Python 如何使用另一列作为参数修改DataFrame列值

我有这样一个数据帧（数据）：

                     mac  len      corp                               detail
18025           14:1F:BA    8  IeeeRegi          IEEE Registration Authority
18026  14:1F:BA:00:00:00   10  Shenzhen  Shenzhen Mining Technology Co.,Ltd.
18027  14:1F:BA:10:00:00   10   Gloquad                                  NaN
18028  14:1F:BA:20:00:00   10  Deutsche      Deutsche Energieversorgung GmbH
18029  14:1F:BA:30:00:00   10   Private                                  NaN

如何使用data['mac'].str.slice（0，data['len']）等方法获得以下结果

我知道应用方法是可以的：

def sub_mac(x):
    return x.mac[:x.len]
data.mac = data.apply(sub_mac, axis=1)

或

但我想知道是否有其他方法来处理它？ 例如，sql之类的方法：

select SUBSTRING(mac, 0, len) as mac_sub from data;

thx.

试试这个：

资料来源：

In [8]: df
Out[8]:
                     mac  len      corp                               detail
18025           14:1F:BA    8  IeeeRegi          IEEE Registration Authority
18026  14:1F:BA:00:00:00   10  Shenzhen  Shenzhen Mining Technology Co.,Ltd.
18027  14:1F:BA:10:00:00   10   Gloquad                                  NaN
18028  14:1F:BA:20:00:00   10  Deutsche      Deutsche Energieversorgung GmbH
18029  14:1F:BA:30:00:00   10   Private                                  NaN

解决方案：

In [9]: df['mac'] = df.groupby('len')['mac'].transform(lambda x: x.str[:x.name])

结果:

In [10]: df
Out[10]:
              mac  len      corp                               detail
18025    14:1F:BA    8  IeeeRegi          IEEE Registration Authority
18026  14:1F:BA:0   10  Shenzhen  Shenzhen Mining Technology Co.,Ltd.
18027  14:1F:BA:1   10   Gloquad                                  NaN
18028  14:1F:BA:2   10  Deutsche      Deutsche Energieversorgung GmbH
18029  14:1F:BA:3   10   Private                                  NaN

试试这个：

资料来源：

In [8]: df
Out[8]:
                     mac  len      corp                               detail
18025           14:1F:BA    8  IeeeRegi          IEEE Registration Authority
18026  14:1F:BA:00:00:00   10  Shenzhen  Shenzhen Mining Technology Co.,Ltd.
18027  14:1F:BA:10:00:00   10   Gloquad                                  NaN
18028  14:1F:BA:20:00:00   10  Deutsche      Deutsche Energieversorgung GmbH
18029  14:1F:BA:30:00:00   10   Private                                  NaN

解决方案：

In [9]: df['mac'] = df.groupby('len')['mac'].transform(lambda x: x.str[:x.name])

结果:

In [10]: df
Out[10]:
              mac  len      corp                               detail
18025    14:1F:BA    8  IeeeRegi          IEEE Registration Authority
18026  14:1F:BA:0   10  Shenzhen  Shenzhen Mining Technology Co.,Ltd.
18027  14:1F:BA:1   10   Gloquad                                  NaN
18028  14:1F:BA:2   10  Deutsche      Deutsche Energieversorgung GmbH
18029  14:1F:BA:3   10   Private                                  NaN