def get_dataframe(self, columns: Optional[Iterable] = None) -> DataFrame:
if pd and get_use_objects_for_output():
if columns:
dataframe = DataFrame(self.get_items(), columns=columns)
columns = arg.get_names(columns)
dataframe = dataframe[columns]
else:
dataframe = DataFrame(self.get_items())
return dataframe
def get_dataframe(self, columns: Optional[Iterable] = None) -> DataFrame:
if columns and hasattr(self, 'select'):
data = self.select(*columns).get_data()
else:
data = self.get_data()
if DataFrame:
return DataFrame(data)
def get_dataframe(self, columns: Columns = None) -> DataFrame:
if pd and get_use_objects_for_output():
dataframe = DataFrame(self.get_items())
if arg.is_defined(columns):
columns = arg.get_names(columns)
dataframe = dataframe[columns]
return dataframe
def take(self, count: Union[int, bool] = 1) -> Native:
if isinstance(count, bool):
if count:
return self
else:
return self.stream(DataFrame())
elif isinstance(count, int):
return self.stream(self.get_dataframe().head(count), )
else:
raise TypeError(
'Expected count as int or bool, got {}'.format(count))
def __init__(
self,
data,
name=arg.AUTO,
source=None,
context=None,
):
assert pd, 'Pandas must be installed and imported for instantiate PandasStream (got fallback {})'.format(
pd)
if isinstance(data,
DataFrame) or data.__class__.__name__ == 'DataFrame':
dataframe = data
elif hasattr(data, 'get_dataframe'): # isinstance(data, RecordStream):
dataframe = data.get_dataframe()
else: # isinstance(data, (list, tuple)):
dataframe = DataFrame(data=data)
super().__init__(
dataframe,
name=name,
source=source,
context=context,
)
def get_dataframe(self) -> DataFrame:
data = self.get_struct_description(include_header=True)
columns = ('n', 'type', 'name', 'caption', 'valid')
return DataFrame(data, columns=columns)
def add_items(self, items: Iterable, before: bool = False) -> Native:
dataframe = DataFrame(items)
return self.add_dataframe(dataframe, before)
def get_dataframe(self, columns: Optional[Iterable] = None) -> DataFrame:
df = DataFrame(self.get_data())
if df and columns:
df = df[columns]
return df