假設您currency_trading_pairs使用以下元素呼叫以下串列：
currency_trading_pairs = ['USD/CAD', 'EUR/USD', 'GBP/USD', 'NZD/USD', 'AUD/USD',
'USD/JPY', 'EUR/CAD', 'EUR/AUD', 'EUR/JPY', 'EUR/GBP',
'AUD/CAD', 'GBP/JPY', 'CHF/JPY', 'AUD/JPY', 'AUD/NZD']
現在，假設您使用以下資料呼叫filtered_df了以下資料框：
Time Currency Volatility expected Event
24 04:30 GBP Low Volatility Expected Inflation Expectations
25 05:00 EUR High Volatility Expected EU Leaders Summit
26 05:10 EUR Low Volatility Expected Italian 15-Year BTP Auction
27 05:10 EUR Low Volatility Expected Italian 3-Year BTP Auction
28 05:10 EUR Low Volatility Expected Italian 7-Year BTP Auction
29 06:00 EUR Low Volatility Expected Spanish Consumer Confidence
30 06:30 INR Low Volatility Expected Bank Loan Growth
31 06:30 INR Low Volatility Expected Deposit Growth
32 06:30 INR Low Volatility Expected FX Reserves, USD
33 07:00 INR Low Volatility Expected Cumulative Industrial Production (Jan)
34 07:00 INR Low Volatility Expected Industrial Production (YoY) (Jan)
35 07:00 INR Low Volatility Expected Manufacturing Output (MoM) (Jan)
36 07:00 BRL Moderate Volatility Expected CPI (YoY) (Feb)
37 07:00 BRL Moderate Volatility Expected CPI (MoM) (Feb)
38 08:06 BRL Moderate Volatility Expected Brazilian IPCA Inflation Index SA (MoM)(Feb)
39 08:30 CAD Low Volatility Expected Capacity Utilization Rate (Q4)
40 08:30 CAD High Volatility Expected Employment Change (Feb)
41 08:30 CAD Low Volatility Expected Full Employment Change (Feb)
42 08:30 CAD Low Volatility Expected Part Time Employment Change (Feb)
43 08:30 CAD Low Volatility Expected Participation Rate (Feb)
44 08:30 CAD Moderate Volatility Expected Unemployment Rate (Feb)
您如何找到currency_trading_pairs（串列）中的哪些貨幣對（元素）在列中的所有單元格中都缺少兩種貨幣，Currency以便filtered_df您可以在名為 的變數中獲得以下輸出the_missing_pairs：
the_missing_pairs = ['NZD/USD', 'AUD/USD', 'USD/JPY', 'CHF/JPY', 'AUD/JPY', 'AUD/NZD']
進一步解釋：基本上，確保串列中的所有貨幣名稱 都the_missing_pairs 不會出現在 .Currency filtered_df
uj5u.com熱心網友回復：
我實際上會轉換currency_trading_pairs為 Series 物件。/然后你可以用and分割explode，然后使用isin, 最后groupby(level=0) any來生成完美的掩碼：
ctp = pd.Series(currency_trading_pairs)
the_missing_pairs = ctp[~ctp.str.split('/').explode().isin(df['Currency']).groupby(level=0).any()].tolist()
輸出：
>>> the_missing_pairs
['NZD/USD', 'AUD/USD', 'USD/JPY', 'CHF/JPY', 'AUD/JPY', 'AUD/NZD']
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