preventing errors when converting empty index to datetime, converting numbers/strings to boolean

## Installation

```

pip install git+https://git.isis.vanderbilt.edu/SmartBuildings/bdx@v0.2.3

pip install git+https://git.isis.vanderbilt.edu/SmartBuildings/bdx@v0.2.5

```

## Usage

BOOL_MAP = {

    'YES': True, 'Yes': True, 'yes': True, 'TRUE': True, 'True': True, 'true': True, 1: True,

    'NO': False, 'No': False, 'no': False, 'FALSE': False, 'False': False, 'false': False, 0: False

}

def get_trend(trend_id: str, username: str, password: str, start: datetime,

    end: datetime, aggregation: str='Point') -> pd.DataFrame:

    """

def parse_trend_dict(trend_dict: List[Dict[str, Any]]) -> pd.DataFrame:

def parse_trend_dict(trend_dict: List[Dict[str, Any]],

    bool_map: Dict[Any, bool]=BOOL_MAP) -> pd.DataFrame:

    # trend_dict is a list of dictionaries. Each dictionary has the structure:

    # 'propertyName': str, short property name e.g vfdPower

    # 'label': str, qualified property name e.g. 'Cell_1bFan vfdPower'

                          .format(time_series['label']))

            series_df = pd.DataFrame({'time': []})

        series_df.set_index('time', inplace=True)

        # Try to convert boolean fields into boolean types

        if 'boolValue' in series_df:

            try:

                series_df['boolValue'] = series_df['boolValue'].map(bool_map).astype('bool')

            except Exception as e:

                warnings.warn(('Failed to convert a boolean field "{}" to boolean '

                               'type. Leaving as-is.'.format(time_series['label'])))

        # If dataframe does not have 'realValue', 'boolValue' column, it means that the

        # whole series was missing values (valueType='NULL'). So a placeholder

        # column is created with NaN values. These can then be handled on

        # per-column basis in the final DataFrame:

        # per-column basis in the final DataFrame

        if ('realValue' not in series_df) and ('boolValue' not in series_df):

            series_df['nullValue'] = np.nan

        series_df.rename(columns={'realValue': time_series['label'],

        series_df.drop(columns='valueType', inplace=True, errors='ignore')

        frames.append(series_df)

    df = pd.concat(frames, axis='columns', join='outer', sort=True)

    if len(df) > 0:

        df.index = pd.to_datetime(df.index)

    return df

 No newline at end of file

setup(name='bdx',

      version='0.2.4',

      version='0.2.5',

      description='Download trends from Building Logix data exchange (BDX)',

      author='Ibrahim Ahmed',

      author_email='ibrahim.ahmed@vanderbilt.edu',