Создайте новый столбец на основе значения другого столбца в pandas

Question

В кадре данных у меня есть столбец для названия разных стран, и я хочу создать новый столбец с их регионами, например, если страна - Индия, регион должен быть Азия и т. Д. c. Я уже пробовал использовать np.where, но кажется, что я делаю что-то не так. Ниже приведен код, который я пробовал:

Region = np.where(country_name == 'US' , "US", 
                 np.where(country_name == ('Brazil' or 'Canada' or 'Peru' or 'Chile') , "Rest of America", 
                 np.where(country_name == ('South Africa 'or 'Egypt' or 'Morocco' or 'Algeria' or 'Ghana'), "Africa", 
                 np.where(country_name == ('Afghanistan'or 'Armenia'or 'Azerbaijan' or 'Bahrain'or'Bangladesh'or 'Bhutan'or 
                                           'Brunei'or 'Burma'or 'Cambodia'or 'China'or 'East Timor' or
                                           'Georgia'or 'Hong Kong'or 'India' or 'Indonesia'or 'Iran' or 'Iraq'or 'Israel'or 'Japan'or
                                           'Jordan'or 'Kazakhstan'or 'Kuwait'or 'Kyrgyzstan'or 'Laos'or 
                                           'Lebanon'or 'Malaysia' or 'Mongolia'or 'Nepal'or 'North Korea'or 'Oman'or 'Pakistan'|
                                           'Papua New Guinea'or 'Philippines'or 'Qatar'or 'Russia'or 'Saudi Arabia'or 'Singapore'| 
                                           'South Korea'or 'Sri Lanka'or 'Syria'or 'Taiwan'or 'Tajikistan'or 'Thailand'or 'Turkey'or 'Turkmenistan'or
                                           'United Arab Emirates'or 'Uzbekistan'or 'Vietnam'or 'Yemen'), "Asia", 
                 np.where(country_name == ('Spain'or 'Italy' or 'Germany'or 'United Kingdom' or'France'), "Europe", "Unchange")))))

Below is the data:

     Entity        Region   Code       Date   Total confirmed deaths (deaths)   Total confirmed cases (cases)
0   Afghanistan     Asia    AFG     2019-12-31  0   0
1   Afghanistan     Asia    AFG     2020-01-01  0   0
2   Afghanistan     Asia    AFG     2020-01-02  0   0
3   Afghanistan     Asia    AFG     2020-01-03  0   0
4   Afghanistan     Asia    AFG     2020-01-04  0   0
5   Afghanistan     Asia    AFG     2020-01-05  0   0
6   Afghanistan     Asia    AFG     2020-01-06  0   0
7   Afghanistan     Asia    AFG     2020-01-07  0   0
8   Afghanistan     Asia    AFG     2020-01-08  0   0
9   Afghanistan     Asia    AFG     2020-01-09  0   0
10  Afghanistan     Asia    AFG     2020-01-10  0   0
11  Afghanistan     Asia    AFG     2020-01-11  0   0

Но этот код работает только для первой страны, например, для Бразилии, Южной Африки, Афганистана и Испании.

Answer 1

list_1 = ["Iceland", "Norway", "Sweden", "Finland","Denmark","United Kingdom", "Ireland",
              "France", "Belgium","Netherlands", "Luxembourg","Monaco", "Portugal", "Spain",
              "Andorra", "Italy","Malta","San Marino", "Vatican City", "Germany", 
              "Switzerland", "Liechtenstein"," Austria", "Poland", "Czech Republic", "Slovakia",
              "Hungary","Slovenia","Croatia", "Bosnia" ,"Herzegovina", "Serbia", "Montenegro", 
              "Albania", "Macedonia", "Romania", "Bulgaria","Greece", "Estonia", "Latvia", 
              "Lithuania", "Belarus", "Ukraine", "Moldova"]
    list_2 = ['Brazil' , 'Canada' , 'Peru' , 'Chile', 'South America']
    list_3 = ['Afghanistan', 'Armenia', 'Azerbaijan', 'Bahrain' ,'Bangladesh',  'Bhutan', 
              'Brunei', 'Burma', 'Cambodia', 'China', 'East Timor','Georgia',  'Hong Kong', 
              'India' , 'Indonesia', 'Iran' , 'Iraq' ,'Israel' , 'Japan','Jordan', 'Kazakhstan',
              'Kuwait' , 'Kyrgyzstan' , 'Laos', 'Lebanon', 'Malaysia' , 'Mongolia', 'Nepal', 
              'North Korea', 'Oman', 'Pakistan','Papua New Guinea', 'Philippines', 'Qatar', 
               'Saudi Arabia','Singapore', 'South Korea', 'Sri Lanka', 'Syria', 'Taiwan'
               'Tajikistan', 'Thailand', 'Turkey', 'Turkmenistan','United Arab Emirates', 
              'Uzbekistan', 'Vietnam', 'Yemen']
    list_4 = ['United States']
    list_5 = ['South Africa','Egypt' , 'Morocco' , 'Algeria' , 'Ghana', 'Africa', "Egypt"]



     conditions = [
            (df['Entity'].isin(list_4)),
            (df['Entity'].isin(list_2)),
            (df['Entity'].isin(list_5)),
            (df['Entity'].isin(list_3)),
            (df['Entity'].isin(list_1))
                     ]
        choices = ['US',"Rest of America","Africa","Asia","Europe"]
        Region = np.select(conditions, choices, default='Rest of the world')