DOC: update the docstring of pandas.DataFrame.info
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>`
- [x] 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/scripts$ python validate_docstrings.py pandas.DataFrame.info

################################################################################
###################### Docstring (pandas.DataFrame.info)  ######################
################################################################################

Concise summary of a DataFrame.

This method shows information about DataFrame type of index, columns
dtypes and non-null values and memory usage.

Parameters
----------
verbose : {None, True, False}, optional
    Whether to print the full summary.
    None follows the `display.max_info_columns` setting.
    True or False overrides the `display.max_info_columns` setting.
buf : writable buffer, defaults to sys.stdout
    Whether to pipe the output.
max_cols : int, default None
    Determines whether full summary or short summary is printed.
    None follows the `display.max_info_columns` setting.
memory_usage : boolean/string, default None
    Specifies whether total memory usage of the DataFrame
    elements (including index) should be displayed. None follows
    the `display.memory_usage` setting. True or False overrides
    the `display.memory_usage` setting. A value of 'deep' is equivalent
    of True, with deep introspection. Memory usage is shown in
    human-readable units (base-2 representation).
null_counts : boolean, default None
    Whether to show the non-null counts

    - If None, then only show if the frame is smaller than
      max_info_rows and max_info_columns.
    - If True, always show counts.
    - If False, never show counts.

Returns
-------
None: NoneType
    This method outputs a summary of a DataFrame and returns None.

Examples
--------
>>> int_values = [1, 2, 3, 4, 5]
>>> text_values = ['alpha', 'beta', 'gamma', 'delta', 'epsilon']
>>> float_values = [0.0, 0.25, 0.5, 0.75, 1.0]
>>> df = pd.DataFrame({"int_col": int_values, "text_col": text_values, "float_col": float_values})
>>> df
   int_col text_col  float_col
0        1    alpha       0.00
1        2     beta       0.25
2        3    gamma       0.50
3        4    delta       0.75
4        5  epsilon       1.00

>>> df.info(verbose=True)
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 3 columns):
int_col      5 non-null int64
text_col     5 non-null object
float_col    5 non-null float64
dtypes: float64(1), int64(1), object(1)
memory usage: 200.0+ bytes

>>> df.info(verbose=False)
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Columns: 3 entries, int_col to float_col
dtypes: float64(1), int64(1), object(1)
memory usage: 200.0+ bytes

>>> file = open("df_info.txt", "w", encoding="utf-8")
>>> df.info(buf=file)

>>> df.drop('text_col', axis=1, inplace=True)
>>> df.info(memory_usage='Deep')
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5 entries, 0 to 4
Data columns (total 2 columns):
int_col      5 non-null int64
float_col    5 non-null float64
dtypes: float64(1), int64(1)
memory usage: 160.0 bytes

See Also
--------

describe: Generate descriptive statistics of DataFrame columns.

################################################################################
################################## Validation ##################################
################################################################################

