Use Pandas to load data from data_file = os.path.join('..', 'data', 'house_tiny.csv').

import pandas as pd

data = pd.read_csv(data_file)

For numerical values in inputs that are missing, replace the “NaN” entries with the mean value of the same column

inputs = inputs.fillna(inputs.mean())

What does inputs = pd.get_dummies(inputs, dummy_na=True) do?

For categorical or discrete values in inputs, we consider “NaN” as a category. If the “Alley” column only takes two types of categorical values “Pave” and “NaN”, pandas can automatically convert this column to two columns “Alley_Pave” and “Alley_nan”. A row whose alley type is “Pave” will set values of “Alley_Pave” and “Alley_nan” to 1 and 0. A row with a missing alley type will set their values to 0 and 1.

Convert inputs dataframes into the tensor format

torch.tensor(inputs.values)