nan

I have a problem with making a histogram when some of my data contains "not a number" values. I can get rid of the error by using nan_to_num from numpy, but than i get a lot of zero values which mess up the histogram as well. pylab.figure() pylab.hist(numpy.nan_to_num(A)) pylab.show() So the idea would be to make another array in which all the nan values are gone, or to just mask them in the histogram in some way (preferrably with some builtin method). Remove np.nan values from your array using A[~np.isnan(A)] , this will select all entries in A which values are not nan , so they will be

Python 2.7.3 (default, Aug 1 2012, 05:14:39) [GCC 4.6.3] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> x = float('nan') >>> id(x) == id(x) True >>> x == x False I'm interested in how nan != nan in python. And just to clarify, I know nan is supposed to behave like that by definition, I'm asking about how not about why. Where is that implemented? Is there any other object which behaves like that? For the "where" part of your questions, look starting at line 391 in Objects/floatobject.c in the Python 2.7.3 source tree. A brief discussion is given about the

I want to get the index of the min value of a numpy array that contains NaNs and I want them ignored >>> a = array([ nan, 2.5, 3., nan, 4., 5.]) >>> a array([ NaN, 2.5, 3. , NaN, 4. , 5. ]) if I run argmin, it returns the index of the first NaN >>> a.argmin() 0 I substitute NaNs with Infs and then run argmin >>> a[isnan(a)] = Inf >>> a array([ Inf, 2.5, 3. , Inf, 4. , 5. ]) >>> a.argmin() 1 My dilemma is the following: I'd rather not change NaNs to Infs and then back after I'm done with argmin (since NaNs have a meaning later on in the code). Is there a better way to do this? There is also a

I'm having a difficult time to debug a problem in which the float nan in a list and nan in a numpy.array are handled differently when these are used in itertools.groupby : Given the following list and array: from itertools import groupby import numpy as np lst = [np.nan, np.nan, np.nan, 0.16, 1, 0.16, 0.9999, 0.0001, 0.16, 0.101, np.nan, 0.16] arr = np.array(lst) When I iterate over the list the contiguous nan s are grouped: >>> for key, group in groupby(lst): ... if np.isnan(key): ... print(key, list(group), type(key)) nan [nan, nan, nan] <class 'float'> nan [nan] <class 'float'> However if I

How can we use them in our codes, and what will cause NaN(not a number)? Cameron This may be a good reference if you want to learn more about floating point numbers in Java. Positive Infinity is a positive number so large that it can't be represented normally. Negative Infinity is a negative number so large that it cannot be represented normally. NaN means "Not a Number" and results from a mathematical operation that doesn't yield a number- like dividing 0 by 0. In Java, the Double and Float classes both have constants to represent all three cases. They are POSITIVE_INFINITY, NEGATIVE_INFINITY

I just started to learn HTML5 and was going through HTML5 Audio player using JQuery. I coded a player with Playlist, everything works fine except the Duration with help of which my input range slider doesn't works. When I debugged I found that my duration is showing me NAN. I am setting the duration after the song is initialized. Here is my JS code jQuery(document).ready(function() { container = $('.container'); playList = $('#playlist'); playListSong = $('#playlist li'); cover = $('.cover'); play = $('#play'); pause = $('#pause'); mute = $('#mute'); muted = $('#muted'); close = $('#close');