# NumPy - Ndarray Object

Ndarray is the n-dimensional array object defined in the numpy. It stores the collection of elements of the same type. Elements in the collection can be accessed using a zero-based index. Each element in an ndarray takes the same size in memory.

## Create a Numpy ndarray object

A Numpy ndarray object can be created using array() function. A list, tuple or any array-like object can be passed into the array() function to convert it into an ndarray. The syntax for using the function is given below:

### Syntax

```numpy.array(object, dtype=None, copy=True, order='K', subok=False, ndmin=0)
```

### Parameters

 `object` `Required. `Specify the collection object to be converted into ndarray. It can be list, tuple, set, dictionary etc. `dtype` `Optional. `Specify the desired data type. It is used to change the data type of the array element. `copy` `Optional. `Specify True to copy the object, False otherwise. `order` `Optional. `Specify order. It can take four possible values. 'C' - for C order (row major). 'F' - for F order (column major). 'A' - unchanged if copy=False. If copy=True, F and C order preserved. 'K' - unchanged if copy=False. If copy=True, When the input is F and not C then F order otherwise C order. `subok` `Optional. `Specify True to make the returned array sub-classes pass through. By default, the returned array forced to be base class array. `ndmin` `Optional. `Specify the minimum dimension of the array.

### Example: Create 1-D Array

In the example below, a list is used to create a 1-D numpy array.

```import numpy as np
MyList = [1, 2, 3, 4, 5]
npArray = np.array(MyList)
print(npArray)
```

The output of the above code will be:

```[1 2 3 4 5]
```

### Example: Create 2-D Array

In this example, a list of lists is used to create a 2-D numpy array.

```import numpy as np
MyList = [[1, 2, 3], [4, 5, 6]]
npArray = np.array(MyList)
print(npArray)
```

The output of the above code will be:

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

### Example: Create 2-D Array using ndmin parameter

A n-dimensional array can be created using ndmin parameter of the array function. Like, in this example, it is used to create 2-D array.

```import numpy as np
MyList = [1, 2, 3, 4, 5]
npArray = np.array(MyList, ndmin=2)
print(npArray)
```

The output of the above code will be:

```[[1 2 3 4 5]]
```

### Example: Create 1-D Array with dtype parameter

The dtype argument is used to change the data type of elements of the ndarray object.

```import numpy as np
MyList = [1, 0, 0, 1, 0]
npArray = np.array(MyList, dtype=bool)
print(npArray)
```

The output of the above code will be:

```[ True False False  True False]
```

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