text: Title: bar df data type issues when converting
  Body: In Entity.py,
  You are converting the timestamp by multiply 1e9 and this cause the datatype to change to Float64 which is not accepted in the panda library and returns TypeError.
   
  Can we do something like this?
  ```
  if not df.empty:
                  df.index = pd.to_datetime(
                      (df.index * 1e9).astype('int64'), utc=True,
                  ).tz_convert(NY)
  ```
  File "/Users/jiawensun/Alpaca/samplealgo/algo.py", line 59, in _get_prices
  return barset.df
  File "/usr/local/lib/python3.7/site-packages/alpaca_trade_api/entity.py", line 107, in df
  df = bars.df.copy()
  File "/usr/local/lib/python3.7/site-packages/alpaca_trade_api/entity.py", line 85, in df
  df.index * 1e9, utc=True,
  File "/usr/local/lib/python3.7/site-packages/pandas/core/tools/datetimes.py", line 603, in to_datetime
  result = convert_listlike(arg, box, format)
  File "/usr/local/lib/python3.7/site-packages/pandas/core/tools/datetimes.py", line 223, in _convert_listlike_datetimes
  arg, _ = maybe_convert_dtype(arg, copy=False)
  File "/usr/local/lib/python3.7/site-packages/pandas/core/arrays/datetimes.py", line 1914, in maybe_convert_dtype
  data = data.astype(_NS_DTYPE)
  File "/usr/local/lib/python3.7/site-packages/pandas/core/indexes/numeric.py", line 330, in astype
  raise TypeError(msg)
  TypeError: Cannot convert Float64Index to dtype datetime64[ns]; integer values are required for conversion