def dependent_columns(self, dataset):
value = parse_float(self.value)
if value is not None:
return []
# if value is not number or date, add as a column
return [self.value]
def group(self):
"""For when aggregation is called with a group parameter."""
self.column = self.column.apply(lambda value: parse_float(value))
group_dframe = self.dframe[self.groups].join(self.column)
indices = group_dframe.reset_index().set_index(
self.groups + [self.name])
def max_index_for_row(row):
groups = row[self.groups]
value = row[self.name]
xsection = indices.xs(groups, level=self.groups)
if isnan(value):
return minint()
max_index = xsection.get_value(value, 'index')
if isinstance(max_index, Series):
max_index = max_index.max()
return max_index
groupby_max = self._groupby().max().reset_index()
column = groupby_max.apply(max_index_for_row, axis=1).apply(int)
column.name = self.name
return DataFrame(column).join(groupby_max[self.groups])
def group(self):
"""For when aggregation is called with a group parameter."""
self.column = self.column.apply(lambda value: parse_float(value))
group_dframe = self.dframe[self.groups].join(self.column)
indices = group_dframe.reset_index().set_index(
self.groups + [self.name])
def max_index_for_row(row):
groups = row[self.groups]
value = row[self.name]
xsection = indices.xs(groups, level=self.groups)
if isnan(value):
return minint()
max_index = xsection.get_value(value, 'index')
if isinstance(max_index, Series):
max_index = max_index.max()
return max_index
groupby_max = self._groupby().max().reset_index()
column = groupby_max.apply(max_index_for_row, axis=1).apply(int)
column.name = self.name
return DataFrame(column).join(groupby_max[self.groups])
def dependent_columns(self, dataset):
value = parse_float(self.value)
if value is not None:
return []
# if value is not number or date, add as a column
return [self.value]
def eval(self, row, dataset):
value = parse_float(self.value)
if value is not None:
return value
# it may be a variable
field = self.field(row)
# test is date and parse as date
return self.__parse_field(field, dataset)
def eval(self, row, dataset):
value = parse_float(self.value)
if value is not None:
return value
# it may be a variable
field = self.field(row)
# test is date and parse as date
return self.__parse_field(field, dataset)
