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[Solved] TypeError: iteration over a 0-d array Python

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error TypeError: iteration over a 0-d array Python 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 TypeError: iteration over a 0-d array Python Error Occurs?

Today I get the following error TypeError: iteration over a 0-d array Python in python.

How To Solve TypeError: iteration over a 0-d array Python Error ?

  1. How To Solve TypeError: iteration over a 0-d array Python Error ?

    To Solve TypeError: iteration over a 0-d array Python Error It is possible to load a 0-d numpy array with arr1 = np.load(..., allow_pickle=True). To access the item stored as being a np.array, use:

  2. TypeError: iteration over a 0-d array Python

    To Solve TypeError: iteration over a 0-d array Python Error It is possible to load a 0-d numpy array with arr1 = np.load(..., allow_pickle=True). To access the item stored as being a np.array, use:

Solution 1

The problem is np.array does not take an iterator, you need convert to list first, as below:

t = np.array(list(map(lambda v: map(lambda w: distance(v, w, L),
                      x_train.values), x_test.values)))

As per numpy.array documentation, the required parameter must be:

An array, any object exposing the array interface, an object whose array method returns an array, or any (nested) sequence.

Alternatively, use numpy.fromiter and remember to supply dtype, e.g. dtype=float.

Solution 2

It is possible to load a 0-d numpy array with arr1 = np.load(..., allow_pickle=True). To access the item stored as being a np.array, use:

arr1.item()

For instance, if the type stored is a dict d1 = {'item1':42, 'item2':np.array(1,3)} we can get the value as such: v1 = arr1.item()['item2'].

Important: Loading with allow_pickle=True is brings security risks and is not recommended.

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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