def performace_table(self,
policy_names: list,
decimals: int,
height: int = 600,
width: int = 900):
"""Table of the result using Bokeh.
Parameters
----------
policy_names : list
List of selected policy names
decimals : int
Number of decimal places to round
height : int
Height of the table
width : int
Width of the table
Returns
-------
None
"""
selected_performance_dict = {
key: self.performance_dict[key]
for key in policy_names
}
table = pd.concat([
pd.DataFrame(v, index=[k]).T
for k, v in selected_performance_dict.items()
],
axis=1)
table.reset_index(inplace=True)
table.rename(columns={"index": "metric"}, inplace=True)
table = table.round(decimals)
Columns = [TableColumn(field=Ci, title=Ci)
for Ci in table.columns] # bokeh columns
data_table = DataTable(columns=Columns,
source=ColumnDataSource(table),
fit_columns=False,
height=height,
width=width) # bokeh table
data_table.index_position = None
show(data_table)
def catalysator(width, height):
df = pd.read_sql(
"""WITH [T] AS (
SELECT [NAZWA], MIN([NEXT_PAY]) AS [NEXT_PAY] FROM [CATALYSATOR]
WHERE [NEXT_PAY] < DATEADD(DAY, 30, GETDATE())
GROUP BY [NAZWA]
)
SELECT [C].[NEXT_PAY] AS [TERMIN], [C].[NAZWA], [ISIN], [CURR_OPR]/100 AS [%], [LICZBA_POZ_OKRESOW] AS [LPO],
"RODZAJ" = CASE
WHEN [FREQ_WYPLAT] = 3 THEN 'Kwartalne'
WHEN [FREQ_WYPLAT] = 6 THEN 'Półroczne'
END
FROM [CATALYSATOR] AS [C], [T]
WHERE [C].[NAZWA] = [T].[NAZWA]
AND [C].[NEXT_PAY] = [T].[NEXT_PAY]
ORDER BY [C].[NEXT_PAY]""", conn)
#dane
source = ColumnDataSource(data=df)
#kolumny
columns = [
TableColumn(field="TERMIN", title="Termin", width=125),
TableColumn(field="NAZWA", title="Emitent"),
TableColumn(field="ISIN", title="ISIN", width=120),
TableColumn(field="RODZAJ", title="Rodzaj", width=120),
TableColumn(field="%",
title="%",
formatter=NumberFormatter(format='0.00%'),
width=50),
TableColumn(field="LPO", title="Poz. wypłat", width=50),
]
#tabela
t = DataTable(source=source, columns=columns, width=width, height=height)
t = finalize_table(t, True, False, False, True)
t.index_position = None
return t
