groupby.first() 和 groupby.head(1) 有什么区别？

两者都返回每组第一行的 DataFrame。在阅读 API 参考时，它首先说“计算第一组值”，但是当并排查看两个输出时，我没有发现重大差异。

我错过了什么吗？

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"]})

第一个API http://pandas.pydata.org/pandas-docs/stable/generated/pandas.core.groupby.GroupBy.first.html#pandas.core.groupby.GroupBy.first

主要区别在于first()将跳到第一个非空值，而head(1) won't.

如果我掉落np.nan进入你的例子：

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

然后我们有：

>>> df.groupby('id').head(1)
    id   value
0    1     NaN      # NaN is included
3    2   first
5    3   first
9    4  second
11   5   first
12   6   first
15   7  fourth

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

（此外，如你所见，head()重置索引。）