Python 熊猫中的不同 read_csv index_col = None / 0 / False
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Different read_csv index_col = None / 0 / False in pandas
提问by markov zain
I used the read_csv command following below:
我使用了下面的 read_csv 命令：
In [20]:
dataframe = pd.read_csv('D:/UserInterest/output/ENFP_0719/Bookmark.csv', index_col=None)
dataframe.head()
Out[20]:
Unnamed: 0 timestamp url visits
0 0 1.404028e+09 http://m.blog.naver.com/PostView.nhn?blogId=mi... 2
1 1 1.404028e+09 http://m.facebook.com/l.php?u=http%3A%2F%2Fblo... 1
2 2 1.404028e+09 market://details?id=com.kakao.story 1
3 3 1.404028e+09 https://story-api.kakao.com/upgrade/install 4
4 4 1.403889e+09 http://m.cafe.daum.net/WorldcupLove/Knj/173424... 1
The result shows column Unnamed:0and it is simillar when I used index_col=False, but when I used index_col=0, the result is following below:
结果显示列Unnamed:0，当我使用时它是相似的index_col=False，但是当我使用时index_col=0，结果如下：
dataframe = pd.read_csv('D:/UserInterest/output/ENFP_0719/Bookmark.csv', index_col=0)
dataframe.head()
Out[21]:
timestamp url visits
0 1.404028e+09 http://m.blog.naver.com/PostView.nhn?blogId=mi... 2
1 1.404028e+09 http://m.facebook.com/l.php?u=http%3A%2F%2Fblo... 1
2 1.404028e+09 market://details?id=com.kakao.story 1
3 1.404028e+09 https://story-api.kakao.com/upgrade/install 4
4 1.403889e+09 http://m.cafe.daum.net/WorldcupLove/Knj/173424... 1
The result did show the column Unnamed:0, In here I want to ask, what is the difference between index_col=None, index_col=0, and index_col=False, I have read the documentation in this, but I still did not get the idea.
结果确实显示了该列Unnamed:0，在这里我想问一下index_col=None，index_col=0， 和之间有什么区别index_col=False，我已经阅读了this中的文档，但我仍然没有得到这个想法。
采纳答案by EdChum
UPDATE
更新
I think since version 0.16.1it will now raise an error if you try to pass Truefor index_colto avoid this ambiguity
我认为从0.16.1版本开始，如果您尝试传递Trueforindex_col以避免这种歧义，它现在会引发错误
ORIGINAL
原来的
A lot of people get confused by this, to specify the ordinal index of your column you should pass the int position in this case 0.
很多人对此感到困惑，要指定列的序数索引，您应该在这种情况下传递 int 位置0。
In [3]:
import io
import pandas as pd
t="""index,a,b
0,hello,pandas"""
pd.read_csv(io.StringIO(t))
?
Out[3]:
index a b
0 0 hello pandas
The default value is index_col=Noneas shown above.
默认值index_col=None如上所示。
If we set index_col=0we're explicitly stating to treat the first column as the index:
如果我们设置，index_col=0我们明确声明将第一列视为索引：
In [4]:
pd.read_csv(io.StringIO(t), index_col=0)
Out[4]:
a b
index
0 hello pandas
If we pass index_col=Falsewe get the same result as None:
如果我们通过，index_col=False我们会得到与以下相同的结果None：
In [5]:
pd.read_csv(io.StringIO(t), index_col=False)
Out[5]:
index a b
0 0 hello pandas
If we now state index_col=Nonewe get the same behaviour as when we didn't pass this param:
如果我们现在声明，index_col=None我们会得到与未传递此参数时相同的行为：
In [6]:
pd.read_csv(io.StringIO(t), index_col=None)
Out[6]:
index a b
0 0 hello pandas
There is a bug where if you pass Truethis was erroneously being converted to index_col=1as Truewas being converted to 1:
有一个错误，如果你通过Truethis 被错误地转换index_col=1为True正在转换为1：
In [6]:
pd.read_csv(io.StringIO(t), index_col=True)
Out[6]:
index b
a
0 hello pandas
EDIT
编辑
For the case where you have a blank index column which is what you have:
对于您拥有一个空白索引列的情况：
In [7]:
import io
import pandas as pd
t=""",a,b
0,hello,pandas"""
pd.read_csv(io.StringIO(t))
?
Out[7]:
Unnamed: 0 a b
0 0 hello pandas
In [8]:
pd.read_csv(io.StringIO(t), index_col=0)
Out[8]:
a b
0 hello pandas
In [9]:
pd.read_csv(io.StringIO(t), index_col=False)
Out[9]:
Unnamed: 0 a b
0 0 hello pandas
In [10]:
pd.read_csv(io.StringIO(t), index_col=None)
Out[10]:
Unnamed: 0 a b
0 0 hello pandas
