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Get: TypeError: 'dict_values' object does not support indexing when using python 3.2.3 [duplicate]
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In Python 3, dict.values() (along with dict.keys() and dict.items()) returns a view, rather than a list. See the documentation here. You therefore need to wrap your call to dict.values() in a call to list like so:
v = list(d.va...
两大桌面系统之战：Yosemite vs Windows 10 - 操作系统(内核) - 清泛网 - ...
...加方便了。
Windows 10 中 Metro 应用设计主要是针对平板电脑启动全屏，不过它不会覆盖底部的任务，也有标题栏。有些可以调整大小尺寸，有些则是固定的。标题栏左边增加一个新按钮，方便用户快速访问 Windows 8 Charms ...
Python Graph Library [closed]
I'm writing a python application that will make heavy use of a graph data structure. Nothing horribly complex, but I'm thinking some sort of graph/graph-algorithms library would help me out. I've googled around, but I don't find anything that particularly leaps out at me.
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Drop all duplicate rows across multiple columns in Python Pandas
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Not the answer you're looking for? Browse other questions tagged python pandas duplicates drop-duplicates or ask your own question.
What is the syntax to insert one list into another list in python?
..., 2, 3, [4, 5, 6]]
foo.extend(bar) --> [1, 2, 3, 4, 5, 6]
http://docs.python.org/tutorial/datastructures.html
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Python: Tuples/dictionaries as keys, select, sort
...e strawberries and so on.
I'd like to organize them in a data structure in Python that allows for easy selection and sorting. My idea was to put them into a dictionary with tuples as keys, e.g.,
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What does the “at” (@) symbol do in Python?
I'm looking at some Python code which used the @ symbol, but I have no idea what it does. I also do not know what to search for as searching Python docs or Google does not return relevant results when the @ symbol is included.
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Accessing class variables from a list comprehension in the class definition
... a list comprehension within the class definition? The following works in Python 2 but fails in Python 3:
5 Answers
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Numpy - add row to array
... before, in the latest version which I am using is numpy version 1.13, and python3, I am doing the same thing with adding a row to a matrix, remember to put a double bracket to the second argument, otherwise, it will raise dimension error.
In here I am adding on matrix A
1 2 3
4 5 6
with a row ...
Are list-comprehensions and functional functions faster than “for loops”?
In terms of performance in Python, is a list-comprehension, or functions like map() , filter() and reduce() faster than a for loop? Why, technically, they run in a C speed , while the for loop runs in the python virtual machine speed ?.
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