Index 0 is out of bounds for axis 0 with size 0 ошибка

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:])/2.0
column2 = data[1,1:]
x_column1 = np.zeros(x.size+2)
x_column1[1:-1] = x
x_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[i]),(column1<x_column1[i+1])))
    temp_column2 = column2[indexes]
    temp_column2[0] -= column2[indexes[0]]*(x_column1[i]-column1[indexes[0]-1])/(column1[indexes[0]]-column1[indexes[0]-1])
    temp_column2[-1] -= column2[indexes[-1]]*(column1[indexes[-1]+1]-x_column1[i+1])/(column1[indexes[-1]+1]-column1[indexes[-1]])
    experiment[i] = np.sum(temp_column2)   
return experiment

user513951

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asked Jan 5, 2017 at 18:37

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]: x
Out[436]: array([], dtype=int32)
In [437]: x[0]
...
IndexError: index 0 is out of bounds for axis 0 with size 0

I also get it if x = np.zeros((0,5), int), a 2d array with 0 rows, and 5 columns.

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:
- pandas.Series.values or pandas.Series.to_numpy() or pandas.Series.array
- pandas.DataFrame.values or pandas.DataFrame.to_numpy()

Resolving the error:

Use a try-except block
Verify the size of the array is not 0
- if x.size != 0:

answered Jan 5, 2017 at 19:02

hpauljhpaulj

219k14 gold badges228 silver badges350 bronze badges

Essentially it means you don’t have the index you are trying to reference. For example:

df = pd.DataFrame()
df['this']=np.nan
df['my']=np.nan
df['data']=np.nan
df['data'][0]=5 #I haven't yet assigned how long df[data] should be!
print(df)

will give me the error you are referring to, because I haven’t told Pandas how long my dataframe is. Whereas if I do the exact same code but I DO assign an index length, I don’t get an error:

df = pd.DataFrame(index=[0,1,2,3,4])
df['this']=np.nan
df['is']=np.nan
df['my']=np.nan
df['data']=np.nan
df['data'][0]=5 #since I've properly labelled my index, I don't run into this problem!
print(df)

Hope that answers your question!

answered Apr 27, 2018 at 21:29

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.

# 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)
<ipython-input-16-0891244a3c59> in <module>
----> 1 arr[0] = 23

IndexError: index 0 is out of bounds for axis 0 with size 0

The reason is that we are trying to access an index (here at 0^th 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]: 0

So, 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.

answered Jan 12, 2020 at 0:37

kmario23kmario23

56.6k13 gold badges158 silver badges150 bronze badges

I encountered this error and found that it was my data type causing the error.
The type was an object, after converting it to an int or float the issue was solved.

I used the following code:

df = df.astype({"column": new_data_type,
                "example": float})

answered Nov 18, 2022 at 9:23

Источник

IndexError: index 0 is out of bounds for axis 0 with size 0 error often appears when we work with NumPy in Python. To avoid this error is very simple. With a few lines of code, we will never face it again. Let’s find out the root cause and how to avoid it.

Why does the “IndexError: index 0 is out of bounds for axis 0 with size 0” error occur?

This error appears when we try to get the first element of an array with size = 0.

Like this:

import numpy as np

# Create an array
holidays = np.array([])

print(holidays[0]) # Error because there's no element in holidays

Run the code sample we get an error message like this:

IndexError: index 0 is out of bounds for axis 0 with size 0

If we access the 3rd element of an array with only two elements, we will also get the same error.

import numpy as np

# Create an array
holidays = np.array([1, 2])

print(holidays[2]) # Error because there's no element at index 2 in holidays

Error message:

IndexError: index 2 is out of bounds for axis 0 with size 2

Or when we access the first element of a multi-dimensional array with no element in the rows (axis 0).

import numpy as np

# Create a multi-dimensional array
holidays = np.zeros((0, 2), dtype=int)

print(holidays[0]) # Error because there's nothing in the row

Error message:

IndexError: index 0 is out of bounds for axis 0 with size 0

Fixing this problem is very simple. Just ensure the array is not empty before accessing its index 0.

