def agg(self, agg_types):
df = DataFrame()
by = []
if self.level is not None:
if isinstance(self.source_series.index, MultiIndex):
# Add index columns specified by multiindex into _df
# Record the index column names for the groupby
for col in self.source_series.index.codes:
df[self.group_name + col] = self.source_series.index.codes[
col]
by.append(self.group_name + col)
else:
if isinstance(self.group_keys, Series):
df[self.group_name] = self.group_keys
by = self.group_name
else:
df = self.group_keys
by = self._by
df[self.source_name] = self.source_series
groupby = df.groupby(by).agg(agg_types)
idx = groupby.index
if len(groupby.columns) == 1:
result = groupby[self.source_name]
result.name = self.source_series.name
idx.name = None
result = result.set_index(idx)
else:
idx.name = self.group_name
result = groupby.set_index(idx)
if len(result) == 0 and self._by is not None:
empties = [[] for x in range(len(self._by))]
mi = MultiIndex(empties, empties, names=self._by)
result = result.set_index(mi)
return result
def __getattr__(self, attr):
df = DataFrame()
df[self.source_name] = self.source_series
by = []
if self.level is not None:
if isinstance(self.source_series.index, MultiIndex):
# Add index columns specified by multiindex into _df
# Record the index column names for the groupby
for col in self.source_series.index.codes:
df[self.group_name +
col] = self.source_series.index.codes[col]
by.append(self.group_name + col)
else:
df[self.group_name] = self.group_series
by = self.group_name
groupby = df.groupby(by, level=self.level, sort=self.sort)
result_df = getattr(groupby, attr)()
def get_result():
result_series = result_df[self.source_name]
result_series.name = self.source_name if self.source_name !=\
'_x' else None
idx = result_df.index
idx.name = self.group_name if self.group_name != '_y' else None
result_series.set_index(idx)
return result_series
return get_result
def agg(self, agg_types):
df = DataFrame()
df['x'] = self.source_series
if self.level is not None:
df['y'] = self.source_series.index
else:
df['y'] = self.group_series
groupby = df.groupby('y').agg(agg_types)
idx = groupby.index
idx.name = None
groupby.set_index(idx)
return groupby
def __getattr__(self, attr):
df = DataFrame()
df['x'] = self.source_series
if self.level is not None:
df['y'] = self.source_series.index
else:
df['y'] = self.group_series
groupby = df.groupby('y', level=self.level, sort=self.sort)
result_df = getattr(groupby, attr)()
def get_result():
result_series = result_df['x']
result_series.name = None
idx = result_df.index
idx.name = None
result_series.set_index(idx)
return result_series
return get_result
def __getattr__(self, attr):
df = DataFrame()
by = []
if self.level is not None:
if isinstance(self.source_series.index, MultiIndex):
# Add index columns specified by multiindex into _df
# Record the index column names for the groupby
for col in self.source_series.index.codes:
df[self.group_name + col] = self.source_series.index.codes[
col]
by.append(self.group_name + col)
else:
if isinstance(self.group_keys, Series):
df[self.group_name] = self.group_keys
by = self.group_name
else:
df = self.group_keys
by = self._by
df[self.source_name] = self.source_series
groupby = df.groupby(by,
level=self.level,
sort=self.sort)
if attr in ['sum', 'min', 'max', 'mean', 'count', 'agg']:
result_df = getattr(groupby, attr)()
else:
return getattr(groupby, attr)
def get_result():
result_series = result_df[self.source_name]
result_series.name = self.source_name if self.source_name !=\
_LEVEL_0_DATA_NAME else None
if len(result_df) == 0 and self._by is not None:
empties = [[] for x in range(len(self._by))]
mi = MultiIndex(empties, empties, names=self._by)
result_series = result_series.set_index(mi)
else:
idx = result_df.index
if self.group_name == _LEVEL_0_INDEX_NAME:
idx.name = None
result_series = result_series.set_index(idx)
return result_series
return get_result
