问题描述
我有这样的数据框df:
a b
10 2
3 1
0 0
0 4
....
# about 50,000+ rows
我希望选择df[:5, 'a'].但是当我呼叫df.loc[:5, 'a']时，出现错误:KeyError: 'Cannot get right slice bound for non-unique label: 5.当我调用df.loc[5]时，结果包含250行，而当我使用df.iloc[5]时只有一行.为什么会发生这种情况，如何正确索引呢?先感谢您！
I wish to choose the df[:5, 'a']. But When I call df.loc[:5, 'a'], I got an error: KeyError: 'Cannot get right slice bound for non-unique label: 5. When I call df.loc[5], the result contains 250 rows while there is just one when I use df.iloc[5]. Why does this thing happen and how can I index it properly? Thank you in advance!
推荐答案
说明了错误消息此处:if the index is not monotonic, then both slice bounds must be unique members of the index.
.loc和.iloc之间的区别是基于label与基于integer position的索引-请参阅文档. .loc用于选择单独的labels或slices标签.这就是.loc[5]选择index的值为250的所有行的原因(错误是关于非唯一索引的).相反，iloc选择第5行(0索引).这就是为什么只得到一行的原因，索引值可能是5，也可能不是.希望这会有所帮助！
The difference between .loc and .iloc is label vs integer position based indexing - see docs. .loc is intended to select individual labels or slices of labels. That's why .loc[5] selects all rows where the index has the value 250 (and the error is about a non-unique index). iloc, in contrast, select row number 5 (0-indexed). That's why you only get a single row, and the index value may or may not be 5. Hope this helps!
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