转置表，然后设置并重命名索引 [英] Transpose table then set and rename index

问题描述

我想转置一个表并重命名索引.

I want to transpose a table and rename the index.

如果显示具有现有索引Time的df，我将得到

If I display the df with existing index Time I get

Time  v1   v2
1     0.5  0.3
2     0.2  0.1
3     0.3  0.3

然后在df.transpose()之后我在

Time  1    2    3
v1    0.5  0.2  0.3
v2    0.3  0.1  0.3

有趣的是，如果我现在这样做df.Time我会得到

Interestingly if I do now df.Time I get

AttributeError: 'DataFrame' object has no attribute 'Time'

尽管它会显示在输出中.

although it gets displayed in the output.

我找不到一种方法可以轻松地将列Time重命名为Variable并将其设置为新索引..

I can't find a way to easily rename the column Time to Variable and set that as the new index ..

我尝试了df.reset_index().set_index("index")，但是得到的却是这样的东西:

I tried df.reset_index().set_index("index") but what I get is something that looks like this:

Time   1    2    3
index
v1     0.5  0.2  0.3
v2     0.3  0.1  0.3

推荐答案

您只需要通过

You need only rename column names by rename_axis:

print (df.transpose().rename_axis('Variable', axis=1))
Variable    1    2    3
v1        0.5  0.2  0.3
v2        0.3  0.1  0.3

或通过分配名称来设置新的列名称:

Or set new column names by assign name:

df1 = df.transpose()
df1.columns.name = 'Var'
print (df1)
Var    1    2    3
v1   0.5  0.2  0.3
v2   0.3  0.1  0.3

但是我认为您需要从index设置新列，然后将列index重命名为var，还将列名重设为None:

But I think you need set new column from index and then rename column index to var, also reset column names to None:

df1 = df.transpose().reset_index().rename(columns={'index':'var'})
df1.columns.name = None
print (df1)
  var    1    2    3
0  v1  0.5  0.2  0.3
1  v2  0.3  0.1  0.3

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