DOC: update the docstring of pandas.DataFrame.from_dict
State: closed

Checklist for the pandas documentation sprint (ignore this if you are doing
an unrelated PR):

- [x] PR title is "DOC: update the <your-function-or-method> docstring"
- [x] The validation script passes: `scripts/validate_docstrings.py <your-function-or-method>`
- [x] The PEP8 style check passes: `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] The html version looks good: `python doc/make.py --single <your-function-or-method>`
- [ ] It has been proofread on language by another sprint participant

Please include the output of the validation script below between the "```" ticks:

```
(pandas_dev) david@david-TM1604:~/repos/pandas$ python scripts/validate_docstrings.py pandas.DataFrame.from_dict

################################################################################
#################### Docstring (pandas.DataFrame.from_dict) ####################
################################################################################

Construct DataFrame from dict of array-like or dicts.

Creates DataFrame object from dictionary by columns or by index
allowing dtype specification.

Parameters
----------
data : dict
    Of the form {field : array-like} or {field : dict}.
orient : {'columns', 'index'}, default 'columns'
    The "orientation" of the data. If the keys of the passed dict
    should be the columns of the resulting DataFrame, pass 'columns'
    (default). Otherwise if the keys should be rows, pass 'index'.
dtype : dtype, default None
    Data type to force, otherwise infer.
columns : list, default None
    Column labels to use when orient='index'. Raises a ValueError
    if used with orient='columns'.
    .. versionadded:: 0.23.0

See Also
--------
pandas.DataFrame.from_records : DataFrame from ndarray (structured dtype),
                                list of tuples, dict, or DataFrame
pandas.DataFrame: DataFrame object creation using constructor

Returns
-------
pandas.DataFrame

Examples
--------
>>> data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
>>> pd.DataFrame.from_dict(data)
   col_1 col_2
0      3     a
1      2     b
2      1     c
3      0     d

>>> data = {'row_1': [3, 2, 1, 0], 'row_2': ['a', 'b', 'c', 'd']}
>>> pd.DataFrame.from_dict(data, orient='index')
       0  1  2  3
row_1  3  2  1  0
row_2  a  b  c  d

################################################################################
################################## Validation ##################################
################################################################################

Errors found:
	Errors in parameters section
		Parameter "columns" description should finish with "."
```

If the validation script still gives errors, but you think there is a good reason
to deviate in this case (and there are certainly such cases), please state this
explicitly.


Checklist for other PRs (remove this part if you are doing a PR for the pandas documentation sprint):

- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry


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



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

##### Comment last updated on March 11, 2018 at 14:38 Hours UTC
PEP-8 inspector marks this chunk as too long but line is not really that long. Any idea how to properly write this?

```
pandas.DataFrame.from_records : DataFrame from ndarray (structured dtype),
                                list of tuples, dict, or DataFrame
```
@dcanones the second line can be written with a single level of indentation:

```
pandas.DataFrame.from_records : DataFrame from ndarray (structured dtype),
    list of tuples, dict, or DataFrame
```
Done!

Noticed .. versionadded looks weird after building html docs with sphinx: 
![image](https://user-images.githubusercontent.com/6515763/37253588-ddba48f0-2533-11e8-9a7c-359a5475a9dc.png)

@dcanones Thanks a lot!