Fixes an incorrect order in examples.
Removes documentation references to pavement.

The references to pavement were causing confusion on what libraries
are needed for installation.
Update zipline/transforms/stddev.py

Fixed typo.
Merge pull request #70 from bernarpa/patch-1

Update zipline/transforms/stddev.py
Merge pull request #69 from mjhanninen/fix-example

Fixes an incorrect order in examples.
Change flag value on unit tests that use market_aware==False.

Changes these tests to use market_aware==True, so that unit tests
follow the same code path as actual execution.

All use of EventWindows against data follows market_aware behavior.

These tests are the only use of market_aware==False, so heading
down the path of removing market aware completely.
Removes unused test transform.
Deprecates market_aware and delta kwargs to EventWindow.

The eventual goal is to remove the market_aware and delta kwargs,
but removing the kwarg completely would break the init
method of EventWindow based classes for existing algorithms.

In the meantime, this ensures that only market_aware is only ever
set to True and raises an error if it is False.

Also raises exceptions if values are set for delta, which was only
used if market_aware was False

Also, since the logic for checking window length is changed,
because in market aware mode we should always be checking the
window length, this adds some sanity checking to the window length.
Changes stddev and vwap transforms to accept parameters as kwargs.

So that algorithms that specifiy market_aware, days and delta
as args can be transitioned to just specifying a window_length kwarg.

Moving towards removing market_aware and delta completely.
Update README.md
Fixes New Year's holidays inclusion in trading calendar.

If NYE lands on the weekend, the Monday following is a holiday.
deleting the portfolio object from every event.
Adds dividends to performance tracking.

Algorithm returns and the risk calculations that depend on them now include
cash dividends. This commit does _not_ provide an API for user algorithms to
access dividends.

PerformanceTracker expects the dividend data to arrive as events, similar to
the way that Trades arrive. Dividends are expected to have adjusted payment
amounts that are inline with adjusted trades.

PerformanceTracker maintains state of all the unpaid dividends in the position
objects held in PerformancePeriod. Dividend objects contain all the relevant
dates (declared, ex, payment) as well as net and gross amounts. Dividends are
removed from the list as they are paid. Cash flow is not incremented until the
payment day. This creates the possibility of a dividend being owed but not
paid or realized before the end of a test. For example, a dividend with an
ex_date of today may have a pay date 2 weeks in the future. Right now the
algorithm does not receive any credit for unpaid dividends.

Tests cover buying/selling around the ex_date and payment_date, and checking
that the performance calculated is as expected.
Implemented dividend costs for short positions.
Based on user feedback in Quantopian forums:
https://www.quantopian.com/posts/total-return-slash-dividends
Merge pull request #76 from quantopian/dividends_for_shorts

Implemented dividend costs for short positions.
Emergency fix - filtering down to TRADE events in the transforms.
Checks to make sure that an Event has a type before checking type.

The Dividend event is currently missing 'type', causing the type
check to fail.

TODO: Add a type to Dividends.
Converts batch transform panel to use pd.Panel dictionary arg.

Based on @twiecki's work in batch_to_pandas branch.