BUG: Fix pandas.io.data.Options for change in format of Yahoo Option page
This should fix #8612.
Will need a sample of a during the week HTML to make sure that the underlying price and quote time work with that format.  I'll update for that on Monday.

Yahoo has weekly and month end options. So, please dont assume that expiry happen on the third friday of the month. 
 I'm not assuming that.  If you provide only a month and year, it defaults to the third friday expiry.  If you provide an expiry date, it will find the closest one to the date you provide.
 Before year-month, gave you all expirations within that month. 

From:
http://stackoverflow.com/questions/5493514/webscraping-with-beautifulsoup-or-lxml-html

data['models']['applet_model']['data']['optionData']['expirationDates']

gives you all expirations... These need Unix time stamp, Then no expiration dates are missed..
 I guess its an API question.  Maybe giving a month and year should provide all the expiries for that month.   On the other hand, month and year have had a deprecation warning for a long time, so maybe this should be the catalyst to drop it.  We could add another method that gets all options for a given month.
 @dstephens99 can you put a release note in v0.15.1.txt (I guess its a Bug fix). pls squash as well.
 Will do.  Any thoughts on whether we should put a note in the API change section? Calling methods using a year and month reference used to provide all the data for expiries within that year / month.   Now, with Yahoo splitting it on different pages, I default it to the standard (third Saturday) expiry.  

However, using year and month has been deprecated for a year and a half.  At what point do we remove deprecated options from the code base? This may be a good catalyst for removing it.

It may be worthwhile to add either a method of an parameter which get all data for a given month.  I'm happy to add that if someone wants it.
 does it show a Deprecation warning now?
can u show a small example of what u mean? u r defaulting to the next expiry of no month is specified?
 Yes, it shows a deprecation warning now.  

It defaults to the next expiry if no date arguments are given.  If you give a date, it gives the you next expiry after that date.  If you give a month and year, it gives you the 'standard' third saturday expiry.  

Here is an example:

``` python

from pandas.io.data import Options
aapl = Options('aapl', 'yahoo')
aapl.get_call_data(month=11,year=2014).iloc[0:5,0:5]
pandas/io/data.py:939: FutureWarning: month, year arguments are deprecated, use expiry instead
  " instead", FutureWarning)
Out[4]: 
                                             Last    Bid    Ask  Chg PctChg
Strike Expiry     Type Symbol                                              
47.5   2014-11-22 call AAPL141122C00047500  58.65  58.85  60.90    0  0.00%
50.0   2014-11-22 call AAPL141122C00050000  53.90  56.35  58.40    0  0.00%
55.0   2014-11-22 call AAPL141122C00055000  44.50  51.35  53.05    0  0.00%
60.0   2014-11-22 call AAPL141122C00060000  36.85  46.35  48.05    0  0.00%
65.0   2014-11-22 call AAPL141122C00065000  34.95  41.35  43.05    0  0.00%



aapl.get_call_data().iloc[0:5,0:5]
Out[6]: 
                                             Last    Bid    Ask   Chg   PctChg
Strike Expiry     Type Symbol                                                 
75     2014-10-31 call AAPL141031C00075000  31.15  32.15  32.55  0.00    0.00%
80     2014-10-31 call AAPL141031C00080000  26.25  27.15  27.50  0.00    0.00%
85     2014-10-31 call AAPL141031C00085000  22.20  22.20  22.45  0.63   +2.92%
86     2014-10-31 call AAPL141031C00086000  19.00  20.35  22.40  0.00    0.00%
87     2014-10-31 call AAPL141031C00087000  20.15  20.15  20.45  1.95  +10.71%

import datetime
expiry = datetime.date(2014,11,10)

aapl.get_call_data(expiry=expiry).iloc[0:5,0:5]
Out[8]: 
                                             Last    Bid    Ask  Chg PctChg
Strike Expiry     Type Symbol                                              
80     2014-11-14 call AAPL141114C00080000  22.75  26.35  28.40    0  0.00%
84     2014-11-14 call AAPL141114C00084000  20.99  22.35  24.40    0  0.00%
85     2014-11-14 call AAPL141114C00085000  21.30  21.35  23.40    0  0.00%
86     2014-11-14 call AAPL141114C00086000  16.08  20.35  22.45    0  0.00%
87     2014-11-14 call AAPL141114C00087000  18.10  19.35  21.45    0  0.00%
```
 I know this might be a bit annoying, but is it possible to return the data for all expiry dates if a year/month is specified (e.g. return more data rather than less)?

