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Is MATLAB OOP slow or am I doing something wrong?
...t; call_nops
Computer: PCWIN Release: 2009b
Calling each function/method 100000 times
nop() function: 0.02261 sec 0.23 usec per call
nop1-5() functions: 0.02182 sec 0.22 usec per call
nop() subfunction: 0.02244 sec 0.22 usec per call
@()[] anonymous f...
Is it better to call ToList() or ToArray() in LINQ queries?
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16 Answers
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Why does ++[[]][+[]]+[+[]] return the string “10”?
This is valid and returns the string "10" in JavaScript ( more examples here ):
9 Answers
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Determine the data types of a data frame's columns
...se ?str(). To explore some examples, let's make some data:
set.seed(3221) # this makes the example exactly reproducible
my.data <- data.frame(y=rnorm(5),
x1=c(1:5),
x2=c(TRUE, TRUE, FALSE, FALSE, FALSE),
X3=letters[1:5])
@...
Getting individual colors from a color map in matplotlib
...lib.cm.get_cmap('Spectral')
rgba = cmap(0.5)
print(rgba) # (0.99807766255210428, 0.99923106502084169, 0.74602077638401709, 1.0)
For values outside of the range [0.0, 1.0] it will return the under and over colour (respectively). This, by default, is the minimum and maximum colour within the range ...
What is the bower (and npm) version syntax?
...example: to indicate you'll take any subsequent patch-level changes on the 1.2.x tree, starting with 1.2.0, but less than 1.3.0, you could use:
"angular": "~1.2"
or:
"angular": "~1.2.0"
This also gets you the same results as using the .x syntax:
"angular": "1.2.x"
But, you can use the tilde...
Replace all 0 values to NA
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Replacing all zeroes to NA:
df[df == 0] <- NA
Explanation
1. It is not NULL what you should want to replace zeroes with. As it says in ?'NULL',
NULL represents the null object in R
which is unique and, I guess, can be seen as the most uninformative and empty object.1 Then it b...
浅析为什么char类型的范围是 -128~+127 - C/C++ - 清泛网 - 专注C/C++及内核技术
浅析为什么char类型的范围是 -128~+127在C语言中, signed char 类型的范围为-128~127,每本教科书上也这么写,但是没有哪一本书上(包括老师)也不会给你为什么是-128~127,这...在C语言中, signed char 类型的范围为-128~127,每本教科书上...
Pandas index column title or name
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In [8]: df.index.name = 'foo'
In [9]: df.index.name
Out[9]: 'foo'
In [10]: df
Out[10]:
Column 1
foo
Apples 1
Oranges 2
Puppies 3
Ducks 4
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