I am new to both python and numpy.I ran a code that I wrote and I am getting this message:"index 0 is out of bounds for axis 0 with size 0"Without the context, I just want to figure out what this means.. It might be silly to ask this but what do they mean by axis 0 and size 0? index 0 means the first value in the array.. but I can"t figure out what axis 0 and size 0 mean.

The "data" is a text file with lots of numbers in two columns.

x = np.linspace(1735.0,1775.0,100)column1 = (data<0,0:-1>+data<0,1:>)/2.0column2 = data<1,1:>x_column1 = np.zeros(x.size+2)x_column1<1:-1> = xx_column1<0> = x<0>+x<0>-x<1>x_column1<-1> = x<-1>+x<-1>-x<-2>experiment = np.zeros_like(x)for i in range(np.size(x_edges)-2): indexes = np.flatnonzero(np.logical_and((column1>=x_column1),(column1
python numpy indexing error-handling index-error
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edited Feb 8 "19 at 22:17


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asked Jan 5 "17 at 18:37

Seoyeon HongSeoyeon Hong
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In numpy, index and dimension numbering starts with 0. So axis 0 means the 1st dimension. Also in numpy a dimension can have length (size) 0. The simplest case is:

In <435>: x = np.zeros((0,), int)In <436>: xOut<436>: array(<>, dtype=int32)In <437>: x<0>...IndexError: index 0 is out of bounds for axis 0 with size 0I also get it if x = np.zeros((0,5), int), a 2d array with 0 rows, and 5 columns.

You are watching: Indexerror: index 0 is out of bounds for axis 0 with size 0

So someplace in your code you are creating an array with a size 0 first axis.

When asking about errors, it is expected that you tell us where the error occurs.

Also when debugging problems like this, the first thing you should do is print the shape (and maybe the dtype) of the suspected variables.

Applied to pandas

The same error can occur for those using pandas, when sending a Series or DataFrame to a numpy.array, as with the following:

Resolving the error:

Use a try-except blockVerify the size of the array is not 0if x.size != 0:
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edited Jan 12 at 0:41

Trenton McKinney
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answered Jan 5 "17 at 19:02

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This is an IndexError in python, which means that we"re trying to access an index which isn"t there in the tensor. Below is a very simple example to understand this error.

See more: Execution Failed Due To Configuration Error: Invalid Permissions On Lambda Function

# create an empty array of dimension `0`In <14>: arr = np.array(<>, dtype=np.int64) # check its shape In <15>: arr.shape Out<15>: (0,)with this array arr in place, if we now try to assign any value to some index, for example to the index 0 as in the case below

In <16>: arr<0> = 23 Then, we will get an IndexError, as below:

IndexError Traceback (most recent call last) in ----> 1 arr<0> = 23IndexError: index 0 is out of bounds for axis 0 with size 0The reason is that we are trying to access an index (here at 0th position), which is not there (i.e. it doesn"t exist because we have an array of size 0).

In <19>: arr.size * arr.itemsize Out<19>: 0So, in essence, such an array is useless and cannot be used for storing anything. Thus, in your code, you"ve to follow the traceback and look for the place where you"re creating an array/tensor of size 0 and fix that.