Method 1: Use the if-else statement and array size

Array size syntax:

array.size

Description:

The array.size gets the number of elements in an array.

After getting the number of elements of the array, we need to use the if-else statement to check before using the array.

import numpy as np

holidays = np.array([])

if holidays.size > 0:
  	print(holidays[0])
else:
  	print("List of holidays is empty")

And now we see “List of holidays is empty” instead of an error message.

Output:

List of holidays is empty

Method 2: Use try-except block

Syntax:

try:
    # Do something
except:
    # Handle the exception

Description:

This is the way to handle errors in many programming languages.

Using try-except, our application will not stop and will not generate the error message: IndexError: index 0 is out of bounds for axis 0 with size 0.

import numpy as np

holidays = np.array([])

try:
  	print(holidays[0])
except IndexError:
  	print("List of holidays is empty")

Output:

List of holidays is empty

Method 3: Use Array shape

Syntax:

array.shape

Description:

The shape property gets the shape of an array in NumPy. It returns a tuple with the first element containing the number of elements of the row and the second element containing the number of elements of the column.

We use shape property to check if the element we access is valid in the array or not.

import numpy as np

holidays = np.zeros((0, 5), dtype=int)

if holidays.shape[0]:
    print(holidays[0])
else:
    print("There is no element in the row")

Output:

There is no element in the row

Summary

As I said before, with just a few simple lines of code, you can avoid the IndexError: index 0 is out of bounds for axis 0 with size 0. So, from now on, you will not have to face that annoying message again. Thank you for reading!

Maybe you are interested:

“IndexError: Only integers, slices (`:`), ellipsis (`…`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices”
IndexError: too many indices for array in Python
JSONDecodeError: Expecting value: line 1 column 1 (char 0)

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Источник

Are you worried 😟 about getting the “IndexError: Index is Out of Bounds for Axis 0 With Size 0” error or similar errors in Python?

When you attempt to access the first item in the first axis of an empty NumPy array, the Python error IndexError: index 0 is out of bounds for axis 0 with size 0 appears. This error occurs when a list item is attempted to be accessed at an out-of-bounds index.

Python lists have a range of [0, n-1], where n is the total number of entries in the list. An error is raised if an attempt is made to access an item at an index outside of this range.

In this article, we’ll learn how to fix the Python error “IndexError: index is out of limits for axis 0″ using the size and discuss the 3 different solutions that you can use to solve this error, including the size or shape functions or a try-except block.

What is The IndexError: Index is Out of Bounds For Axis 0 With Size?
How to Fix the “IndexError: Index is Out of Bounds For Axis 0 With Size” Error?
1. Adjust The Size of an Array
2. Adjust The Shape of an Array
3. Use Exception Handling

To understand and fix the error, let’s look at an example demonstrating the error.

Code

# error program --> IndexError: index is out of bounds for axis 0 with size

import numpy as np

array = np.array([])

print(array[0])

Output

Index is out of bounds for axis 0 with size

You may print the array’s form using the shape property or its size using the size property (the number of elements in the array). The issue was caused by your attempt to retrieve the first element of an empty array. Numpy utilizes a zero-based indexing system, where the index of the first member in an array is 0.

How to Fix the “IndexError: Index is Out of Bounds For Axis 0 With Size” Error?

In Python, we have different approaches to solve the error Index is out of bound for axis 0 with size. Some of the approaches to fix this error are given below:

Adjust the size of an array
Adjust the shape of an array
Use exception handling

1. Adjust The Size of an Array

One technique to fix the error is checking whether the array’s size is larger than 0 before accessing its first item. If the array size is larger than 0, just then if block is executed; otherwise, the else block should be executed. An array’s axis 0 is its initial dimension, and its size property may be used to determine how many items are there in the array.

