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PostgreSQL, checking date relative to “today”

... answered Oct 13 '10 at 22:37 Paul TomblinPaul Tomblin 162k5555 gold badges299299 silver badges392392 bronze badges ...
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Deserializing JSON Object Array with Json.net

... | edited Jan 30 '15 at 20:55 James Newton-King 42.9k2222 gold badges105105 silver badges127127 bronze badges ...
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How to make an immutable object in Python?

..."b"]) It does not solve the problem that attributes can be accessed via [0] etc., but at least it's considerably shorter and provides the additional advantage of being compatible with pickle and copy. namedtuple creates a type similar to what I described in this answer, i.e. derived from tuple an...
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MySQL: how to get the difference between two timestamps in seconds

...and the TIME_TO_SEC() functions as follows: SELECT TIME_TO_SEC(TIMEDIFF('2010-08-20 12:01:00', '2010-08-20 12:00:00')) diff; +------+ | diff | +------+ | 60 | +------+ 1 row in set (0.00 sec) You could also use the UNIX_TIMESTAMP() function as @Amber suggested in an other answer: SELECT UNIX_T...
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Show AlertDialog in any position of the screen

... +50 After searching in various post I have found the solution. The code is posted below: private CharSequence[] items = {"Set as Rington...
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How do I specify a single test in a file with nosetests?

... answered Jul 2 '12 at 0:58 WillWill 4,09711 gold badge1818 silver badges1919 bronze badges ...
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runOnUiThread in fragment

... | edited Apr 10 '18 at 17:36 answered May 7 '13 at 17:35 ...
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Assigning a variable NaN in python without numpy

... 170 Yes -- use math.nan. >>> from math import nan >>> print(nan) nan >>>...
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twitter bootstrap autocomplete dropdown / combobox with Knockoutjs

... | edited Oct 10 '17 at 7:53 Alex Polo 322 bronze badges answered Oct 16 '12 at 12:31 ...
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how do you filter pandas dataframes by multiple columns

...sub-statements with (): males = df[(df[Gender]=='Male') & (df[Year]==2014)] To store your dataframes in a dict using a for loop: from collections import defaultdict dic={} for g in ['male', 'female']: dic[g]=defaultdict(dict) for y in [2013, 2014]: dic[g][y]=df[(df[Gender]==g) & ...