I have a data frame with country and traffic columns:
Country | Traffic
US 8687
Italy 902834
Germany 2343
Brazil 4254
France 23453
I want to add a third column called "Region" to this data frame. It would look like this:
Country | Traffic | Region
US 8687 US
Italy 902834 EU
Germany 2343 EU
Brazil 4254 LA
France 23453 EU
The following code works if I have only two Regions. I am looking more for an if/else
, map
, or lambda
statement:
df['Region'] = np.where(df['Country'] == 'US', 'US', 'EU')
Thank You.
You could use a dictionary:
region_from_country = {
'US': 'US',
'Italy': 'EU',
'Germany': 'EU',
'Brazil': 'LA',
'France': 'EU',
}
df['Region'] = df['Country'].replace(region_from_country)
The keys in the dictionary are the countries and the values are the corresponding regions.
One simple approach is this:
dict ={'US':'US','Italy':'EU','Germany':'EU','Brazil':'LA','France':'EU'}
df['Region']=df['Country'].apply(lambda x : dict[x])
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