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[Solved] IndexError: boolean index did not match indexed array along dimension 0

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error IndexError: boolean index did not match indexed array along dimension 0 in python. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

How IndexError: boolean index did not match indexed array along dimension 0 Error Occurs?

Today I get the following error IndexError: boolean index did not match indexed array along dimension 0 in python.

How To Solve IndexError: boolean index did not match indexed array along dimension 0 Error ?

  1. How To Solve IndexError: boolean index did not match indexed array along dimension 0 Error ?

    To Solve IndexError: boolean index did not match indexed array along dimension 0 Error I am using Numpy 1.11, instead of an IndexError I get a VisibleDeprecationWarning. So I guess using an incorrect size is no longer tolerated.

  2. IndexError: boolean index did not match indexed array along dimension 0

    To Solve IndexError: boolean index did not match indexed array along dimension 0 Error I am using Numpy 1.11, instead of an IndexError I get a VisibleDeprecationWarning. So I guess using an incorrect size is no longer tolerated.

Solution 1

np.diff is one element smaller than data_array.

The shape of the output is the same as a except along axis where the dimension is smaller by n.

numpy.diff

I am using Numpy 1.11, instead of an IndexError I get a VisibleDeprecationWarning. So I guess using an incorrect size is no longer tolerated.

You need to define which behaviour you want, e.g. start at the second element, or remove the last:

arr = np.array([1,2,3,4,5])

arr2 = arr[:-1]
m = arr2[np.diff(np.cumsum(arr) >= sum(arr))]

arr3 = arr[1:]
m = arr3[np.diff(np.cumsum(arr) >= sum(arr))]

Summery

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

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