def _add_rolling_table(self):
dtos = RollingAnalysisFactory.calculate_analysis(self.strategy_series, self.benchmark_series)
column_names = [
Table.ColumnCell("Rolling Return Period", css_class="left-align"),
"Strategy Average",
"Strategy Worst",
Table.ColumnCell("Strategy Best", css_class="right-align"),
"Benchmark Average",
"Benchmark Worst",
Table.ColumnCell("Benchmark Best", css_class="right-align"),
Table.ColumnCell("% Strategy outperform Benchmark")]
result = Table(column_names, grid_proportion=GridProportion.Sixteen, css_class="table rolling-table")
for dto in dtos:
result.add_row([Table.Cell(dto.period, css_class="right-align"),
Table.Cell(dto.strategy_average, "{:.2%}"),
Table.Cell(dto.strategy_worst, "{:.2%}"),
Table.Cell(dto.strategy_best, "{:.2%}"),
Table.Cell(dto.benchmark_average, "{:.2%}"),
Table.Cell(dto.benchmark_worst, "{:.2%}"),
Table.Cell(dto.benchmark_best, "{:.2%}"),
Table.Cell(dto.percentage_difference, "{:.2%}")])
self.document.add_element(result)
def populate_table(self, table: Table, name=None) -> None:
"""
Adds the data calculated in this analysis to the specified table. The table may be brand new or contain other
analyses of the same kind.
Parameters
----------
table
The table to add the data to.
name
Name to give this analysis in the columns.
"""
new_table = Table()
if name is None:
name = self.returns_tms.name
new_table.set_column_names(["Statistic", name])
for item in self._get_results_list():
row_name = item[1] + " [" + item[3] + "]"
if item[3] == '':
row_name = item[1]
new_table.add_row([row_name, Table.Cell(item[2])])
if len(table.rows) != 0:
new_table = table.combine(new_table)
table.set_column_names(new_table.get_column_names())
table.rows = new_table.rows