API/BUG/ENH: ewmvar/cov debiasing factors; add 'adjust' to ewmvar/std/vol/cov/corr; ewm*() min_periods
Closes https://github.com/pydata/pandas/issues/7911.
Closes https://github.com/pydata/pandas/issues/7912.
Closes https://github.com/pydata/pandas/issues/7977.
Closes https://github.com/pydata/pandas/issues/7900.

These are all fixed simultaneously in order to enable consistency testing across the various functions.

Enhancement -- add `adjust` to `ewm*()` (https://github.com/pydata/pandas/issues/7911):
This code adds `adjust` arguments to `ewmvar`, `ewmstd`, `ewmvol`, `ewmcov`, and `ewmcorr` (`ewma` already had it). If ok, I'd like to reorder the parameters to be more logical and consistent, but for now I just added `adjust=True` to the end of the arguments list.

Bug fix -- `ewmvar/std/cov` debiasing factors (https://github.com/pydata/pandas/issues/7912):
This code corrects the bias correction factor for exponentially weighted (co)variance calculations. The prior factor was the asymptotic value for an infinite number of observations.

As a result of this change, `ewmvar/cov` will now return `NaN` for the (co)variance of a single value when `bias=False`, and `0` when `bias=True`. Previously they always returned `0` for a single value. See also https://github.com/pydata/pandas/issues/7900.

API -- meaning of `min_periods` (https://github.com/pydata/pandas/issues/7977):
The meaning of the `min_periods` argument to the `ewm*()` functions is now consistent with that of the `expanding_*()` functions, i.e. an entry will be `NaN` if the count of non-`NaN`  input values through that point is `<min_periods`. Note that in view of this change, https://github.com/pydata/pandas/issues/7884 / https://github.com/pydata/pandas/pull/7898 is no longer relevant.

Bug fix -- `rolling/expanding_var/std` for a single value (https://github.com/pydata/pandas/issues/7900)
