## Issue

In ** numpy** /

**, is there an**

`scipy`

**efficient**way to get frequency counts for unique values in an array?

Something along these lines:

```
x = array( [1,1,1,2,2,2,5,25,1,1] )
y = freq_count( x )
print y
>> [[1, 5], [2,3], [5,1], [25,1]]
```

( For you, R users out there, I’m basically looking for the `table()`

function )

## Solution

Take a look at `np.bincount`

:

http://docs.scipy.org/doc/numpy/reference/generated/numpy.bincount.html

```
import numpy as np
x = np.array([1,1,1,2,2,2,5,25,1,1])
y = np.bincount(x)
ii = np.nonzero(y)[0]
```

And then:

```
zip(ii,y[ii])
# [(1, 5), (2, 3), (5, 1), (25, 1)]
```

or:

```
np.vstack((ii,y[ii])).T
# array([[ 1, 5],
[ 2, 3],
[ 5, 1],
[25, 1]])
```

or however you want to combine the counts and the unique values.

Answered By – JoshAdel

Answer Checked By – Senaida (BugsFixing Volunteer)