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How to use the 'sweep' function
...nd use in the operation defined by FUN.
For instance, if you want to add 1 to the 1st row, 2 to the 2nd, etc. of the matrix you defined, you will do:
sweep (M, 1, c(1: 4), "+")
I frankly did not understand the definition in the R documentation either, I just learned by looking up examples.
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Convert a row of a data frame to vector
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When you extract a single row from a data frame you get a one-row data frame. Convert it to a...
How does zip(*[iter(s)]*n) work in Python?
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iter() is an iterator over a sequence. [x] * n produces a list containing n quantity of x, i.e...
What is the fastest method for selecting descendant elements in jQuery?
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Method 1 and method 2 are identical with the only difference is that method 1 needs to parse the scope passed and translate it to a call to $parent.find(".child").show();.
Method 4 and Method 5 both need to parse the selector and ...
php中json_decode()和json_encode()的使用方法 - 更多技术 - 清泛网 - 专注C/C++及内核技术
php中json_decode()和json_encode()的使用方法1.json_decode()json_decode(PHP 5 >= 5.2.0, PECL json >= 1.2.0)json_decode — 对 JSON 格式的字符串进行编码说明mixed jso...1.json_decode()
(PHP 5 >= 5.2.0, PECL json >= 1.2.0)
对 JSON 格式的字符串进行编码
说明：
mix...
What is the difference between Ruby 1.8 and Ruby 1.9
I'm not clear on the differences between the "current" version of Ruby (1.8) and the "new" version (1.9). Is there an "easy" or a "simple" explanation of the differences and why it is so different?
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What does this square bracket and parenthesis bracket notation mean [first1,last1)?
I have seen number ranges represented as [first1,last1) and [first2,last2) .
4 Answers
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How do I find the duplicates in a list and create another list with them?
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Python creating a dictionary of lists
...s import defaultdict
>>> d = defaultdict(list)
>>> a = ['1', '2']
>>> for i in a:
... for j in range(int(i), int(i) + 2):
... d[j].append(i)
...
>>> d
defaultdict(<type 'list'>, {1: ['1'], 2: ['1', '2'], 3: ['2']})
>>> d.items()
[(1, ['1']), (...
Pandas dataframe get first row of each group
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>>> df.groupby('id').first()
value
id
1 first
2 first
3 first
4 second
5 first
6 first
7 fourth
If you need id as column:
>>> df.groupby('id').first().reset_index()
id value
0 1 first
1 2 first
2 3 first
3 4 seco...