Python 将列表与列匹配并从列中提取匹配值

我在匹配dataframe的列表和列以及从匹配中提取列中的特定匹配值时遇到问题

数据集：

    address
0   58 Chatham Street, Chatham, New Jersey, 07928
1   3420 W. MacArthur Blvd. Ste. C, Santa Ana, California
2   2016 Chalk Rd, Wake Forest, North Carolina, 27587

我有一份包含州名的清单

state = ['New York','New Jersey','California',...]

渴望结果

    address                                                   State
0   58 Chatham Street, Chatham, New Jersey, 07928             New Jersey
1   3420 W. MacArthur Blvd. Ste. C, Santa Ana, California     California
2   2016 Chalk Rd, Wake Forest, North Carolina, 27587         North Carolina

我试过的代码

for i in state:
    ship_add['state'] = ship_add['address'].str.strip(i)

使用：

如果匹配分割值：

state = ['New York','New Jersey','California','North Carolina']

df1 = df['address'].str.split(', ', expand=True)
df['State'] = df1.where(df1.isin(state)).ffill(1).iloc[:, -1]
print (df)
                                             address           State
0      58 Chatham Street, Chatham, New Jersey, 07928      New Jersey
1  3420 W. MacArthur Blvd. Ste. C, Santa Ana, Cal...      California
2  2016 Chalk Rd, Wake Forest, North Carolina, 27587  North Carolina

尝试：

---

这种方法对于更大的数据也会更快

嗨，耶斯雷尔，它给了我一个价值观。这是我的错。我的数据集有问题，因为我面临Nan。是的，现在开始工作了。感谢您可以基于逗号将值拆分为新的列，因为获取状态的模式在df['address']的每一行中都是不固定的。str.split（'，'，expand=True）如果您尝试提取那些并非结尾都是数字的值，该怎么办

.str.extract（r'（\w[^，]*）（？：，\s*\d+）？$，expand=False）

？

state = ['New York','New Jersey','California','North Carolina']

df1 = df['address'].str.split(', ', expand=True)
df['State'] = df1.where(df1.isin(state)).ffill(1).iloc[:, -1]
print (df)
                                             address           State
0      58 Chatham Street, Chatham, New Jersey, 07928      New Jersey
1  3420 W. MacArthur Blvd. Ste. C, Santa Ana, Cal...      California
2  2016 Chalk Rd, Wake Forest, North Carolina, 27587  North Carolina

state = ['New York','New Jersey','California','North Carolina']
def search_states(df):
    for i in state:
        if i in df['address']:
            df['states'] = i
            break
        else:
            continue
    return df
df = df.apply(search_states, axis = 1)