Code

import numpy as np

array = np.array([])

if array.size > 0:

    print(array[0])

else:

    print('Array size is 0.')

Output

Array size is 0.

2. Adjust The Shape of an Array

Code

import numpy as np

array = np.zeros((0, 1), dtype=int)

print(array.shape)

Output

(0, 1)

The array above has a size 0 for its first dimension, so trying to access any element at the index would cause an IndexError.

3. Use Exception Handling

Using a try statement, exceptions may be managed in Python. The try statement contains the main operation that can cause an exception. The except clause contains the code that manages exceptions. Thus, we may decide what steps are needed after we have identified the exception. Let’s see the example below 👇:

Code

import numpy as np

array = np.array([])



try:

    print(array[0])

except IndexError:

    print('There is no item in the array at index 0')

Output

There is no item in the array at index 0

As an alternative, you can handle the problem with a try-except sentence. When we attempted to retrieve the array element at index 0, an IndexError error was thrown. You can also handle using the pass keyword in the except block. Make sure an array has the appropriate dimensions before declaring it.

Conclusion

To summarize the article on how to fix the error, IndexError: Index is out of bound for axis 0 with size. We’ve discussed why it occurs and how to fix it using three approaches: adjusting the size of an array, adjusting the shape of an array, and using exception handling.

This kind of error occurs when accessing the first item in the first dimension of an empty NumPy array resulting in the Python error IndexError: index 0 is out of bounds for axis 0 with size 0.

There are alternative solutions mentioned in the above article. The first one is to use a try-except block to identify the issue and execute an except statement to handle it.

The second one is to verify that the array’s size is not equal to 0. Use a try-except block to address the issue or verify that the array’s size is not equal to 0 by using the size or shape property before accessing it at a certain index.

If you have found this article helpful, don’t forget to share it and comment 👇 below on which method has helped you solve the IndexError.

Zeeshan is a detail-oriented software engineer and technical content writer with a Bachelor’s in Computer Software Engineering and certifications in SEO and content writing. Thus, he has a passion for creating high-quality, SEO-optimized technical content to help companies and individuals document ideas to make their lives easier with software solutions. With over 150 published articles in various niches, including computer sciences and programming languages such as C++, Java, Python, HTML, CSS, and Ruby, he has a proven track record of delivering well-researched and engaging technical content.

Источник

This article will show you how to fix the IndexError: index 0 is out of bounds for axis 0 with size 0 error that occurs in Python.

This error appears when you try to access a NumPy array that is empty.

Here’s an example code that would trigger this error:

import numpy as np

arr = np.array([])
val = arr[0]  # ❌

The highlighted line above tries to access the element at index 0 of an empty array.

Python responds with the following error message:

Traceback (most recent call last):
  File ...
    val = arr[0]
IndexError: index 0 is out of bounds for axis 0 with size 0

The arr variable is empty, so the index 0 is out of bounds.

To fix this error, you need to ensure that the NumPy array is not empty before trying to access its elements.

You can do this with an if statement as follows:

import numpy as np

arr = np.array([])

if arr.size > 0:
    val = arr[0]
else:
    print("Array is empty")

The if block in the code above only runs when the array size is greater than 0.

Another way to fix this error is to use the try-except statement to catch the error and handle it gracefully:

import numpy as np

arr = np.array([])

try:
    val = arr[0]
except IndexError:
    print("Array is empty")

When working with NumPy arrays, make sure the index you are trying to access is within the bounds of the array.

Another variation of this error is when you get index 1 is out of bounds for axis 0 with size 1.

This error means that you are trying to access the element at index 1 when the array only has a size of 1.

The code below triggers this error:

import numpy as np

arr = np.array([1])
val = arr[1]

Numpy array index are zero-based, so the first element is at index 0.

This means arr[1] is trying to access the second element, which doesn’t exist in the array.