Docstring for "pandas.DataFrame.info" correct. :)
```

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

Hello @dcanones! Thanks for updating the PR.



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

##### Comment last updated on March 16, 2018 at 20:12 Hours UTC Thanks for your feedback. We will improve this PR asap.

On Sat, Mar 10, 2018, 19:48 Hissashi Rocha <notifications@github.com> wrote:

> *@hissashirocha* commented on this pull request.
>
> There are some errors in the doctring format and in the examples.
> ------------------------------
>
> In pandas/core/frame.py
> <https://github.com/pandas-dev/pandas/pull/20197#discussion_r173627567>:
>
> > +        memory usage: 200.0+ bytes
> +
> +        >>> file = open("df_info.txt", "w", encoding="utf-8")
> +        >>> df.info(buf=file)
> +
> +        >>> df.drop('text_col', axis=1, inplace=True)
> +        >>> df.info(memory_usage='Deep')
> +        <class 'pandas.core.frame.DataFrame'>
> +        RangeIndex: 5 entries, 0 to 4
> +        Data columns (total 2 columns):
> +        int_col      5 non-null int64
> +        float_col    5 non-null float64
> +        dtypes: float64(1), int64(1)
> +        memory usage: 160.0 bytes
> +
> +        See Also
>
> See Also section should go before the Examples section.
> ------------------------------
>
> In pandas/core/frame.py
> <https://github.com/pandas-dev/pandas/pull/20197#discussion_r173627912>:
>
> > @@ -1840,6 +1844,59 @@ def info(self, verbose=None, buf=None, max_cols=None, memory_usage=None,
>              - If True, always show counts.
>              - If False, never show counts.
>
> +        Returns
> +        -------
> +        None: NoneType
> +            This method outputs a summary of a DataFrame and returns None.
>
> It would be more clear to me if it says "This method prints" instead of
> "This method outputs".
> ------------------------------
>
> In pandas/core/frame.py
> <https://github.com/pandas-dev/pandas/pull/20197#discussion_r173629679>:
>
> > @@ -1815,13 +1815,17 @@ def info(self, verbose=None, buf=None, max_cols=None, memory_usage=None,
>          """
>          Concise summary of a DataFrame.
>
> Since info() is a method, it should start with an infinitive verb.
> ------------------------------
>
> In pandas/core/frame.py
> <https://github.com/pandas-dev/pandas/pull/20197#discussion_r173630022>:
>
> > @@ -1815,13 +1815,17 @@ def info(self, verbose=None, buf=None, max_cols=None, memory_usage=None,
>          """
>          Concise summary of a DataFrame.
>
> +        This method shows information about DataFrame type of index, columns
> +        dtypes, non-null values and memory usage.
>
> I'd like to recommend some little changes in the text: "This method shows
> information about a DataFrame: index dtype, ..."
> ------------------------------
>
> In pandas/core/frame.py
> <https://github.com/pandas-dev/pandas/pull/20197#discussion_r173630577>:
>
> > +        Data columns (total 3 columns):
> +        int_col      5 non-null int64
> +        text_col     5 non-null object
> +        float_col    5 non-null float64
> +        dtypes: float64(1), int64(1), object(1)
> +        memory usage: 200.0+ bytes
> +
> +        >>> df.info(verbose=False)
> +        <class 'pandas.core.frame.DataFrame'>
> +        RangeIndex: 5 entries, 0 to 4
> +        Columns: 3 entries, int_col to float_col
> +        dtypes: float64(1), int64(1), object(1)
> +        memory usage: 200.0+ bytes
> +
> +        >>> file = open("df_info.txt", "w", encoding="utf-8")
> +        >>> df.info(buf=file)
>
> We've tried to run this example but it didn't work. In order to make this
> work, it is necessary to give a io.StringIO() object to the 'buf'
> parameter. And then write the StringIO value to a file.
>
> import io
> buf = io.StringIO()
> df2.info(buf=buf)
> s = buf.getvalue()
> file = open("df_info.txt", "w", encoding="utf-8")
> file.write(s)
> ------------------------------
>
> In pandas/core/frame.py
> <https://github.com/pandas-dev/pandas/pull/20197#discussion_r173630874>:
>
> > +        dtypes: float64(1), int64(1), object(1)
> +        memory usage: 200.0+ bytes
> +
> +        >>> df.info(verbose=False)
> +        <class 'pandas.core.frame.DataFrame'>
> +        RangeIndex: 5 entries, 0 to 4
> +        Columns: 3 entries, int_col to float_col
> +        dtypes: float64(1), int64(1), object(1)
> +        memory usage: 200.0+ bytes
> +
> +        >>> file = open("df_info.txt", "w", encoding="utf-8")
> +        >>> df.info(buf=file)
> +        >>> file.close()
> +
> +        >>> df.drop('text_col', axis=1, inplace=True)
> +        >>> df.info(memory_usage='Deep')
>
> The correct parameter is 'deep', not 'Deep'. I'd also like to suggest a
> more detailed explanation of what it does.
> ------------------------------
>
> In pandas/core/frame.py
> <https://github.com/pandas-dev/pandas/pull/20197#discussion_r173630976>:
>
> > +        float_col    5 non-null float64
> +        dtypes: float64(1), int64(1), object(1)
> +        memory usage: 200.0+ bytes
> +
> +        >>> df.info(verbose=False)
> +        <class 'pandas.core.frame.DataFrame'>
> +        RangeIndex: 5 entries, 0 to 4
> +        Columns: 3 entries, int_col to float_col
> +        dtypes: float64(1), int64(1), object(1)
> +        memory usage: 200.0+ bytes
> +
> +        >>> file = open("df_info.txt", "w", encoding="utf-8")
> +        >>> df.info(buf=file)
> +        >>> file.close()
> +
> +        >>> df.drop('text_col', axis=1, inplace=True)
>
> There is no reason to use df.drop in this example.
> ------------------------------
>
> In pandas/core/frame.py
> <https://github.com/pandas-dev/pandas/pull/20197#discussion_r173631020>:
>
> > +        dtypes: float64(1), int64(1), object(1)
> +        memory usage: 200.0+ bytes
> +
> +        >>> df.info(verbose=False)
> +        <class 'pandas.core.frame.DataFrame'>
> +        RangeIndex: 5 entries, 0 to 4
> +        Columns: 3 entries, int_col to float_col
> +        dtypes: float64(1), int64(1), object(1)
> +        memory usage: 200.0+ bytes
> +
> +        >>> file = open("df_info.txt", "w", encoding="utf-8")
> +        >>> df.info(buf=file)
> +        >>> file.close()
> +
> +        >>> df.drop('text_col', axis=1, inplace=True)
> +        >>> df.info(memory_usage='Deep')
>
> Without 'deep'
>
> df2.info()
> <class 'pandas.core.frame.DataFrame'>
> RangeIndex: 300000 entries, 0 to 299999
> Data columns (total 2 columns):
> a 300000 non-null object
> b 300000 non-null object
> dtypes: object(2)
> memory usage: 4.6+ MB <<<<<<<<
>
> With memory_usage='deep'
>
> df2.info(memory_usage = 'deep')
> <class 'pandas.core.frame.DataFrame'>
> RangeIndex: 300000 entries, 0 to 299999
> Data columns (total 2 columns):
> a 300000 non-null object
> b 300000 non-null object
> dtypes: object(2)
> memory usage: 36.7 MB <<<<<<<<<
>
> —
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> Reply to this email directly, view it on GitHub
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>
 Added latest changes. I think it is ready to merge. Pushed a few changes (lines too long, some rewording of parameters).