檢查一個資料框列是否是另一列的子集

我有一個帶有 和 列的資料框Enrolled_Months，Eligible_Months描述如下：

month_list1 = [
    [(1, 2018), (2, 2018), (3, 2019)],
    [(7, 2018), (8, 2018), (10, 2018)],
    [(4, 2018), (5, 2018), (7, 2018)],
    [(1, 2019), (2, 2019), (4, 2019)]
]

month_list2 = [
    [(2, 2018), (3, 2019)],
    [(7, 2018), (8, 2018)],
    [(2, 2018), (3, 2019)],
    [(10, 2018), (11, 2019)]
]

EID = [1, 2, 3, 4]

df = pd.DataFrame({
    'EID': EID,
    'Enrolled_Months': month_list1,
    'Eligible_Months': month_list2
})
df

Out[6]: 
   EID                     Enrolled_Months           Eligible_Months
0    1   [(1, 2018), (2, 2018), (3, 2019)]    [(2, 2018), (3, 2019)]
1    2  [(7, 2018), (8, 2018), (10, 2018)]    [(7, 2018), (8, 2018)]
2    3   [(4, 2018), (5, 2018), (7, 2018)]    [(2, 2018), (3, 2019)]
3    4   [(1, 2019), (2, 2019), (4, 2019)]  [(10, 2018), (11, 2019)]

我想創建一個新列Check，如果Eligible_Months它是Enrolled_Months. 我想要的輸出如下：

Out[8]: 
   EID                     Enrolled_Months           Eligible_Months  Check
0    1   [(1, 2018), (2, 2018), (3, 2019)]    [(2, 2018), (3, 2019)]   True
1    2  [(7, 2018), (8, 2018), (10, 2018)]    [(7, 2018), (8, 2018)]   True
2    3   [(4, 2018), (5, 2018), (7, 2018)]    [(2, 2018), (3, 2019)]  False
3    4   [(1, 2019), (2, 2019), (4, 2019)]  [(10, 2018), (11, 2019)]  False

我嘗試了以下方法：

df['Check'] = set(df['Eligible_Months']).issubset(df['Enrolled_Months'])

但最終得到錯誤TypeError: unhashable type: 'list'。

關于如何實作這一目標的任何想法？

旁注：Enrolled_Months資料最初的格式大不相同，每個月都有自己的二進制列，并且有一個單獨的Year列指定年份（真的很糟糕的設計 imo）。我創建了串列列，因為我認為使用它會更容易，但請告訴我原始格式是否更適合我想要實作的目標。

uj5u.com熱心網友回復：

您可以使用一些explodes然后eval和any：

df['Check'] = df.explode('Eligible_Months').explode('Enrolled_Months').eval('Enrolled_Months == Eligible_Months').groupby(level=0).any()

輸出：

>>> df
   EID                     Enrolled_Months           Eligible_Months  Check
0    1   [(1, 2018), (2, 2018), (3, 2019)]    [(2, 2018), (3, 2019)]   True
1    2  [(7, 2018), (8, 2018), (10, 2018)]    [(7, 2018), (8, 2018)]   True
2    3   [(4, 2018), (5, 2018), (7, 2018)]    [(2, 2018), (3, 2019)]  False
3    4   [(1, 2019), (2, 2019), (4, 2019)]  [(10, 2018), (11, 2019)]  False

uj5u.com熱心網友回復：

您可以使用df.apply()創建新列：

df['Check'] = df.apply(
    lambda row: set(row['Eligible_Months']).issubset(row['Enrolled_Months']), axis=1
)

這輸出：

   EID                     Enrolled_Months           Eligible_Months  Check
0    1   [(1, 2018), (2, 2018), (3, 2019)]    [(2, 2018), (3, 2019)]   True
1    2  [(7, 2018), (8, 2018), (10, 2018)]    [(7, 2018), (8, 2018)]   True
2    3   [(4, 2018), (5, 2018), (7, 2018)]    [(2, 2018), (3, 2019)]  False
3    4   [(1, 2019), (2, 2019), (4, 2019)]  [(10, 2018), (11, 2019)]  False

uj5u.com熱心網友回復：

串列理解作業正常：

df.assign(check = [set(l).issuperset(r) 
                   for l, r in 
                   zip(df.Enrolled_Months, df.Eligible_Months)])

   EID                     Enrolled_Months           Eligible_Months  check
0    1   [(1, 2018), (2, 2018), (3, 2019)]    [(2, 2018), (3, 2019)]   True
1    2  [(7, 2018), (8, 2018), (10, 2018)]    [(7, 2018), (8, 2018)]   True
2    3   [(4, 2018), (5, 2018), (7, 2018)]    [(2, 2018), (3, 2019)]  False
3    4   [(1, 2019), (2, 2019), (4, 2019)]  [(10, 2018), (11, 2019)]  False

標籤：Python 熊猫 列表 数据框 元组

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