Is their an easy way to get expiry dates? (in a particular date range)?
 Yes, we can do that.  It will just require up to 5 page loads, so a bit slower. 

I have a private method that gets the listed expiry dates from the yahoo page, I will make that one public.
 hmm ok what you have is prob reasonable then

can u rebase and maybe out a note in the whatsnew  (just that format changed) and that the year month behavior is now slightly I different (but is deprecated anyhow) (and out same note in remote.rst)
 @jorisvandenbossche ?
 @dstephens99 I am not familiar with this part of pandas, but is there now an actual change in behaviour for some cases? (different output than before with certain arguments) 
As the whatsnew entry now only says it fixed the yahoo format change
 @jorisvandenbossche 
Yes, there is a difference in behaviour.  I've updated the whatsnew entry. 
 @dstephens99 minor docs changes, otherwise looking good. pls png when green
 I was thinking it may be worthwhile to undeprecate year & month and use that as the API for getting all data in a  month.  Given that there is no other way to do it (other than a user writing a loop) and a different API would be clumsy (adding another method).

Alternatively (or perhaps in addition), I could make expiry take a list/range of dates (as well as an individual date), so a user could be specific about what expiry dates they want data for.

Thoughts?  Thanks.  Sorry to beat a dead horse on this API question.   
 @dstephens99 If its not crazy intesive (perf or dev time!) to make year/month 'work' to get all expiry's in that range would be great. (and then expiry to take multiple expiry's also great).

We are trying to release 0.15.1 next week. So if you can revert asap on this in whatever you think you can get done.
 No prob.  I refactored it already so the function that does all the work takes lists.    Will get a new version out today.
 @jreback 
Green with discussed new features.   Note that this also closes #8052.
 @jreback  
Fixed those docstring comments, also pd.to_datetime in the validate expiry function.
I had a typo in my previous comment - this closes #8052, not #8053.
 @jorisvandenbossche anything final on this?
 good for me!
 thanks!

pls look at built docs on dev site
takes about 1 hr
 @dstephens99 There are errors in the docs (all the same): `RemoteDataError: Unable to determine time of quote for page http://finance.yahoo.com/q/op?s=AAPL&date=1415318400`
 @jreback @jorisvandenbossche 
Guys, did you consider moving some sub-packages to separate libraries? I mean, it will come at a cost of increased maintenance overhead, but untying release cycles should simplify bugfixes and speed up their propagation to users. In this particular case, given that yahoo may decide to change their UI arbitrarily, the users at any moment may be left with a choice either to wait for up to three months till the next release or to switch to master branch.
 @immerrr are you offering??

sure I think some parts of remote_data access could certainly be outsourced to a separate repo
 @immerrr exactly my thought also (eg now, yahoo broke right after 0.15 was released, so fix has to wait untill the next release and all yahoo related code does not work with 0.15). But let's discuss this is a separate issue
 @dstephens99 Small question about the `expiry_dates` that @jreback raised. It does now return a list of `datetime.date` values. But another option is to return `Timestamp`s? 
I am not having a real preference, and I don't know if there are any precedences in pandas.
 I used dates because there is no time associated with the expiry.  When I'm comparing what was input to what dates are available, I need to compare dates with dates, not with datetimes or timestamps, unless I was sure the datetimes and timestamps had consistent times.

I'm happy to change it to timestamps, I'm not sure if there is a benefit/drawback either way, but would likely change it to dates in the comparison logic.
 @dstephens99 its not a big deal either way. Timestamps can represent both (dates and datetimes). And are generally used within pandas. But `datetimes` are converted whenever used anyhow. Its fine.
