# How to count the frequency of unique values in NumPy array?

• Last Updated : 02 Sep, 2020

Let’s see How to count the frequency of unique values in NumPy array. Pythonâ€™s numpy library provides a numpy.unique() function to find the unique elements and it’s corresponding frequency in a numpy array.

Syntax: numpy.unique(arr, return_counts=False)

Return: Sorted unique elements of an array with their corresponding frequency counts NumPy array.

Now, Let’s see examples:

Example 1:

## Python3

 `# import library``import` `numpy as np`` ` `ini_array ``=` `np.array([``10``, ``20``, ``5``,``                      ``10``, ``8``, ``20``,``                      ``8``, ``9``])`` ` `# Get a tuple of unique values ``# and their frequency in``# numpy array``unique, frequency ``=` `np.unique(ini_array, ``                              ``return_counts ``=` `True``)``# print unique values array``print``(``"Unique Values:"``, ``      ``unique)`` ` `# print frequency array``print``(``"Frequency Values:"``,``      ``frequency)`

Output:

```Unique Values: [ 5  8  9 10 20]
Frequency Values: [1 2 1 2 2]
```

Example 2:

## Python3

 `# import library``import` `numpy as np`` ` `# create a 1d-array``ini_array ``=` `np.array([``10``, ``20``, ``5``,``                    ``10``, ``8``, ``20``,``                    ``8``, ``9``])`` ` `# Get a tuple of unique values ``# amnd their frequency ``# in numpy array``unique, frequency ``=` `np.unique(ini_array,``                              ``return_counts ``=` `True``) `` ` `# convert both into one numpy array``count ``=` `np.asarray((unique, frequency ))`` ` `print``(``"The values and their frequency are:\n"``,``     ``count)`

Output:

```The values and their frequency are:
[[ 5  8  9 10 20]
[ 1  2  1  2  2]]```

Example 3:

## Python3

 `# import library``import` `numpy as np`` ` `# create a 1d-array``ini_array ``=` `np.array([``10``, ``20``, ``5``,``                      ``10``, ``8``, ``20``,``                      ``8``, ``9``])`` ` `# Get a tuple of unique values ``# and their frequency in``# numpy array``unique, frequency ``=` `np.unique(ini_array, ``                              ``return_counts ``=` `True``) `` ` `# convert both into one numpy array ``# and then transpose it``count ``=` `np.asarray((unique,frequency )).T`` ` `print``(``"The values and their frequency are in transpose form:\n"``,``     ``count)`

Output:

```The values and their frequency are in transpose form:
[[ 5  1]
[ 8  2]
[ 9  1]
[10  2]
[20  2]]```

My Personal Notes arrow_drop_up