# FAQs¶

## Why does it take so long ?¶

A typical fitter usage is as follows:

```
from fitter import Fitter
f = Fitter(data)
f.fit()
f.summary()
```

This will run the fitting process on your data with about 80 different distributions. If you want to reduce the time significantly, provide a subset of distributions as follows:

```
from fitter import Fitter
f = Fitter(data, distributions=["gamma", "rayleigh", "uniform"])
f.fit()
f.summary()
```

Another easy way to reduce the computational time is to provide a subset of your data. If you date set has a length of 1 million data points, just sub-sample it to 10,000 points for instance. This way you can identify sensible distributions, and try again with those distributions on the entire data (divide and conquer, as always !)

## What are the distributions available ?¶

Since version 1.2, you can use:

```
from fitter import get_distributions
get_distributions()
```

You may get a sub set of common distributions as follows:

```
from fitter import get_common_distributions
get_common_distributions()
```