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In pandas dataframe, how to fill the value of a column conditionally to values in an other column being part of a list ?
This is very similar to this SO question, but when I apply:
df['type'] = np.where(df['food'] in ['apple', 'banana', 'kiwi'], 'fruit', 'oth. food')
I got an error:
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
I suppose the in operator has been not overridden to work with vectors..
509
You can extract a column of pandas DataFrame based on another value by using the DataFrame. query() method. The query() is used to query the columns of a DataFrame with a boolean expression.
Using fillna() to fill values from another column Here, we apply the fillna() function on “Col1” of the dataframe df and pass the series df['Col2'] as an argument. The above code fills the missing values in “Col1” with the corresponding values (based on the index) from “Col2”.
this should work
df['type'] = np.where(df['food'].isin(['apple', 'banana', 'kiwi']), 'fruit', 'oth. food')
I think you can use isin:
df['type'] = np.where(df['food'].isin(['apple', 'banana', 'kiwi']), 'fruit', 'oth. food')
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