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+# [The N-dimensional array (ndarray)​](https://numpy.org/doc/stable/reference/arrays.ndarray.html)
+{:.no_toc}
+
+<nav markdown="1" class="toc-class">
+* TOC
+{:toc}
+</nav>
+
+## The goal
+
+Class has a very important job as a core container type in Python. It is really hard to find a good overview how to use them in a good practice manner.
+
+Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
+
+## Chaining of (ndarray) methods​
+
+```python
+import numpy as np
+a = np.ones((3, 3))
+b = a.mean(axis=1).max()
+print(b) # -> 1.0
+```
+
+## [numpy.ndarray.fill​](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.fill.html)
+
+
+
+## [Array methods](https://numpy.org/doc/stable/reference/arrays.ndarray.html#array-methods)
+
+### [Array conversion](https://numpy.org/doc/stable/reference/arrays.ndarray.html#array-conversion)
+
+|||
+|---|---|
+|[ndarray.item(*args)](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.item.html#numpy.ndarray.item)|Copy an element of an array to a standard Python scalar and return it.|
+|[ndarray.tolist()](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tolist.html#numpy.ndarray.tolist)|Return the array as an a.ndim-levels deep nested list of Python scalars.|
+|[ndarray.itemset(*args)](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.itemset.html#numpy.ndarray.itemset)|Insert scalar into an array (scalar is cast to array's dtype, if possible)|
+|[ndarray.tostring([order])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tostring.html#numpy.ndarray.tostring)|A compatibility alias for tobytes, with exactly the same behavior.|
+|[ndarray.tobytes([order])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tobytes.html#numpy.ndarray.tobytes)|Construct Python bytes containing the raw data bytes in the array.|
+|[ndarray.tofile(fid[, sep, format])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tofile.html#numpy.ndarray.tofile)|Write array to a file as text or binary (default).|
+|[ndarray.dump(file)](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.dump.html#numpy.ndarray.dump)|Dump a pickle of the array to the specified file.|
+|[ndarray.dumps()](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.dumps.html#numpy.ndarray.dumps)|Returns the pickle of the array as a string.|
+|[ndarray.astype(dtype[, order, casting, ...])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.astype.html#numpy.ndarray.astype)|Copy of the array, cast to a specified type.|
+|[ndarray.byteswap([inplace])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.byteswap.html#numpy.ndarray.byteswap)|Swap the bytes of the array elements|
+|[ndarray.copy([order])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.copy.html#numpy.ndarray.copy)|Return a copy of the array.|
+|[ndarray.view([dtype][, type])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.view.html#numpy.ndarray.view)|New view of array with the same data.|
+|[ndarray.getfield(dtype[, offset])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.getfield.html#numpy.ndarray.getfield)|Returns a field of the given array as a certain type.|
+|[ndarray.setflags([write, align, uic])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.setflags.html#numpy.ndarray.setflags)|Set array flags WRITEABLE, ALIGNED, WRITEBACKIFCOPY, respectively.|
+|[ndarray.fill(value)](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.fill.html#numpy.ndarray.fill)|Fill the array with a scalar value.|
+
+### Shape manipulation
+
+|||
+|---|---|
+
+|[ndarray.reshape(shape[, order])]()|
+Returns an array containing the same data with a new shape.
+
+|[ndarray.resize(new_shape[, refcheck])]()|
+Change shape and size of array in-place.
+
+|[ndarray.transpose(*axes)]()|
+Returns a view of the array with axes transposed.
+
+|[ndarray.swapaxes(axis1, axis2)]()|
+Return a view of the array with axis1 and axis2 interchanged.
+
+|[ndarray.flatten([order])]()|
+Return a copy of the array collapsed into one dimension.
+
+|[ndarray.ravel([order])]()|
+Return a flattened array.
+
+|[ndarray.squeeze([axis])]()|
+Remove axes of length one from a.
+
+### Item selection and manipulation
+
+|[ndarray.take(indices[, axis, out, mode])]()|
+Return an array formed from the elements of a at the given indices.
+
+|[ndarray.put(indices, values[, mode])]()|
+Set a.flat[n] = values[n] for all n in indices.
+
+|[ndarray.repeat(repeats[, axis])]()|
+Repeat elements of an array.
+
+|[ndarray.choose(choices[, out, mode])]()|
+Use an index array to construct a new array from a set of choices.
+
+|[ndarray.sort([axis, kind, order])]()|
+Sort an array in-place.
+
+|[ndarray.argsort([axis, kind, order])]()|
+Returns the indices that would sort this array.
+
+|[ndarray.partition(kth[, axis, kind, order])]()|
+Rearranges the elements in the array in such a way that the value of the element in kth position is in the position it would be in a sorted array.
+
+|[ndarray.argpartition(kth[, axis, kind, order])]()|
+Returns the indices that would partition this array.
+
+|[ndarray.searchsorted(v[, side, sorter])]()|
+Find indices where elements of v should be inserted in a to maintain order.
+
+|[ndarray.nonzero()]()|
+Return the indices of the elements that are non-zero.
+
+|[ndarray.compress(condition[, axis, out])]()|
+Return selected slices of this array along given axis.
+
+|[ndarray.diagonal([offset, axis1, axis2])]()|
+Return specified diagonals.
+
+### [Calculation](https://numpy.org/doc/stable/reference/arrays.ndarray.html#calculation)
+
+|[ndarray.max([axis, out, keepdims, initial, ...])]()|
+Return the maximum along a given axis.
+
+|[ndarray.argmax([axis, out, keepdims])]()|
+Return indices of the maximum values along the given axis.
+
+|[ndarray.min([axis, out, keepdims, initial, ...])]()|
+Return the minimum along a given axis.
