pandas 冒号(:) 在python 和pandas 中是如何工作的？
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How colon(:) works in python & pandas?
提问by Peng He
I create a DataFrame：
我创建了一个DataFrame：
import pandas as pd
data = pd.DataFrame({'a':range(1,11),'b':['m','f','m','m','m','f','m','f','f','f'],'c':np.random.randn(10)})
Which looks like：
看起来像：
a b c
0 1 m 0.495439
1 2 f 1.444694
2 3 m 0.150637
3 4 m -1.078252
4 5 m 0.618045
5 6 f -0.525368
6 7 m 0.188912
7 8 f 0.159014
8 9 f 0.536495
9 10 f 0.874598
When I want to select some rows, I run
当我想选择一些行时，我运行
data[:2] or data.ix[2]
But when I try:
但是当我尝试：
se = range(2)
data[se]
There's a error:
有一个错误：
KeyError: 'No column(s) named: [0 1]'
I know DataFrame select a col as default.What happened when I run data[se]?
How colon(:) works in python?
我知道 DataFrame 选择一个 col 作为默认值。运行时发生了什么data[se]？冒号(:) 在python 中是如何工作的？
回答by urban
I have never used Pandas but a good explanation of slicing ([::]notation in python can be found here. Now from what I read in the manual
我从未使用过 Pandas，但对切片有一个很好的解释（[::]python 中的符号可以在这里找到。现在从我在手册中读到的内容）
With DataFrame, slicing inside of [] slices the rows. This is provided largely as a convenience since it is such a common operation.
In [32]: df[:3] Out[32]: A B C D 2000-01-01 -0.282863 0.469112 -1.509059 -1.135632 2000-01-02 -0.173215 1.212112 0.119209 -1.044236 2000-01-03 -2.104569 -0.861849 -0.494929 1.071804 In [33]: df[::-1] Out[33]: A B C D 2000-01-08 -1.157892 -0.370647 -1.344312 0.844885 2000-01-07 0.577046 0.404705 -1.715002 -1.039268 2000-01-06 0.113648 -0.673690 -1.478427 0.524988 2000-01-05 0.567020 -0.424972 0.276232 -1.087401 2000-01-04 -0.706771 0.721555 -1.039575 0.271860 2000-01-03 -2.104569 -0.861849 -0.494929 1.071804 2000-01-02 -0.173215 1.212112 0.119209 -1.044236 2000-01-01 -0.282863 0.469112 -1.509059 -1.135632
使用 DataFrame，在 [] 内部切片会切片行。这主要是为了方便，因为它是一种常见的操作。
In [32]: df[:3] Out[32]: A B C D 2000-01-01 -0.282863 0.469112 -1.509059 -1.135632 2000-01-02 -0.173215 1.212112 0.119209 -1.044236 2000-01-03 -2.104569 -0.861849 -0.494929 1.071804 In [33]: df[::-1] Out[33]: A B C D 2000-01-08 -1.157892 -0.370647 -1.344312 0.844885 2000-01-07 0.577046 0.404705 -1.715002 -1.039268 2000-01-06 0.113648 -0.673690 -1.478427 0.524988 2000-01-05 0.567020 -0.424972 0.276232 -1.087401 2000-01-04 -0.706771 0.721555 -1.039575 0.271860 2000-01-03 -2.104569 -0.861849 -0.494929 1.071804 2000-01-02 -0.173215 1.212112 0.119209 -1.044236 2000-01-01 -0.282863 0.469112 -1.509059 -1.135632
In your example where you use range(2)that gives you [0, 1]as list. What I think you need is data[0:1]to slice the DataFrameand get rows 0 and 1 which is the same as data[:1]omitting the zero. If you wanted for example rows 3,4 and 5 that would be data[3:5].
在您使用的示例中，range(2)它为您[0, 1]提供了列表。我认为您需要的是data[0:1]切片DataFrame并获取第 0 行和第 1 行，这与data[:1]省略零相同。例如，如果您想要第 3,4 和 5 行，那就是data[3:5].
Additionally, looking at some examples in the manual you can use step, so:
此外，查看手册中的一些示例，您可以使用step，因此：
data[::2]gives you every 2nd rowdata[::-1]returns all the rows in reverse order- Combining ranges and step:
data[0:10:2]will result in rows 0,2,4,6,8 and 10
data[::2]给你每第二行data[::-1]以相反的顺序返回所有行- 组合范围和步长：
data[0:10:2]将导致第 0、2、4、6、8 和 10 行
Hope it helps
希望能帮助到你
回答by birdypme
The [start:limit:step] syntax is known as slicing. You can easily create an instance of a slice using the slice()function:
[start:limit:step] 语法称为切片。您可以使用slice()函数轻松创建切片的实例：
class slice(stop)
class slice(start, stop[, step])
Return a slice object representing the set of indices specified by range(start, stop, step). The start and step arguments default to None. Slice objects have read-only data attributes start, stop and step which merely return the argument values (or their default). They have no other explicit functionality; however they are used by Numerical Python and other third party extensions. Slice objects are also generated when extended indexing syntax is used. For example: a[start:stop:step] or a[start:stop, i]. See itertools.islice() for an alternate version that returns an iterator.
类切片（停止）
类切片（开始，停止[，步骤]）
返回一个切片对象，表示由 range(start, stop, step) 指定的索引集。start 和 step 参数默认为 None。Slice 对象具有只读数据属性 start、stop 和 step，它们仅返回参数值（或它们的默认值）。它们没有其他明确的功能；但是它们被 Numerical Python 和其他第三方扩展使用。使用扩展索引语法时也会生成切片对象。例如：a[start:stop:step] 或 a[start:stop, i]。有关返回迭代器的替代版本，请参阅 itertools.islice()。
In your case, you could write something like this to return the first 2 rows
在你的情况下，你可以写这样的东西来返回前 2 行
se = slice(None, 2)
data[se]
回答by Alexander
>>> data.ix[range(2)]
a b c
0 1 m -0.323834
1 2 f 0.159787
