DOC: improved the docstring of pandas.Series.clip_lower
State: closed

```
(pandas_dev) david@david-TM1604:~/repos/pandas/scripts$ python validate_docstrings.py pandas.Series.clip_lower

################################################################################
##################### Docstring (pandas.Series.clip_lower) #####################
################################################################################

Return copy of the input with values below given value(s) truncated.

It truncate values below a certain threshold. Threshold can be a single
value or an array, in the latter case it performs the truncation element-wise.

Parameters
----------
threshold : float or array_like
    Minimum value allowed. All values below threshold will be
    set to this value.
axis : int or string axis name, optional
    Align object with threshold along the given axis.
inplace : boolean, default False
    Whether to perform the operation in place on the data.

See Also
--------
clip : Return copy of the input with values below and over given thresholds values truncated.

Returns
-------
clipped : same type as input

Examples
--------
>>> s = pd.Series([3.816052, 7.969235, 6.903116, 2.532261, 5.015296])
>>> s
0    3.816052
1    7.969235
2    6.903116
3    2.532261
4    5.015296
dtype: float64

>>> s.clip_lower(4)
0    4.000000
1    7.969235
2    6.903116
3    4.000000
4    5.015296
dtype: float64

>>> t = [4,8,7,2,5]
>>> t
[4, 8, 7, 2, 5]

>>> s.clip_lower(t)
0    4.000000
1    8.000000
2    7.000000
3    2.532261
4    5.015296
dtype: float64

################################################################################
################################## Validation ##################################
################################################################################

Docstring for "pandas.Series.clip_lower" correct. :)
```

Labels:
name: Docs
name: Numeric Operations
description: Arithmetic, Comparison, and Logical operations

Comments:
Hello @dcanones! Thanks for updating the PR.



Cheers ! There are no PEP8 issues in this Pull Request. :beers: 

##### Comment last updated on March 15, 2018 at 21:10 Hours UTC
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------

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Reviewer requests added
lgtm
Thanks @dcanones