Hello again, The best way so far that's come to my attention is to use:
numpy.ma.masked_object The problem with this is that it's looking for a specific instance of an object. So if the user had some elements of their array that were, for example, "randomString" , then it would not be picked up e.g. --- from numpy import * mixedArray=array([1,2, '', 3, 4, 'randomString'], dtype=object) mixedArrayMask = ma.masked_object(mixedArray, 'randomString').mask --- then mixedArrayMask will yield: array([ False, False, False, False, False, True]) Can anyone help me so that all strings are found in the array without having to explicitly loop through them in Python? Thanks, Darryl On Fri, Nov 6, 2009 at 3:56 PM, Darryl Wallace <darryl.wall...@prosensus.ca>wrote: > What I'm doing is importing some data from excel and sometimes there are > strings in the worksheet. Often times a user will use an empty cell or a > string to represent data that is missing. > > e.g. > from numpy import * > mixedArray=array([1, 2, '', 3, 4, 'String'], dtype=object) > > Two questions: > 1) Is there a quick way to find the elements in the array that are the > strings without iterating over each element in the array? > > or > > 2) Could I quickly turn it into a masked array of type float where all > string elements are set as missing points? > > I've been struggling with this for a while and can't come across a method > that will all me to do it without iterating over each element. > > Any help or pointers in the right direction would be greatly appreciated. > > Thanks, > Darryl > -- ______________________________________ Darryl Wallace: Project Leader ProSensus Inc. McMaster Innovation Park 175 Longwood Road South, Suite 301 Hamilton, Ontario, L8P 0A1 Canada (GMT -05:00) Tel: 1-905-528-9136 Fax: 1-905-546-1372 Web site: http://www.prosensus.ca/ ______________________________________
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