我正在嘗試編寫一個 python 函數，它允許我向 pandas df 添加功能以進行機器學習。我想我誤解了如何在 python 函數中使用字符串。該函數查看 df 的一行，檢查行標識符是否在未來幾個月（以下行數）具有相同的標識符。如果是這樣，它將未來行的“開始”特征的值添加到新特征列，否則將初始行的“結束”。這是一個定制的班次功能。一旦我添加了這個功能，我想再添加一列 1 或 0 作為 df 的新功能，并帶有適當的列標簽。這將被標記為“feat_so_many_months_in_future_is_higher_or_lower”。問題是我什至無法到達閾值部分附近的第二個二進制文件。我在添加第一個具有適當名稱的新功能時遇到問題。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我的想法是調用函數如下：binary_up_down('feat_value_in_1m', 1, 5)#Thenbinary_up_down('feat_value_in_3m', 3, 5) # and on an on...當我運行代碼時，這一行似乎是問題所在：df[str(name_of_new_feature)] = name_of_new_feature...因為它將所有新的特征列值添加為列名！非常感謝任何指針！
1 回答
互換的青春
TA貢獻1797條經驗 獲得超6個贊
您將替換name_of_new_feature為函數第一行中的列表。我建議將其重命名為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
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