def process_iris_data(data):
    p_data = np.zeros((data.shape[0], data.shape[1]))
    max_col1 = np.amax(data[:, 0])
    max_col2 = np.amax(data[:, 1])
    max_col3 = np.amax(data[:, 2])
    max_col4 = np.amax(data[:, 3])
    for n in range(len(data)):
        p_data[(n, 0)] = (data[(n, 0)] / max_col1)
        p_data[(n, 1)] = (data[(n, 1)] / max_col2)
        p_data[(n, 2)] = (data[(n, 2)] / max_col3)
        p_data[(n, 3)] = (data[(n, 3)] / max_col4)
    return p_data
def process_iris_data(data):
    p_data = np.zeros((data.shape[0], data.shape[1]))
    max_col1 = np.amax(data[:, 0])
    max_col2 = np.amax(data[:, 1])
    max_col3 = np.amax(data[:, 2])
    max_col4 = np.amax(data[:, 3])
    for n in range(len(data)):
        p_data[(n, 0)] = (data[(n, 0)] / max_col1)
        p_data[(n, 1)] = (data[(n, 1)] / max_col2)
        p_data[(n, 2)] = (data[(n, 2)] / max_col3)
        p_data[(n, 3)] = (data[(n, 3)] / max_col4)
    return p_data