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Common MySQL fields and their appropriate data types

... answered Dec 10 '08 at 0:57 da5idda5id 8,83288 gold badges3636 silver badges5050 bronze badges ...
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How to remove an element slowly with jQuery?

... answered Nov 27 '09 at 7:09 GregGreg 7,18077 gold badges3939 silver badges6464 bronze badges ...
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How to split a delimited string into an array in awk?

... Have you tried: echo "12|23|11" | awk '{split($0,a,"|"); print a[3],a[2],a[1]}' share | improve this answer | follow | ...
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How can I scale an image in a CSS sprite

... not all http://caniuse.com/#search=background-size) background-size : 150% 150%; Or You can use a combo of zoom for webkit/ie and transform:scale for Firefox(-moz-) and Opera(-o-) for cross-browser desktop & mobile [class^="icon-"]{ display: inline-block; background: url('../img/...
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Parse (split) a string in C++ using string delimiter (standard C++)

...>=tiger"; std::string delimiter = ">="; std::string token = s.substr(0, s.find(delimiter)); // token is "scott" The find(const string& str, size_t pos = 0) function returns the position of the first occurrence of str in the string, or npos if the string is not found. The substr(size_t p...
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PHP cURL vs file_get_contents

... answered Jun 16 '12 at 16:00 XeoncrossXeoncross 49k7070 gold badges234234 silver badges340340 bronze badges ...
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binning data in python with scipy/numpy

... easier to use numpy.digitize(): import numpy data = numpy.random.random(100) bins = numpy.linspace(0, 1, 10) digitized = numpy.digitize(data, bins) bin_means = [data[digitized == i].mean() for i in range(1, len(bins))] An alternative to this is to use numpy.histogram(): bin_means = (numpy.histo...
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Parsing command-line arguments in C?

... 190 To my knowledge, the three most popular ways how to parse command line arguments in C are: Get...
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Make Div overlay ENTIRE page (not just viewport)?

...nd why this is so hard to do... I've tried setting body, html heights to 100% etc but that isn't working. Here is what I have so far: ...
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Flatten nested dictionaries, compressing keys

...t(items) >>> flatten({'a': 1, 'c': {'a': 2, 'b': {'x': 5, 'y' : 10}}, 'd': [1, 2, 3]}) {'a': 1, 'c_a': 2, 'c_b_x': 5, 'd': [1, 2, 3], 'c_b_y': 10} share | improve this answer | ...