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Immutable vs Mutable types
... know the float object is considered to be immutable, with this type of example from my book:
16 Answers
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Efficient evaluation of a function at every cell of a NumPy array
...irectly to a Numpy array each time you need it:
import numpy as np
def f(x):
return x * x + 3 * x - 2 if x > 0 else x * 5 + 8
f = np.vectorize(f) # or use a different name if you want to keep the original f
result_array = f(A) # if A is your Numpy array
It's probably better to specify...
Test for equality among all elements of a single vector
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I use this method, which compares the min and the max, after dividing by the mean:
# Determine if range of vector is FP 0.
zero_range <- function(x, tol = .Machine$double.eps ^ 0.5) {
if (length(x) == 1) return(TRUE)
x <- range(x) / mean(x)
isTRUE(all.equal(x[1], ...
Does a favicon have to be 32x32 or 16x16?
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Update for 2020: Sticking to the original question of 16x16 versus 32x32 icons: the current recommendation should be to provide a 32x32 icon, skipping 16x16 entirely. All current browsers and devices support 32x32 icons. The icon will routinely be upscaled to as much as 192x192 de...
E731 do not assign a lambda expression, use a def
I get this pep8 warning whenever I use lambda expressions. Are lambda expressions not recommended? If not why?
4 Answers
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How to add a border just on the top side of a UIView
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Bad value X-UA-Compatible for attribute http-equiv on element meta
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Either X-UA-Compatible is not "standard" HTML (FSVO "standard" that involves appearing on a publicly editable wiki page referenced by the specification) or the Validator isn't up to date with the current status of that wiki.
At the...
When is “i += x” different from “i = i + x” in Python?
... depends entirely on the object i.
+= calls the __iadd__ method (if it exists -- falling back on __add__ if it doesn't exist) whereas + calls the __add__ method1 or the __radd__ method in a few cases2.
From an API perspective, __iadd__ is supposed to be used for modifying mutable objects in pl...
Fast check for NaN in NumPy
...astest way to check for the occurrence of NaN ( np.nan ) in a NumPy array X . np.isnan(X) is out of the question, since it builds a boolean array of shape X.shape , which is potentially gigantic.
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Selecting only numeric columns from a data frame
...e is a list we can use the list-apply functions:
nums <- unlist(lapply(x, is.numeric))
Then standard subsetting
x[ , nums]
## don't use sapply, even though it's less code
## nums <- sapply(x, is.numeric)
For a more idiomatic modern R I'd now recommend
x[ , purrr::map_lgl(x, is.numer...