Create README.md

Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>

numpy/dimensions/README.md

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+# Dimensions and shape
+{:.no_toc}
+
+<nav markdown="1" class="toc-class">
+* TOC
+{:toc}
+</nav>
+
+## The goal
+
+
+
+Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
+
+## [numpy.ndarray.shape](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.shape.html)
+
+```python
+ndarray.shape
+```
+
+> Tuple of array dimensions.
+> 
+> The shape property is usually used to get the current shape of an array, but may also be used to reshape the array in-place by assigning a tuple of array dimensions to it. As with numpy.reshape, one of the new shape dimensions can be -1, in which case its value is inferred from the size of the array and the remaining dimensions. Reshaping an array in-place will fail if a copy is required.
+
+```python
+import numpy as np
+
+data = np.zeros((2, 4, 2, 7, 2))
+print(data.shape)  # -> (2, 4, 2, 7, 2)
+```
+
+## Vanishing dimensions
+
+```python
+import numpy as np
+
+data = np.zeros((5, 3, 2))
+
+# All the same dimensionwise
+print(data.shape)  # -> (5, 3, 2)
+print(data[:].shape)  # ->  (5, 3, 2)
+print(data[:, :, :].shape)  # ->  (5, 3, 2)
+print(data[...].shape)  # ->  (5, 3, 2)
+
+
+print(data[0, :, :].shape)  # ->  (3, 2)
+print(data[:, 0, :].shape)  # ->  (5, 2)
+print(data[:, :, 0].shape)  # ->  (5, 3)
+
+print(data[:, 0, 0].shape)  # ->  (5,)
+print(data[0, :, 0].shape)  # ->  (3,)
+print(data[0, 0, :].shape)  # ->  (2,)
+
+print(data[0, 0, 0].shape)  # ->  ()
+print(type(data[0, 0, 0]))  # ->  <class 'numpy.float64'>
+```
+
+```python
+import numpy as np
+
+data = np.zeros((5, 3, 2))
+
+# All the same dimensionwise
+print(data.shape)  # -> (5, 3, 2)
+print(data.sum().shape)  # -> ()
+print(data.sum(axis=0).shape)  # -> (3, 2)
+print(data.sum(axis=1).shape)  # -> (5, 2)
+print(data.sum(axis=2).shape)  # -> (5, 3)
+
+# You can use keepdims:
+
+print(data.sum(axis=0, keepdims=True).shape)  # -> (1, 3, 2)
+print(data.sum(axis=1, keepdims=True).shape)  # -> (5, 1, 2)
+print(data.sum(axis=2, keepdims=True).shape)  # -> (5, 3, 1)
+```
+
+