Added Reshape task

Author: sofiiako

Numpy/Array Basics/Reshape/__init__.py

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+type: edu
+files:
+- name: task.py
+  visible: true
+  placeholders:
+  - offset: 24
+    length: 20
+    placeholder_text: '# TODO'
+  - offset: 49
+    length: 15
+    placeholder_text: '# TODO'
+- name: tests/test_task.py
+  visible: false
+- name: __init__.py
+  visible: false
+- name: tests/__init__.py
+  visible: false

Numpy/Array Basics/Reshape/task-info.yaml

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+## Reshape
+
+Reshaping means changing the `shape` of an array without changing its data.
+As we mentioned earlier, the `shape` of an array is the number of elements in each dimension.
+By reshaping we can add or remove dimensions or change the number of elements in each dimension.
+
+The function [`numpy.reshape`](https://numpy.org/doc/stable/reference/generated/numpy.reshape.html#numpy.reshape) 
+is used for reshaping, and it accepts three arguments:
+
+- The array to be reshaped.
+- The new shape as an `int` or tuple of `int`s.
+- An optional argument `order`, which defines the order in which the elements are read and placed into the reshaped array.
+
+### Examples
+1. Reshape 1D array into a 2D array:
+```python
+a = np.arange(10)
+print(np.reshape(a, (2, 5)))
+```
+Output:
+```text
+[[0 1 2 3 4]
+ [5 6 7 8 9]]
+```
+2. Reshape a 2D array into a 1D array:
+```python
+a = np.array([[1, 2, 3], [4, 5, 6]])
+print(np.reshape(a, 6))
+```
+Output:
+```text
+[1 2 3 4 5 6]
+```
+
+The latter can also be achieved by using `numpy.ndarray.flatten`:
+```python
+a = np.array([[1, 2, 3], [4, 5, 6]])
+print(a.flatten())
+```
+Output:
+```text
+[1 2 3 4 5 6]
+```
+
+### Task
+1. Create an array `a` of integers in the interval from `12` to `30` with step `3`.
+2. Reshape it so that it has 2 rows and 3 columns.
+
+<div class="hint">For (1) you can use the <code>arange</code> function.</div>

Numpy/Array Basics/Reshape/task.md

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+import numpy as np
+
+a = np.arange(12, 30, 3)
+b = a.reshape(2, 3)
+
+if __name__ == "__main__":
+    print(a)
+    print('shape : ', a.shape)
+    print('\nAfter reshaping : ')
+    print(b)
+    print('shape : ', b.shape)

Numpy/Array Basics/Reshape/task.py

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+import unittest
+import numpy as np
+
+from task import a, b
+
+class TestCase(unittest.TestCase):
+    def test_arrays(self):
+        np.testing.assert_array_equal(a, np.arange(12, 30, 3), err_msg='Array a is not what we expected!')
+        np.testing.assert_array_equal(b, a.reshape(2, 3), err_msg='Array b is not what we expected!')
+

Numpy/Array Basics/Reshape/tests/__init__.py

@@ -3,4 +3,5 @@ content:
 - Create an Array from List
 - Create an Empty Array
 - Create an Array from Range
+- Reshape
 - Random Sampling