fuel_dotted_decimal.py

numeric_columns = ['distance','consume','temp_inside','refill liters'] # columns with ','

for column in numeric_columns:
    #print(column)
    x = [x.replace(',','.') for x in df[column].values]
    df[column] = list(map(np.float32, x))
    
#including other numeric columns
numeric_columns.extend(['speed','temp_outside'])

# Defining the dataypes
for column in df.columns:
    if column in numeric_columns:
        df[column] = df[column].astype('float32')
    else:
        df[column] = df[column].astype('int64')