+
+|[ndarray.argmin([axis, out, keepdims])]()|
+Return indices of the minimum values along the given axis.
+
+|[ndarray.ptp([axis, out, keepdims])]()|
+Peak to peak (maximum - minimum) value along a given axis.
+
+|[ndarray.clip([min, max, out])]()|
+Return an array whose values are limited to [min, max].
+
+|[ndarray.conj()]()|
+Complex-conjugate all elements.
+
+|[ndarray.round([decimals, out])]()|
+Return a with each element rounded to the given number of decimals.
+
+|[ndarray.trace([offset, axis1, axis2, dtype, out])]()|
+Return the sum along diagonals of the array.
+
+|[ndarray.sum([axis, dtype, out, keepdims, ...])]()|
+Return the sum of the array elements over the given axis.
+
+|[ndarray.cumsum([axis, dtype, out])]()|
+Return the cumulative sum of the elements along the given axis.
+
+|[ndarray.mean([axis, dtype, out, keepdims, where])]()|
+Returns the average of the array elements along given axis.
+
+|[ndarray.var([axis, dtype, out, ddof, ...])]()|
+Returns the variance of the array elements, along given axis.
+
+|[ndarray.std([axis, dtype, out, ddof, ...])]()|
+Returns the standard deviation of the array elements along given axis.
+
+|[ndarray.prod([axis, dtype, out, keepdims, ...])]()|
+Return the product of the array elements over the given axis
+
+|[ndarray.cumprod([axis, dtype, out])]()|
+Return the cumulative product of the elements along the given axis.
+
+|[ndarray.all([axis, out, keepdims, where])]()|
+Returns True if all elements evaluate to True.
+
+|[ndarray.any([axis, out, keepdims, where])]()|
+Returns True if any of the elements of a evaluate to True.
+
+## [Arithmetic, matrix multiplication, and comparison operations](https://numpy.org/doc/stable/reference/arrays.ndarray.html#arithmetic-matrix-multiplication-and-comparison-operations)
+
+|[ndarray.\_\_lt\_\_(value, /)]()|
+Return self<value.
+
+|[ndarray.\_\_le\_\_(value, /)]()|
+Return self<=value.
+
+|[ndarray.\_\_gt\_\_(value, /)]()|
+Return self>value.
+
+|[ndarray.\_\_ge\_\_(value, /)]()|
+Return self>=value.
+
+|[ndarray.\_\_eq\_\_(value, /)]()|
+Return self==value.
+
+|[ndarray.\_\_ne\_\_(value, /)]()|
+Return self!=value.
+
+|[ndarray.\_\_bool\_\_(/)]()|
+True if self else False
+
+|[ndarray.\_\_neg\_\_(/)]()|
+-self
+
+|[ndarray.\_\_pos\_\_(/)]()|
++self
+
+|[ndarray.\_\_abs\_\_(self)]()|
+
+|[ndarray.\_\_invert\_\_(/)]()|
+~self
+
+|[ndarray.\_\_add\_\_(value, /)]()|
+Return self+value.
+
+|[ndarray.\_\_sub\_\_(value, /)]()|
+Return self-value.
+
+|[ndarray.\_\_mul\_\_(value, /)]()|
+Return self*value.
+
+|[ndarray.\_\_truediv\_\_(value, /)]()|
+Return self/value.
+
+|[ndarray.\_\_floordiv\_\_(value, /)]()|
+Return self//value.
+
+|[ndarray.\_\_mod\_\_(value, /)]()|
+Return self%value.
+
+|[ndarray.\_\_divmod\_\_(value, /)]()|
+Return divmod(self, value).
+
+|[ndarray.\_\_pow\_\_(value[, mod])]()|
+Return pow(self, value, mod).
+
+|[ndarray.\_\_lshift\_\_(value, /)]()|
+Return self<<value.
+
+|[ndarray.\_\_rshift\_\_(value, /)]()|
+Return self>>value.
+
+|[ndarray.\_\_and\_\_(value, /)]()|
+Return self&value.
+
+|[ndarray.\_\_or\_\_(value, /)]()|
+Return self|value.
+
+|[ndarray.\_\_xor\_\_(value, /)]()|
+Return self^value.
+
+|[ndarray.\_\_iadd\_\_(value, /)]()|
+Return self+=value.
+
+|[ndarray.\_\_isub\_\_(value, /)]()|
+Return self-=value.
+
+|[ndarray.\_\_imul\_\_(value, /)]()|
+Return self*=value.
+
+|[ndarray.\_\_itruediv\_\_(value, /)]()|
+Return self/=value.
+
+|[ndarray.\_\_ifloordiv\_\_(value, /)]()|
+Return self//=value.
+
+|[ndarray.\_\_imod\_\_(value, /)]()|
+Return self%=value.
+
+|[ndarray.\_\_ipow\_\_(value, /)]()|
+Return self**=value.
+
+|[ndarray.\_\_ilshift\_\_(value, /)]()|
+Return self<<=value.
+
+|[ndarray.\_\_irshift\_\_(value, /)]()|
+Return self>>=value.
+
+|[ndarray.\_\_iand\_\_(value, /)]()|
+Return self&=value.
+
+|[ndarray.\_\_ior\_\_(value, /)]()|
+Return self|=value.
+
+|[ndarray.\_\_ixor\_\_(value, /)]()|
+Return self^=value.
+
+|[ndarray.\_\_matmul\_\_(value, /)]()|
+Return self@value.
+
+
+### [Special methods](https://numpy.org/doc/stable/reference/arrays.ndarray.html#special-methods)
+
+[special methods](https://numpy.org/doc/stable/reference/arrays.ndarray.html#special-methods)
+
+
+