What does [:, :] mean on NumPy arrays - Stack Overflow
numpy uses tuples as indexes. In this case, this is a detailed slice assignment. [0] #means line 0 of your matrix [(0,0)] #means cell at 0,0 of your matrix [0:1] #means lines 0 to 1 excluded of your matrix [:1] #excluding the first value means all lines until line 1 excluded [1:] #excluding the last param mean all lines starting form line 1 included [:] #excluding both means all lines [::2] # ...
In numpy, what does selection by [:,None] do? - Stack Overflow
Jun 16, 2016 · What I wanted to do is transpose the one dimensional numpy series/array which does not work with numpy.transpose([1, 2, 3]). So I wanted to add you can transpose like this ( source ): numpy.matrix([1, 2, 3]).T
python - Pretty-print a NumPy array without scientific notation …
How do I print formatted NumPy arrays in a way similar to this: x = 1.23456 print('%.3f' % x) If I want to print the numpy.ndarray of floats, it prints several decimals, often in 'scientific' form...
How do numpy's in-place operations (e.g. `+=`) work?
May 4, 2016 · import numpy as np a = np.arange(4) i = a > 0 i = array([False, True, True, True], dtype=bool) I understand that: a[i] = x is the same as a.__setitem__(i, x) , which assigns directly to the items indicated by i
How do I read CSV data into a record array in NumPy?
Aug 19, 2010 · @JoséL.Patiño The second part of the question deals with the request for a Numpy record array. The first part of the answer shows df.values which gives a Numpy representation of the DataFrame; a convenient method imho. –
Multiple conditions using 'or' in numpy array - Stack Overflow
numpy logical_and and logical_or are the ufuncs that you want (I think) Note that & is not logical and , it is bitwise and . This still works for you because (a>10) returns a logical array (e.g. 1's and 0's) as does your second condition.
add a comma between the elements of a numpy array
record arrays, recarrays, structured arrays... are a very common useage of numpy arrays. Numpy doesn't limit its dtype to one common type.
Most efficient way to map function over numpy array
Feb 5, 2016 · But first let's state the obvious: no matter how you map a Python-function onto a numpy-array, it stays a Python function, that means for every evaluation: numpy-array element must be converted to a Python-object (e.g. a Float).
NumPy: Comparing Elements in Two Arrays - Stack Overflow
Dec 7, 2010 · Numpy has a set function numpy.setmember1d() that works on sorted and uniqued arrays and returns exactly the boolean array that you want. If the input arrays don't match the criteria you'll need to convert to the set format and invert the transformation on the result.
Most efficient way to reverse a numpy array - Stack Overflow
Jul 21, 2011 · Believe it or not, after profiling my current code, the repetitive operation of numpy array reversion ate a giant chunk of the running time. What I have right now is the common view-based method: