我的代码:
import nltk.data
tokenizer = nltk.data.load('nltk:tokenizers/punkt/english.pickle')
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错误信息:
[ec2-user@ip-172-31-31-31 sentiment]$ python mapper_local_v1.0.py
Traceback (most recent call last):
File "mapper_local_v1.0.py", line 16, in <module>
tokenizer = nltk.data.load('nltk:tokenizers/punkt/english.pickle')
File "/usr/lib/python2.6/site-packages/nltk/data.py", line 774, in load
opened_resource = _open(resource_url)
File "/usr/lib/python2.6/site-packages/nltk/data.py", line 888, in _open
return find(path_, path + ['']).open()
File "/usr/lib/python2.6/site-packages/nltk/data.py", line 618, in find
raise LookupError(resource_not_found)
LookupError:
Resource u'tokenizers/punkt/english.pickle' not found. Please
use the NLTK Downloader to obtain the resource:
>>>nltk.download()
Searched in:
- '/home/ec2-user/nltk_data'
- '/usr/share/nltk_data'
- '/usr/local/share/nltk_data'
- '/usr/lib/nltk_data'
- '/usr/local/lib/nltk_data' …Run Code Online (Sandbox Code Playgroud) 如何使用按位运算验证数字n是否可整除x?
我在这方面找到了很多相关链接,但我不清楚它们,因为它们不在 Python 中。例如,如果我想验证是否81可以被3,9或整除4怎么办?
我想使用按位运算,我想了解如何使用 Python 实现这一点。
我有以下示例代码.我有一个有16行的数据帧ts.当我用实际数字进行子集时,它工作正常但是当我用计算数字进行子集时,为什么我的代码表现得很奇怪?
有人可以解释一下这有什么不对吗?
情况1:
> a
[1] 12
> c
[1] 16
> ts$trend[13:16]
[1] 21.36926 21.48654 21.60383 21.72111
> ts$trend[a+1:c]
[1] 21.36926 21.48654 21.60383 21.72111 NA NA NA NA NA NA NA NA
[13] NA NA NA NA
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案例2:
> b
[1] 4
> temp[1: 8]
[1] 1 2 3 4 5 6 7 8
> temp[1: b+b]
[1] 5 6 7 8
Run Code Online (Sandbox Code Playgroud) 我pandas.pivot_table在 Pandas 数据帧上使用了该函数,我的输出看起来与此类似:
Winners Runnerup
year 2016 2015 2014 2016 2015 2014
Country Sport
india badminton
india wrestling
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我真正需要的是像下面这样的东西
Country Sport Winners_2016 Winners_2015 Winners_2014 Runnerup_2016 Runnerup_2015 Runnerup_2014
india badminton 1 1 1 1 1 1
india wrestling 1 0 1 0 1 0
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我有很多列和年份,所以我无法手动编辑它们,所以有人可以告诉我如何做到这一点吗?
python ×3
dataframe ×2
data-munging ×1
nltk ×1
pandas ×1
pivot-table ×1
r ×1
subset ×1
unix ×1