Updated On : Jul-09,2020  numpy, basics

# Learning Numpy - Simple Tutorial For Beginners - NumPy - Indexing & Slicing Part 8¶

Contents of ndarray object can be accessed and modified by indexing or slicing, just like Python's in-built container objects.

As mentioned earlier, items in ndarray object follows zero-based index. Three types of indexing methods are available − field access, basic slicing and advanced indexing.

Basic slicing is an extension of Python's basic concept of slicing to n dimensions. A Python slice object is constructed by giving start, stop, and step parameters to the built-in slice function. This slice object is passed to the array to extract a part of array.

### Example 1¶

In [2]:
```import numpy as np
a = np.arange(10)
s = slice(2,7,2)
print (a[s])
```
```[2 4 6]
```

### Example 2¶

In [3]:
```import numpy as np
a = np.arange(10)
b = a[2:7:2]
print (b)
```
```[2 4 6]
```

### Example 3¶

In [5]:
```# slice single item
import numpy as np

a = np.arange(10)
b = a[5]
print (b)
```
```5
```

### Example 4¶

In [8]:
```# slice items starting from index
import numpy as np
a = np.arange(10)
print (a[2:])
```
```[2 3 4 5 6 7 8 9]
```

### Example 5¶

In [9]:
```# slice items between indexes
import numpy as np
a = np.arange(10)
print (a[2:5])
```
```[2 3 4]
```

### Example 6¶

In [12]:
```import numpy as np
a = np.array([[1,2,3],[3,4,5],[4,5,6]])
print (a)

# slice items starting from index
print ('Now we will slice the array from the index a[1:]')
print (a[1:])
```
```[[1 2 3]
[3 4 5]
[4 5 6]]
Now we will slice the array from the index a[1:]
[[3 4 5]
[4 5 6]]
```

### Example 7¶

In [14]:
```# array to begin with
import numpy as np
a = np.array([[1,2,3],[3,4,5],[4,5,6]])

print ('Our array is:')
print (a)
print ('\n')

# this returns array of items in the second column
print ('The items in the second column are:')
print (a[...,1])
print ('\n')

# Now we will slice all items from the second row
print ('The items in the second row are:')
print (a[1,...])
print ('\n')

# Now we will slice all items from column 1 onwards
print ('The items column 1 onwards are:')
print (a[...,1:])
```
```Our array is:
[[1 2 3]
[3 4 5]
[4 5 6]]

The items in the second column are:
[2 4 5]

The items in the second row are:
[3 4 5]

The items column 1 onwards are:
[[2 3]
[4 5]
[5 6]]
```
Dolly Solanki

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