﻿ NumPy: Count the frequency of unique values in numpy array - w3resource

# NumPy: Count the frequency of unique values in numpy array

## NumPy: Array Object Exercise-94 with Solution

Write a NumPy program to count the frequency of unique values in numpy array.

Pictorial Presentation:

Sample Solution:

Python Code:

``````import numpy as np
a = np.array( [10,10,20,10,20,20,20,30, 30,50,40,40] )
print("Original array:")
print(a)
unique_elements, counts_elements = np.unique(a, return_counts=True)
print("Frequency of unique values of the said array:")
print(np.asarray((unique_elements, counts_elements)))
```
```

Sample Output:

```Original array:
[10 10 20 10 20 20 20 30 30 50 40 40]
Frequency of unique values of the said array:
[[10 20 30 40 50]
[ 3  4  2  2  1]]
```

Python Code Editor:

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## Python: Tips of the Day

Getting the last element of a list:

some_list[-1] is the shortest and most Pythonic.

In fact, you can do much more with this syntax. The some_list[-n] syntax gets the nth-to-last element. So some_list[-1] gets the last element, some_list[-2] gets the second to last, etc, all the way down to some_list[-len(some_list)], which gives you the first element.

You can also set list elements in this way. For instance:

```>>> some_list = [1, 2, 3]
>>> some_list[-1] = 5 # Set the last element
>>> some_list[-2] = 3 # Set the second to last element
>>> some_list
[1, 3, 5]
```

Note that getting a list item by index will raise an IndexError if the expected item doesn't exist. This means that some_list[-1] will raise an exception if some_list is empty, because an empty list can't have a last element.

Ref: https://bit.ly/3d8TfFP