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Is there an equivalent of 'which' on the Windows command line?
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Windows Server 2003 and later (i.e. anything after Windows XP 32 bit) provide the where.exe program which does some of what which does, though it matches all types of files, not just executable commands. (It does not match built-in shell co...
Replace all elements of Python NumPy Array that are greater than some value
...o replace all values in it greater than or equal to a threshold T with 255.0. To my knowledge, the most fundamental way would be:
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Default value to a parameter while passing by reference in C++
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104
You can do it for a const reference, but not for a non-const one. This is because C++ does not ...
Remove empty elements from an array in Javascript
...xample, if you want 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 exa...
Unicode equivalents for \w and \b in Java regular expressions?
...s Regex Unicode Problems
The problem with Java regexes is that the Perl 1.0 charclass escapes — meaning \w, \b, \s, \d and their complements — are not in Java extended to work with Unicode. Alone amongst these, \b enjoys certain extended semantics, but these map neither to \w, nor to Unicode i...
How to check if a value exists in a dictionary (python)
...rative timing:
>>> T(lambda : 'one' in d.itervalues()).repeat()
[0.28107285499572754, 0.29107213020324707, 0.27941107749938965]
>>> T(lambda : 'one' in d.values()).repeat()
[0.38303399085998535, 0.37257885932922363, 0.37096405029296875]
>>> T(lambda : 'one' in d.viewvalue...
Equivalent of String.format in jQuery
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20 Answers
20
Active
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Conditional Replace Pandas
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.ix indexer works okay for pandas version prior to 0.20.0, but since pandas 0.20.0, the .ix indexer is deprecated, so you should avoid using it. Instead, you can use .loc or iloc indexers. You can solve this problem by:
mask = df.my_channel > 20000
column_name = 'my_chann...
Multiple aggregations of the same column using pandas GroupBy.agg()
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You can simply pass the functions as a list:
In [20]: df.groupby("dummy").agg({"returns": [np.mean, np.sum]})
Out[20]:
mean sum
dummy
1 0.036901 0.369012
or as a dictionary:
In [21]: df.groupby('dummy').agg({'returns':
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