    import numpy as np
    import pandas as pd

#### First, let us get some intuition from it

    >>> data_table = pd.read_csv("/home/yingshaoxo/500_Person_Gender_Height_Weight_Index.csv")

    >>> data_table.head()
       Gender  Height  Weight  Index
    0    Male     174      96      4
    1    Male     189      87      2
    2  Female     185     110      4
    3  Female     195     104      3
    4    Male     149      61      3

#### For our case, we only need the `height and weight` as `input`, `gender` as `output`

    >>> x = data_table[['Height', 'Weight']].values
    >>> x[:10]
    array([[174,  96],
           [189,  87],
           [185, 110],
           [195, 104],
           [149,  61],
           [189, 104],
           [147,  92],
           [154, 111],
           [174,  90],
           [169, 103]])

    >>> def convert_gender_to_number(row):
    ...     if row['Gender'] == 'Male':
    ...         return 1
    ...     else:
    ...         return 0
    ...
    >>> y = data_table[['Gender']].apply(lambda row: convert_gender_to_number(row), axis=1)
    >>> y[:10]
    0    1
    1    1
    2    0
    3    0
    4    1
    5    1
    6    1
    7    1
    8    1
    9    0

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