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Backporting Python 3 open(encoding=“utf-8”) to Python 2
I have a Python codebase, built for Python 3, which uses Python 3 style open() with encoding parameter:
6 Answers
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How does zip(*[iter(s)]*n) work in Python?
... arguments for a function call. Therefore you're passing the same iterator 3 times to zip(), and it pulls an item from the iterator each time.
x = iter([1,2,3,4,5,6,7,8,9])
print zip(x, x, x)
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Pandas dataframe get first row of each group
...;> 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 second
4 5 first
5 6...
Integrate ZXing in Android Studio
...
234
I was integrating ZXING into an Android application and there were no good sources for the inpu...
Python - abs vs fabs
...(-2))
Out[7]: int
In [8]: type(abs(-2.0))
Out[8]: float
In [9]: type(abs(3+4j))
Out[9]: float
In [10]: type(math.fabs(-2))
Out[10]: float
In [11]: type(math.fabs(-2.0))
Out[11]: float
In [12]: type(math.fabs(3+4j))
---------------------------------------------------------------------------
Type...
Can't install Ruby under Lion with RVM – GCC issues
...
553
This answer was edited multiple times and now contains several alternative solutions. Try the...
Remove empty elements from an array in Javascript
... to remove null or undefined values:
var array = [0, 1, null, 2, "", 3, undefined, 3,,,,,, 4,, 4,, 5,, 6,,,,];
var filtered = array.filter(function (el) {
return el != null;
});
console.log(filtered);
It will depend on what you consider to be "empty" for example, if you were d...
Accessing last x characters of a string in Bash
I found out that with ${string:0:3} one can access the first 3 characters of a string. Is there a equivalently easy method to access the last three characters?
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How can I obtain the element-wise logical NOT of a pandas Series?
... True, False, True])
In [8]: ~s
Out[8]:
0 False
1 False
2 True
3 False
dtype: bool
Using Python2.7, NumPy 1.8.0, Pandas 0.13.1:
In [119]: s = pd.Series([True, True, False, True]*10000)
In [10]: %timeit np.invert(s)
10000 loops, best of 3: 91.8 µs per loop
In [11]: %timeit ~s
10...