# otp.Source.head (jupyter)

#### Source.head(n=5, \*\*kwargs)

*Executes the query* and returns first `n` ticks as a pandas dataframe.

It is useful in the Jupyter case when you want to observe first `n` values.

* **Parameters:**
  * **n** ([*int*](https://docs.pip.distribution.sol.onetick.com/api/types/int.html.md#onetick.py.int) *,* *default=5*) -- number of ticks to return
  * **kwargs** -- parameters will be passed to [`otp.run`](https://docs.pip.distribution.sol.onetick.com/api/run.html.md#onetick.py.run)
  * **self** ([*Source*](https://docs.pip.distribution.sol.onetick.com/api/source/root.html.md#onetick.py.Source))
* **Return type:**
  [DataFrame](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html)

### Examples

```pycon
>>> data = otp.Ticks(X=list('abcdefgik'))
>>> data.head()
                     Time  X
0 2003-12-01 00:00:00.000  a
1 2003-12-01 00:00:00.001  b
2 2003-12-01 00:00:00.002  c
3 2003-12-01 00:00:00.003  d
4 2003-12-01 00:00:00.004  e
```

#### SEE ALSO
[`onetick.py.agg.first()`](https://docs.pip.distribution.sol.onetick.com/api/aggregations/first.html.md#onetick.py.agg.first)
<br/>
[`otp.run`](https://docs.pip.distribution.sol.onetick.com/api/run.html.md#onetick.py.run)
<br/>
[`onetick.py.Source.tail()`](https://docs.pip.distribution.sol.onetick.com/api/source/runners/tail.html.md#onetick.py.Source.tail)
<br/>
[`onetick.py.Source.count()`](https://docs.pip.distribution.sol.onetick.com/api/source/runners/count.html.md#onetick.py.Source.count)
<br/>