IndexError: too many indices. Numpy Array with 1 row and 2 columns

Question

When I try to get just the first element of an array like this

import numpy

a = numpy.array([1,2])

a[:,0]

I get this error

---------------------------------------------------------------------------
 IndexError                                Traceback (most recent call last)
<ipython-input-3-ed371621c46c> in <module>()
----> 1 a[:,0]

IndexError: too many indices

I would like to find a way to do this while still using slicing because the full code opens and reads many different files using numpy.loadtxt() all having two columns which vary from 1 to some N.

Community · Accepted Answer · 2017-05-23 12:17:48Z

11

Your array a = numpy.array([1,2]) only has one dimension: its shape is (2,). However, your slice a[:,0] specifies selections for two dimensions. This causes NumPy to raise the error.

To get the first element from a you only need to write a[0] (a selection for only one dimension is being made here).

Looking at your other question, if you want to ensure that the syntax a[:,0] always works, you could ensure that a always has two dimensions. When loading an array with np.loadtxt use the ndmin parameter, e.g.:

np.loadtxt(F, skiprows=0, ndmin=2)

edited May 23, 2017 at 12:17

CommunityBot

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answered Mar 22, 2015 at 20:43

Alex Riley

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4 Comments

Stripers247 Over a year ago

Thank you for your reply. The problem is that in the full code I have many files with varying column lengths so just getting the first element does not work.

Alex Riley Over a year ago

@Surfcast23: I see you've edited your question with some extra details, but I'm not quite sure what you're after. If your arrays only have one dimension (as in your example) a[i] will select the value at index i. For arrays with two dimensions (rows and columns), a[i,j]will select the value in the jth column from row i.

Stripers247 Over a year ago

Sorry if unclear, my question actually stems from a problem I was having that I asked in this question stackoverflow.com/questions/29191240/…

Alex Riley Over a year ago

@Surfcast23 - Ah, OK, I think I might understand - I've edited my answer with a suggestion (let me know if it's of any use to you or not).

rkp · Accepted Answer · 2015-03-22 21:21:06Z

6

As mentioned above, you have a one-dimensional array and you're trying to slice it with two dimensions.

One thing to add, and which I've found very useful in the past, is that numpy allows you easily cast a 1D array into a 2D array (either as a row or column):

>>> a = np.array([0,1,2])
>>> a.shape
(3,)
>>> a_row = a[None,:]
>>> a_row.shape
(1,3)
>>> a_col = a[:,None]
>>> a_col.shape
(3,1)

answered Mar 22, 2015 at 21:21

rkp

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Comments

Dave cook · Accepted Answer · 2017-03-22 18:31:56Z

1

I have also struggled with this problem when parsing many input files that can have 1-1000s of rows. However, I am using numpy genfromtxt which doesn't allow you to set 'ndmin', so the solution I came up with is to manually set the array shape equal 1 for arrays with 1 row:

>>> arr=np.genfromtxt('file',names=['a','b'],dtype='f4,f4') 
>>> if (np.size(arr) == 1): arr.shape=1

The 1 row array now acts like a 1-D array that can be indexed:

>>> for i in range(np.size(arr)): print arr['a'][i]

answered Mar 22, 2017 at 18:31

Dave cook

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