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Apply a function to every row of a matrix or a data frame
..., byrow=TRUE)
R> M
[,1] [,2]
[1,] 1 2
[2,] 3 4
[3,] 5 6
R> apply(M, 1, function(x) 2*x[1]+x[2])
[1] 4 10 16
R>
This takes a matrix and applies a (silly) function to each row. You pass extra arguments to the function as fourth, fifth, ... arguments to apply().
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python pandas remove duplicate columns
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Jean-François Corbett
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answered Nov 5 '16 at 6:15
Gene BurinskyGene ...
Creating a zero-filled pandas data frame
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edited Feb 9 '16 at 5:16
answered Apr 9 '14 at 13:49
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Interpolating a string into a regex
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answered Sep 29 '08 at 18:53
Jonathan LonowskiJonathan Lonowski
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What's the (hidden) cost of Scala's lazy val?
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answered Jun 15 '10 at 7:51
oxbow_lakesoxbow_lakes
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100% width Twitter Bootstrap 3 template
...p://themeforest.net/item/geometry-design-for-geolocation-social-networkr/4752268
5 Answers
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deleting rows in numpy array
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157
The simplest way to delete rows and columns from arrays is the numpy.delete method.
Suppose I ...
How to convert list of tuples to multiple lists?
...n zip() will almost do what you want:
>>> zip(*[(1, 2), (3, 4), (5, 6)])
[(1, 3, 5), (2, 4, 6)]
The only difference is that you get tuples instead of lists. You can convert them to lists using
map(list, zip(*[(1, 2), (3, 4), (5, 6)]))
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How can I sort a dictionary by key?
What would be a nice way to go from {2:3, 1:89, 4:5, 3:0} to {1:89, 2:3, 3:0, 4:5} ?
I checked some posts but they all use the "sorted" operator that returns tuples.
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Sorting arrays in NumPy by column
...turn a copy:
In [1]: import numpy as np
In [2]: a = np.array([[1,2,3],[4,5,6],[0,0,1]])
In [3]: np.sort(a.view('i8,i8,i8'), order=['f1'], axis=0).view(np.int)
Out[3]:
array([[0, 0, 1],
[1, 2, 3],
[4, 5, 6]])
To sort it in-place:
In [6]: a.view('i8,i8,i8').sort(order=['f1'], axis...