Convert string into float for multiple columns in data frame

Question

I am playing with the data set from FIFA 19 and currently trying to convert string value, wage and release clauses into float values e.g. €110.5M into 110500000. Here is my function which takes text as an argument and returns float value:

def text_to_num(text):
    d = {'K': 3, 'M': 6, 'B': 9}
    new_text = text[1:]
    if new_text[-1] in d:
        num = new_text[:-1]
        magnitude = new_text[-1]
        return Decimal(num) * 10 ** d[magnitude]
    else:
        return Decimal(new_text)

It's quite easy to apply it on single column, e.g. Value:

def convert_into_float(data):
    data['Value'] = data['Value'].apply(text_to_num)
    return data

I am wondering, how to convert all 3 columns at once instead of using above function three times.

def main():
    # load the data from .csv file, use ID column as index  
    new_data = load_data("data.csv", 'ID') 
    new_data = convert_into_float(new_data)

jezrael · Accepted Answer · 2019-02-12 13:10:20Z

1

You can use DataFrame.applymap with filtered columns by list:

def convert_into_float(data):
    cols = ['col1','col2','col3']
    data[cols] = data[cols].applymap(text_to_num)
    return data

answered Feb 12, 2019 at 13:10

jezrael

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