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我正在尝试编写一个 python 函数，它允许我向 pandas df 添加功能以进行机器学习。我想我误解了如何在 python 函数中使用字符串。

该函数查看 df 的一行，检查行标识符是否在未来几个月（以下行数）具有相同的标识符。如果是这样，它将未来行的“开始”特征的值添加到新特征列，否则将初始行的“结束”。这是一个定制的班次功能。

一旦我添加了这个功能，我想再添加一列 1 或 0 作为 df 的新功能，并带有适当的列标签。这将被标记为“feat_so_many_months_in_future_is_higher_or_lower”。

问题是我什至无法到达阈值部分附近的第二个二进制文件。我在添加第一个具有适当名称的新功能时遇到问题。

def binary_up_down(name_of_new_feature, months_in_future, percent_threshold):
    name_of_new_feature = [] 
    for i in range(0, df.shape[0], 1): 
        try:
            if df['identifier'][i]==df['identifier'][i + months_in_future]:
                name_of_new_feature.append(df['start'][i + months_in_future])
            else:
                name_of_new_feature.append(df['end'][i])
        except KeyError:
                name_of_new_feature.append(df['end'][i])

    df[str(name_of_new_feature)]=name_of_new_feature

    ### Add test to check if shifted value is above or below threshold and name new feature  
        appropriately ###

    return df

我的想法是调用函数如下：

binary_up_down('feat_value_in_1m', 1, 5)
#Then
binary_up_down('feat_value_in_3m', 3, 5) # and on an on...

当我运行代码时，这一行似乎是问题所在：

df[str(name_of_new_feature)] = name_of_new_feature

...因为它将所有新的特征列值添加为列名！

非常感谢任何指针！

4

1 回答 1

1

您将替换name_of_new_feature为函数第一行中的列表。我建议将其重命名为value_of_new_feature

def binary_up_down(name_of_new_feature, months_in_future, percent_threshold):
    value_of_new_feature = [] 
    for i in range(0, df.shape[0], 1): 
        try:
            if df['identifier'][i]==df['identifier'][i + months_in_future]:
                value_of_new_feature .append(df['start'][i + months_in_future])
            else:
                value_of_new_feature .append(df['end'][i])
        except KeyError:
                value_of_new_feature .append(df['end'][i])

    df[name_of_new_feature]=value_of_new_feature 

    ### Add test to check if shifted value is above or below threshold and name new feature  
        appropriately ###

    return df
于 2019-09-22T21:56:49.473 回答