大约有 46,000 项符合查询结果（耗时：0.0401秒） [XML]
Convert list of dictionaries to a pandas DataFrame
I have a list of dictionaries like this:
7 Answers
7
...
Which is faster: while(1) or while(2)?
This was an interview question asked by a senior manager.
23 Answers
23
...
Is there a difference between YES/NO,TRUE/FALSE and true/false in objective-c?
Simple question really; is there a difference between these values (and is there a difference between BOOL and bool)? A co-worker mentioned that they evaluate to different things in Objective-C, but when I looked at the typedefs in their respective .h files, YES/TRUE/true were all defined as 1 an...
Unicode equivalents for \w and \b in Java regular expressions?
Many modern regex implementations interpret the \w character class shorthand as "any letter, digit, or connecting punctuation" (usually: underscore). That way, a regex like \w+ matches words like hello , élève , GOÄ_432 or gefräßig .
...
How to check if a value exists in a dictionary (python)
I have the following dictionary in python:
6 Answers
6
...
How to create custom easing function with Core Animation?
I am animating a CALayer along a CGPath (QuadCurve) quite nicely in iOS. But I'd like to use a more interesting easing function than the few provided by Apple (EaseIn/EaseOut etc). For instance, a bounce or elastic function.
...
Equivalent of String.format in jQuery
I'm trying to move some JavaScript code from MicrosoftAjax to JQuery. I use the JavaScript equivalents in MicrosoftAjax of the popular .net methods, e.g. String.format(), String.startsWith(), etc. Are there equivalents to them in jQuery?
...
Suppress Scientific Notation in Numpy When Creating Array From Nested List
I have a nested Python list that looks like the following:
4 Answers
4
...
Fast stable sorting algorithm implementation in javascript
I'm looking to sort an array of about 200-300 objects, sorting on a specific key and a given order (asc/desc). The order of results must be consistent and stable.
...
Multiple aggregations of the same column using pandas GroupBy.agg()
Is there a pandas built-in way to apply two different aggregating functions f1, f2 to the same column df["returns"] , without having to call agg() multiple times?
...