# NumPy - ndarray.tolist() function

The NumPy ndarray.tolist() function returns a copy of the array data as a (nested) Python list. Data items are converted to the nearest compatible built-in Python type.

If the dimension of the array is 0, then since the depth of the nested list is 0, it will not be a list at all, but a simple Python scalar.

### Syntax

```numpy.ndarray.tolist()
```

### Parameters

`No parameter is required.`

### Return Value

Returns the possibly nested Python list containing array elements.

### Example:

In the example below, numpy arrays are converted into Python lists.

```import numpy as np

#0-D numpy array
Arr0 = np.array(100)
#1-D numpy array
Arr1 = np.arange(1, 6)
#2-D numpy array
Arr2 = np.arange(1, 7).reshape(2,3)

#converting into python list
List0 = Arr0.tolist()
List1 = Arr1.tolist()
List2 = Arr2.tolist()

#displaying the result
print(List0)
print(List1)
print(List2)
```

The output of the above code will be:

```100
[1, 2, 3, 4, 5]
[[1, 2, 3], [4, 5, 6]]
```

### Example:

Data items are converted to the nearest compatible built-in Python type. Consider the example below:

```import numpy as np

#1-D numpy array
Arr = np.arange(1, 6)

#converting into python list
MyList = Arr.tolist()

#displaying numpy array info
print(Arr)
print(type(Arr))
print(type(Arr))

print()
#displaying python list info
print(MyList)
print(type(MyList))
print(type(MyList))
```

The output of the above code will be:

```[1 2 3 4 5]
<class 'numpy.ndarray'>
<class 'numpy.int64'>

[1, 2, 3, 4, 5]
<class 'list'>
<class 'int'>
```

❮ NumPy - Functions

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