# otp.Source.tail (jupyter)

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

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

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

* **Parameters:**
  * **n** ([*int*](https://docs.pip.distribution.sol.onetick.com/api/types/int.html.md#onetick.py.int)) -- 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.tail()
                     Time  X
0 2003-12-01 00:00:00.004  e
1 2003-12-01 00:00:00.005  f
2 2003-12-01 00:00:00.006  g
3 2003-12-01 00:00:00.007  i
4 2003-12-01 00:00:00.008  k
```

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