Updated On : Jun-25,2020  numpy, basics

# Learning Numpy - Simple Tutorial For Beginners - NumPy - Array Attributes Part 4¶

Here we would be learning about the attributes of the array.

### ndarray.shape ¶

This array attribute returns a tuple consisting of array dimensions. It can also be used to resize the array.

### Example 1¶

In [2]:
```import numpy as np
a = np.array([[1,2,3],[4,5,6]])
print (a.shape)
```
```(2, 3)
```

### Example 2¶

In [3]:
```# this resizes the ndarray
import numpy as np

a = np.array([[1,2,3],[4,5,6]])
a.shape = (3,2)
print (a)
```
```[[1 2]
[3 4]
[5 6]]
```

### Example 3¶

NumPy also provides a reshape function to resize an array.

In [5]:
```import numpy as np
a = np.array([[1,2,3],[4,5,6]])
b = a.reshape(3,2)
print (b)
```
```[[1 2]
[3 4]
[5 6]]
```

### ndarray.ndim ¶

This array attribute returns the number of array dimensions.

### Example 1¶

In [6]:
```# an array of evenly spaced numbers
import numpy as np
a = np.arange(24)
print (a)
```
```[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]
```

### Example 2¶

In [7]:
```# this is one dimensional array
import numpy as np
a = np.arange(24)
a.ndim

# now reshape it
b = a.reshape(2,4,3)
print (b)
# b is having three dimensions
```
```[[[ 0  1  2]
[ 3  4  5]
[ 6  7  8]
[ 9 10 11]]

[[12 13 14]
[15 16 17]
[18 19 20]
[21 22 23]]]
```

### numpy.itemsize ¶

This array attribute returns the length of each element of array in bytes.

### Example 1¶

In [9]:
```# dtype of array is int8 (1 byte)
import numpy as np
x = np.array([1,2,3,4,5], dtype = np.int8)
print (x.itemsize)
```
```1
```

### Example 2¶

In [11]:
```# dtype of array is now float32 (4 bytes)
import numpy as np
x = np.array([1,2,3,4,5], dtype = np.float32)
print (x.itemsize)
```
```4
```

### numpy.flags ¶

The ndarray object has the following attributes. Its current values are returned by this function.

### Example 1¶

In [1]:
```import numpy as np
x = np.array([1,2,3,4,5])
print (x.flags)
```
```  C_CONTIGUOUS : True
F_CONTIGUOUS : True
OWNDATA : True
WRITEABLE : True
ALIGNED : True
WRITEBACKIFCOPY : False
UPDATEIFCOPY : False
```
Attribute Description
C_CONTIGUOUS (C) The data is in a single, C-style contiguous segment
F_CONTIGUOUS (F) The data is in a single, Fortran-style contiguous segment
OWNDATA (O) The array owns the memory it uses or borrows it from another object
WRITEABLE (W) The data area can be written to. Setting this to False locks the data, making it read-only
ALIGNED (A) The data and all elements are aligned appropriately for the hardware
UPDATEIFCOPY (U) This array is a copy of some other array. When this array is deallocated, the base array will be updated with the contents of this array
Dolly Solanki

## Support Us

Thank You for visiting our website. If you like our work, please support us so that we can keep on creating new tutorials/blogs on interesting topics (like AI, ML, Data Science, Python, Digital Marketing, SEO, etc.) that can help people learn new things faster. You can support us by clicking on the Coffee button at the bottom right corner. We would appreciate even if you can give a thumbs-up to our article in the comments section below.

## Want to Share Your Views? Have Any Suggestions?

If you want to

• provide some suggestions on topic
• include some details in tutorial
• suggest some new topics on which we should create tutorials/blogs