd.read_csv(gapminder_csv_url)
  
print(pd.unique(record['continent']))

输出:

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