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import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

%matplotlib inline
auto_prices = pd.read_csv('Automobile price data _Raw_.csv')

def clean_auto_data(auto_prices):
    'Function to load the auto price data set from a .csv file' 
    import pandas as pd
    import numpy as np
    
    ## Recode names
    ## fix column names so the '-' character becomes '_'
    cols = auto_prices.columns
    auto_prices.columns = [str.replace('-', '_') for str in cols]
    
    ## Treat missing values
    ## Remove rows with missing values, accounting for mising values coded as '?'
    cols = ['price', 'bore', 'stroke', 
          'horsepower', 'peak_rpm']
    for column in cols:
        auto_prices.loc[auto_prices[column] == '?', column] = np.nan
    auto_prices.dropna(axis = 0, inplace = True)

    ## Transform column data type
    ## Convert some columns to numeric values
    for column in cols:
        auto_prices[column] = pd.to_numeric(auto_prices[column])

    return auto_prices
auto_prices = clean_auto_data(auto_prices)

print(auto_prices.columns)
Index(['symboling', 'normalized_losses', 'make', 'fuel_type', 'aspiration', 'num_of_doors', 'body_style', 'drive_wheels', 'engine_location', 'wheel_base', 'length', 'width', 'height', 'curb_weight', 'engine_type', 'num_of_cylinders', 'engine_size', 'fuel_system', 'bore', 'stroke', 'compression_ratio', 'horsepower', 'peak_rpm', 'city_mpg', 'highway_mpg', 'price'], dtype='object') 
auto_prices.head()

auto_prices.dtypes
symboling              int64
normalized_losses     object
make                  object
fuel_type             object
aspiration            object
num_of_doors          object
body_style            object
drive_wheels          object
engine_location       object
wheel_base           float64
length               float64
width                float64
height               float64
curb_weight            int64
engine_type           object
num_of_cylinders      object
engine_size            int64
fuel_system           object
bore                 float64
stroke               float64
compression_ratio    float64
horsepower             int64
peak_rpm               int64
city_mpg               int64
highway_mpg            int64
price                  int64
dtype: object
auto_prices.describe()