# numpy.insert¶

numpy.insert(arr, obj, values, axis=None)[source]

Insert values along the given axis before the given indices.

Parameters : arr : array_like Input array. obj : int, slice or sequence of ints Object that defines the index or indices before which values is inserted. values : array_like Values to insert into arr. If the type of values is different from that of arr, values is converted to the type of arr. axis : int, optional Axis along which to insert values. If axis is None then arr is flattened first. out : ndarray A copy of arr with values inserted. Note that insert does not occur in-place: a new array is returned. If axis is None, out is a flattened array.

append
Append elements at the end of an array.
delete
Delete elements from an array.

Examples

```>>> a = np.array([[1, 1], [2, 2], [3, 3]])
>>> a
array([[1, 1],
[2, 2],
[3, 3]])
>>> np.insert(a, 1, 5)
array([1, 5, 1, 2, 2, 3, 3])
>>> np.insert(a, 1, 5, axis=1)
array([[1, 5, 1],
[2, 5, 2],
[3, 5, 3]])
```
```>>> b = a.flatten()
>>> b
array([1, 1, 2, 2, 3, 3])
>>> np.insert(b, [2, 2], [5, 6])
array([1, 1, 5, 6, 2, 2, 3, 3])
```
```>>> np.insert(b, slice(2, 4), [5, 6])
array([1, 1, 5, 2, 6, 2, 3, 3])
```
```>>> np.insert(b, [2, 2], [7.13, False]) # type casting
array([1, 1, 7, 0, 2, 2, 3, 3])
```
```>>> x = np.arange(8).reshape(2, 4)
>>> idx = (1, 3)
>>> np.insert(x, idx, 999, axis=1)
array([[  0, 999,   1,   2, 999,   3],
[  4, 999,   5,   6, 999,   7]])
```

numpy.delete

numpy.append