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Extract first item of each sublist

... You could use zip: >>> lst=[[1,2,3],[11,12,13],[21,22,23]] >>> zip(*lst)[0] (1, 11, 21) Or, Python 3 where zip does not produce a list: >>> list(zip(*lst))[0] (1, 11, 21) Or, >>> next(zip(*lst)) (1, 11, 21) Or, (my favorite) use numpy: ...
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Simple regular expression for a decimal with a precision of 2

... answered Nov 21 '08 at 7:32 DocMaxDocMax 11.3k44 gold badges3939 silver badges4040 bronze badges ...
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Numpy: Divide each row by a vector element

... | edited Nov 21 '19 at 16:13 answered Mar 21 '19 at 4:52 ...
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Using Razor, how do I render a Boolean to a JavaScript variable?

...lete the code. – taylorswiftfan Apr 21 at 19:11 add a comment  |  ...
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leading zeros in rails

... answered Apr 27 '11 at 21:02 Jon GauthierJon Gauthier 23k55 gold badges5959 silver badges6868 bronze badges ...
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What's the difference between “mod” and “remainder”?

... There is a difference between modulus and remainder. For example: -21 mod 4 is 3 because -21 + 4 x 6 is 3. But -21 divided by 4 gives -5 with a remainder of -1. For positive values, there is no difference. share ...
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Java recursive Fibonacci sequence

... = 3 fibonacci(5) = 3+2 = 5 And from fibonacci sequence 0,1,1,2,3,5,8,13,21.... we can see that for 5th element the fibonacci sequence returns 5. See here for Recursion Tutorial. share | improve ...
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How to find the installed pandas version

... None LANG: en_US.UTF-8 pandas: 0.15.2-113-g5531341 nose: 1.3.1 Cython: 0.21.1 numpy: 1.8.2 scipy: 0.14.0.dev-371b4ff statsmodels: 0.6.0.dev-a738b4f IPython: 2.0.0-dev sphinx: 1.2.2 patsy: 0.3.0 dateutil: 1.5 pytz: 2012c bottleneck: None tables: 3.1.1 numexpr: 2.2.2 matplotlib: 1.4.2 openpyxl: None...
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How to form tuple column from two columns in Pandas

... JungDale Jung 2,81011 gold badge1414 silver badges1212 bronze badges 3 ...
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How to access pandas groupby dataframe by key

... You can use the get_group method: In [21]: gb.get_group('foo') Out[21]: A B C 0 foo 1.624345 5 2 foo -0.528172 11 4 foo 0.865408 14 Note: This doesn't require creating an intermediary dictionary / copy of every subdataframe for every gr...