I have the following data frame:
import pandas as pd
import numpy as np
df = pd.DataFrame({'Manufacturer':['Mercedes', 'BMW', 'Mercedes', 'Audi', 'Honda', 'Aston Martin', 'Audi', 'Jeep', 'Land Rover'],
'Color':['Blue', 'White', 'Black', 'Green', 'Red', 'White', 'Silver', 'Silver', 'Blue'],
'Country':['United States', '["United States", "Mexico"]', 'Ireland', 'Japan', '["United States","Canada"]', 'Sweden', 'United Kingdom', 'United Kingdom', '["Brazil","United States","Canada"]'],
'Region':['Americas','','Europe','Asia','','Europe', 'Europe', 'Europe', '']
})
Manufacturer Color Country Region
0 Mercedes Blue United States Americas
1 BMW White ['United States','Mexico']
2 Mercedes Black Ireland Europe
3 Audi Green Japan Asia
4 Honda Red ['Canada','United States']
5 Aston Martin White Sweden Europe
6 Audi Silver United Kingdom Europe
7 Jeep Silver United Kingdom Europe
8 Land Rover Blue ['Brazil','United States','Canada']
I would like to write "Americas" to the Region
column if:
a) there is no existing value in the Region
column, and
b) the Country
column has "United States" somewhere in the string
It's possible to use np.where
, as follows:
df['Region'] = np.where(df['Country'].str.contains('United States'), 'Americas', '**ERROR**')
But, this approach overwrites the existing values in the Region
column:
Manufacturer Color Country Region
0 Mercedes Blue United States Americas
1 BMW White ["United States", "Japan"] Americas
2 Mercedes Black Ireland **ERROR**
3 Audi Green Japan **ERROR**
4 Honda Red ["United States","Canada"] Americas
5 Aston Martin White Sweden **ERROR**
6 Audi Silver United Kingdom **ERROR**
7 Jeep Silver United Kingdom **ERROR**
8 Land Rover Blue ["Brazil","United States","Canada"] Americas
What's the best way to do this without overwriting any existing values in the Region
column?
Thanks in advance!
You can easily do with your own approach by a little twisting in your code. I hope this code will solve your problem:
df['Region'] = np.where((df['Region'].isnull()|(df['Region']==''))&(df['Country'].str.contains('United States')), 'Americas', df['Region'])
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