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

Let’s see How to count the frequency of unique values in NumPy array. Python’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 ` `# and 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]]```

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