The error message would be:

Traceback (most recent call last):
  File ...
    val = arr[1]
IndexError: index 1 is out of bounds for axis 0 with size 1

Just like the previous error, you need to make sure you are accessing an element that exists.

I hope this tutorial helps you solve the index out of bounds error. 🙏

Источник

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:])/2.0
column2 = data[1,1:]
x_column1 = np.zeros(x.size+2)
x_column1[1:-1] = x
x_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[i]),(column1<x_column1[i+1])))
    temp_column2 = column2[indexes]
    temp_column2[0] -= column2[indexes[0]]*(x_column1[i]-column1[indexes[0]-1])/(column1[indexes[0]]-column1[indexes[0]-1])
    temp_column2[-1] -= column2[indexes[-1]]*(column1[indexes[-1]+1]-x_column1[i+1])/(column1[indexes[-1]+1]-column1[indexes[-1]])
    experiment[i] = np.sum(temp_column2)   
return experiment

This question is related to
python
numpy
indexing
error-handling
index-error

The answer is

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]: x
Out[436]: array([], dtype=int32)
In [437]: x[0]
...
IndexError: index 0 is out of bounds for axis 0 with size 0

I also get it if x = np.zeros((0,5), int), a 2d array with 0 rows, and 5 columns.

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:
- pandas.Series.values or pandas.Series.to_numpy() or pandas.Series.array
- pandas.DataFrame.values or pandas.DataFrame.to_numpy()

Resolving the error:

Use a try-except block
Verify the size of the array is not 0
- if x.size != 0:

Essentially it means you don’t have the index you are trying to reference. For example:

df = pd.DataFrame()
df['this']=np.nan
df['my']=np.nan
df['data']=np.nan
df['data'][0]=5 #I haven't yet assigned how long df[data] should be!
print(df)

will give me the error you are referring to, because I haven’t told Pandas how long my dataframe is. Whereas if I do the exact same code but I DO assign an index length, I don’t get an error:

df = pd.DataFrame(index=[0,1,2,3,4])
df['this']=np.nan
df['is']=np.nan
df['my']=np.nan
df['data']=np.nan
df['data'][0]=5 #since I've properly labelled my index, I don't run into this problem!
print(df)

Hope that answers your question!

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.

# 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)
<ipython-input-16-0891244a3c59> in <module>
----> 1 arr[0] = 23

IndexError: index 0 is out of bounds for axis 0 with size 0

The reason is that we are trying to access an index (here at 0^th 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]: 0

Applied to `pandas`

Resolving the error:

Why does the “IndexError: index 0 is out of bounds for axis 0 with size 0” error occur?

Method 1: Use the if-else statement and array size

Method 2: Use try-except block

Method 3: Use Array shape

Summary

Table of Contents

How to Fix the “IndexError: Index is Out of Bounds For Axis 0 With Size” Error?

1. Adjust The Size of an Array

2. Adjust The Shape of an Array

3. Use Exception Handling

Conclusion

The answer is

Applied to `pandas`

Resolving the error:

Similar questions with python tag:

Similar questions with numpy tag:

Similar questions with indexing tag:

Similar questions with error-handling tag:

Similar questions with index-error tag:

Возможно, вам также будет интересно:

Applied to pandas

Resolving the error:

Why does the “IndexError: index 0 is out of bounds for axis 0 with size 0” error occur?

Method 1: Use the if-else statement and array size

Method 2: Use try-except block

Method 3: Use Array shape

Summary

Table of Contents

How to Fix the “IndexError: Index is Out of Bounds For Axis 0 With Size” Error?

1. Adjust The Size of an Array

2. Adjust The Shape of an Array

3. Use Exception Handling

Conclusion

The answer is

Applied to pandas

Resolving the error:

Similar questions with python tag:

Similar questions with numpy tag:

Similar questions with indexing tag:

Similar questions with error-handling tag:

Similar questions with index-error tag:

Возможно, вам также будет интересно:

Applied to `pandas`

Applied to `pandas`