pandas iloc返回的范围与loc不同

问题描述

我对pandas的iloc函数有些困惑，因为我想选择一系列列，并且输出与预期的不同.行选择也会发生同样的情况，所以我写了一个小例子:

I am a bit confused of the iloc function of pandas, because I want to select a range of columns and the output is different than expected. The same will happen to row selection, so I wrote a little example:

template = pd.DataFrame(
    {'Headline': ['Subheading', '', 'Animal', 'Tiger', 'Bird', 'Lion'],
     'Headline2': ['', 'Weight', 2017, 'group1', 'group2', 'group3'],
     'Headline3': ['', '', 2018, 'group1', 'group2', 'group3']
     })

     Headline Headline2 Headline3
0  Subheading                    
1                Weight          
2      Animal      2017      2018
3       Tiger    group1    group1
4        Bird    group2    group2
5        Lion    group3    group3

我想用print(template.loc[1:2])选择第1行到第2行，结果是我所期望的:

I want to select line 1 to line 2 with print(template.loc[1:2]) the result is what I have expected:

  Headline Headline2 Headline3
1             Weight          
2   Animal      2017      2018

如果我这样做print(template.iloc[1:2])我会认为我得到了相同的结果，但没有:

If I do this print(template.iloc[1:2]) I would think that I get the same result, but no:

  Headline Headline2 Headline3
1             Weight          

我有点困惑，因为我期望两个函数的行为相同，但是如果我选择一个范围(FROM:TO)，两个函数的输出会有所不同.
似乎使用iloc必须具有TO值+1才能获得与loc print(template.iloc[1:3])相同的结果:

I am a bit confused, because I expected the same behavior for both functions, but the output of both functions differ if I select a range (FROM:TO).
It seems like using iloc needs to have the TO value +1 in order to have the same result as loc print(template.iloc[1:3]):

  Headline Headline2 Headline3
1             Weight          
2   Animal      2017      2018

有人可以给它一些照明吗?

Can someone put some light on it?

推荐答案

如:

As it mentioned in docs for loc:

另一方面，iloc确实基于基于整数位置的索引进行选择，因此它不包含停止索引.

On the other hand, iloc do selects based on integer-location based indexing, so it doesn't include stop index.

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