熊猫数据框获得每组的第一行

Question

我有一只熊猫 DataFrame 如下所示：

 df = pd.DataFrame({'id' : [1,1,1,2,2,3,3,3,3,4,4,5,6,6,6,7,7],
                'value'  : ["first","second","second","first",
                            "second","first","third","fourth",
                            "fifth","second","fifth","first",
                            "first","second","third","fourth","fifth"]})

我想将其分组 ["id","value"] 并获取每组的第一行：

         id   value
0        1   first
1        1  second
2        1  second
3        2   first
4        2  second
5        3   first
6        3   third
7        3  fourth
8        3   fifth
9        4  second
10       4   fifth
11       5   first
12       6   first
13       6  second
14       6   third
15       7  fourth
16       7   fifth

预期结果：

     id   value
     1   first
     2   first
     3   first
     4  second
     5  first
     6  first
     7  fourth

我试过以下，它只给出了 DataFrame 的第一行。对此有任何帮助表示赞赏。

 In [25]: for index, row in df.iterrows():
   ....:     df2 = pd.DataFrame(df.groupby(['id','value']).reset_index().ix[0])

原文由 Nilani Algiriyage 发布，翻译遵循 CC BY-SA 4.0 许可协议

Answer 1

>>> df.groupby('id').first()
     value
id
1    first
2    first
3    first
4   second
5    first
6    first
7   fourth

如果您需要 id 作为列：

 >>> df.groupby('id').first().reset_index()
   id   value
0   1   first
1   2   first
2   3   first
3   4  second
4   5   first
5   6   first
6   7  fourth

要获取 n 条第一条记录，可以使用 head()：

 >>> df.groupby('id').head(2).reset_index(drop=True)
    id   value
0    1   first
1    1  second
2    2   first
3    2  second
4    3   first
5    3   third
6    4  second
7    4   fifth
8    5   first
9    6   first
10   6  second
11   7  fourth
12   7   fifth

原文由 Roman Pekar 发布，翻译遵循 CC BY-SA 3.0 许可协议

Answer 2

这将为您提供每组的第二行（零索引，nth(0) 与 first() 相同）：

 df.groupby('id').nth(1)

文档：http: //pandas.pydata.org/pandas-docs/stable/groupby.html#taking-the-nth-row-of-each-group

原文由 wij 发布，翻译遵循 CC BY-SA 3.0 许可协议