重命名数据切片的列上的列未按预期执行 [英] Renaming columns on slice of dataframe not performing as expected

问题描述

我试图清除数据框中的列名，但只清除部分列.

I was trying to clean up column names in a dataframe but only a part of the columns.

当尝试以某种方式替换数据框切片上的列名称时，它不起作用，为什么?

It doesn't work when trying to replace column names on a slice of the dataframe somehow, why is that?

让我们说我们有以下数据框:
注意，底部是可复制的代码以重现数据:

Lets say we have the following dataframe:
Note, on the bottom is copy-able code to reproduce the data:

   Value ColAfjkj ColBhuqwa ColCouiqw
0      1        a         e         i
1      2        b         f         j
2      3        c         g         k
3      4        d         h         l

我要清理列名(预期输出):

I want to clean up the column names (expected output):

   Value ColA ColB ColC
0      1    a    e    i
1      2    b    f    j
2      3    c    g    k
3      4    d    h    l

---

方法1 :

我可以这样获得干净的列名:

I can get the clean column names like this:

df.iloc[:, 1:].columns.str[:4]

Index(['ColA', 'ColB', 'ColC'], dtype='object')

或

方法2 :

s = df.iloc[:, 1:].columns
[col[:4] for col in s]

['ColA', 'ColB', 'ColC']

---

但是，当我尝试覆盖列名时，什么也没发生:

---

But when I try to overwrite the column names, nothing happens:

df.iloc[:, 1:].columns = df.iloc[:, 1:].columns.str[:4]

   Value ColAfjkj ColBhuqwa ColCouiqw
0      1        a         e         i
1      2        b         f         j
2      3        c         g         k
3      4        d         h         l

与第二种方法相同:

s = df.iloc[:, 1:].columns
cols = [col[:4] for col in s]

df.iloc[:, 1:].columns = cols

   Value ColAfjkj ColBhuqwa ColCouiqw
0      1        a         e         i
1      2        b         f         j
2      3        c         g         k
3      4        d         h         l

---

这确实有效，但是您必须手动连接第一列的名称，这并不理想:

---

This does work, but you have to manually concat the name of the first column, which is not ideal:

df.columns = ['Value'] + df.iloc[:, 1:].columns.str[:4].tolist()

   Value ColA ColB ColC
0      1    a    e    i
1      2    b    f    j
2      3    c    g    k
3      4    d    h    l

有没有更简单的方法来实现这一目标?我想念什么吗?

Is there an easier way to achieve this? Am I missing something?

要复制的数据帧:

df = pd.DataFrame({'Value':[1,2,3,4],
                   'ColAfjkj':['a', 'b', 'c', 'd'],
                   'ColBhuqwa':['e', 'f', 'g', 'h'],
                   'ColCouiqw':['i', 'j', 'k', 'l']})

推荐答案

这是因为熊猫的索引是不可变的.如果您查看 class pandas的文档.索引 ，您会看到它定义为:

This is because pandas' index is immutable. If you check the documentation for class pandas.Index, you'll see that it is defined as:

不可变的ndarray实现有序的，可切片的集合

Immutable ndarray implementing an ordered, sliceable set

因此，要对其进行修改，您必须创建一个新的列名列表，例如:

So in order to modify it you'll have to create a new list of column names, for instance with:

df.columns = [df.columns[0]] + list(df.iloc[:, 1:].columns.str[:4])

---

另一种选择是使用 使用包含要替换列的字典的重命名 :

df.rename(columns=dict(zip(df.columns[1:], df.columns[1:].str[:4])))

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