给出一个小测试数据如下：
id city address
0 1 HK 55 Peng Sui Road Che Sham Man Hong Kong
1 2 HK 77 Kun Chok Fong San Tsuen Noi Fok Kowloon
2 3 HK 48 Nut Chok Lou Tsa Sik Kowloon Hong Kong
3 4 HK Block 69, Hai Ang Court Aberdeen Kowloon
4 5 HK 40 Tsang Tai Kit Street Wak Luet New Territories
如果Hong Kong不包含在 中address，那么我想detailed_add通过组合创建一个新列df['address'] + ', ' + df['city']：
id city address detailed_add
0 1 HK 55 Peng Sui Road Che Sham Man Hong Kong 55 Peng Sui Road Che Sham Man Hong Kong
1 2 HK 77 Kun Chok Fong San Tsuen Noi Fok Kowloon 77 Kun Chok Fong San Tsuen Noi Fok Kowloon, HK
2 3 HK 48 Nut Chok Lou Tsa Sik Kowloon Hong Kong 48 Nut Chok Lou Tsa Sik Kowloon Hong Kong
3 4 HK Block 69, Hai Ang Court Aberdeen Kowloon Block 69, Hai Ang Court Aberdeen Kowloon, HK
4 5 HK 40 Tsang Tai Kit Street Wak Luet New Territories 40 Tsang Tai Kit Street Wak Luet New Territori..., HK
过滤行：df[~df['address'].str.contains('Hong Kong', na = False)].
id city address
1 2 HK 77 Kun Chok Fong San Tsuen Noi Fok Kowloon
3 4 HK Block 69, Hai Ang Court Aberdeen Kowloon
4 5 HK 40 Tsang Tai Kit Street Wak Luet New Territories
我怎么能那样做？谢谢。
你可以使用 np.where()
df['detailed_add'] = np.where(df['address'].str.contains('Hong Kong'), df['address'], df['address'] + ', ' + df['city'])
print(df)
id city address detailed_add
0 1 HK 55 Peng Sui Road Che Sham Man Hong Kong 55 Peng Sui Road Che Sham Man Hong Kong
1 2 HK 77 Kun Chok Fong San Tsuen Noi Fok Kowloon 77 Kun Chok Fong San Tsuen Noi Fok Kowloon, HK
2 3 HK 48 Nut Chok Lou Tsa Sik Kowloon Hong Kong 48 Nut Chok Lou Tsa Sik Kowloon Hong Kong
3 4 HK Block 69, Hai Ang Court Aberdeen Kowloon Block 69, Hai Ang Court Aberdeen Kowloon, HK
4 5 HK 40 Tsang Tai Kit Street Wak Luet New Territories 40 Tsang Tai Kit Street Wak Luet New Territori...
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