排序数据框后更新索引 [英] Update index after sorting data-frame

问题描述

采用以下数据框:

x = np.tile(np.arange(3),3)
y = np.repeat(np.arange(3),3)
df = pd.DataFrame({"x": x, "y": y})

   x  y
0  0  0
1  1  0
2  2  0
3  0  1
4  1  1
5  2  1
6  0  2
7  1  2
8  2  2

我需要先按x对其进行排序，然后仅按y对其进行排序:

I need to sort it by x first, and only second by y:

df2 = df.sort(["x", "y"])

   x  y
0  0  0
3  0  1
6  0  2
1  1  0
4  1  1
7  1  2
2  2  0
5  2  1
8  2  2

如何更改索引，使其再次上升. IE.我怎么得到这个:

How can I change the index such that it is ascending again. I.e. how do I get this:

   x  y
0  0  0
1  0  1
2  0  2
3  1  0
4  1  1
5  1  2
6  2  0
7  2  1
8  2  2

我尝试了以下方法.不幸的是，它根本不会改变索引:

I have tried the following. Unfortunately, it doesn't change the index at all:

df2.reindex(np.arange(len(df2.index)))

推荐答案

您可以使用

You can reset the index using reset_index to get back a default index of 0, 1, 2, ..., n-1 (and use drop=True to indicate you want to drop the existing index instead of adding it as an additional column to your dataframe):

In [19]: df2 = df2.reset_index(drop=True)

In [20]: df2
Out[20]:
   x  y
0  0  0
1  0  1
2  0  2
3  1  0
4  1  1
5  1  2
6  2  0
7  2  1
8  2  2

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