def get_data(self, latitude, longitude, start, end,<EOL>vert_level=None, query_variables=None,<EOL>close_netcdf_data=True):
if not self.connected:<EOL><INDENT>self.connect_to_catalog()<EOL><DEDENT>if vert_level is not None:<EOL><INDENT>self.vert_level = vert_level<EOL><DEDENT>if query_variables is None:<EOL><INDENT>self.query_variables = list(self.variables.values())<EOL><DEDENT>else:<EOL><INDENT>self.query_variables = query_variables<EOL><DEDENT>self.latitude = latitude<EOL>self.longitude = longitude<EOL>self.set_query_latlon()  <EOL>self.set_location(start, latitude, longitude)<EOL>self.start = start<EOL>self.end = end<EOL>self.query.time_range(self.start, self.end)<EOL>if self.vert_level is not None:<EOL><INDENT>self.query.vertical_level(self.vert_level)<EOL><DEDENT>self.query.variables(*self.query_variables)<EOL>self.query.accept(self.data_format)<EOL>self.netcdf_data = self.ncss.get_data(self.query)<EOL>self.data = self._netcdf2pandas(self.netcdf_data, self.query_variables,<EOL>self.start, self.end)<EOL>if close_netcdf_data:<EOL><INDENT>self.netcdf_data.close()<EOL><DEDENT>return self.data<EOL>
Submits a query to the UNIDATA servers using Siphon NCSS and
converts the netcdf data to a pandas DataFrame.

Parameters
----------
latitude: float
    The latitude value.
longitude: float
    The longitude value.
start: datetime or timestamp
    The start time.
end: datetime or timestamp
    The end time.
vert_level: None, float or integer, default None
    Vertical altitude of interest.
query_variables: None or list, default None
    If None, uses self.variables.
close_netcdf_data: bool, default True
    Controls if the temporary netcdf data file should be closed.
    Set to False to access the raw data.

Returns
-------
forecast_data : DataFrame
    column names are the weather model's variable names.