def compare_df(df: pd.DataFrame, chart_type: ChartType = ChartType.line):
"""
compare indicators(columns) of entities in df
:param df: normal df
:param chart_type:
"""
drawer = Drawer(main_df=df)
drawer.draw(main_chart=chart_type, show=True)
def compare(entity_ids, schema_map_columns: dict = None, chart_type: ChartType = ChartType.line):
entity_type_map_ids = _group_entity_ids(entity_ids=entity_ids)
dfs = []
for entity_type in entity_type_map_ids:
if schema_map_columns:
for schema in schema_map_columns:
columns = ["entity_id", "timestamp"] + schema_map_columns.get(schema)
df = schema.query_data(entity_ids=entity_type_map_ids.get(entity_type), columns=columns)
dfs.append(df)
else:
schema = get_kdata_schema(entity_type=entity_type)
df = schema.query_data(entity_ids=entity_type_map_ids.get(entity_type))
dfs.append(df)
all_df = pd.concat(dfs)
if schema_map_columns:
drawer = Drawer(main_df=all_df)
drawer.draw(main_chart=chart_type, show=True)
else:
drawer = Drawer(main_df=all_df, sub_df_list=[all_df[["entity_id", "timestamp", "turnover"]].copy()])
drawer.draw_kline(show=True)
def compare(
entity_ids=None,
codes=None,
schema=None,
columns=None,
schema_map_columns: dict = None,
chart_type: ChartType = ChartType.line,
start_timestamp=None,
scale_value: int = None,
):
"""
compare indicators(columns) of entities
:param entity_ids:
:param codes:
:param schema:
:param columns:
:param schema_map_columns: key represents schema, value represents columns
:param chart_type: "line", "area", "scatter", default "line"
:param start_timestamp: "
:param scale_value: compare with same value which scaled to scale_value
"""
dfs = []
# default compare kdata
if schema_map_columns is None and schema is None:
entity_type_map_ids = _group_entity_ids(entity_ids=entity_ids)
for entity_type in entity_type_map_ids:
schema = get_kdata_schema(entity_type=entity_type)
df = schema.query_data(
entity_ids=entity_type_map_ids.get(entity_type),
start_timestamp=start_timestamp)
dfs.append(df)
all_df = pd.concat(dfs)
drawer = Drawer(main_df=all_df,
sub_df_list=[
all_df[["entity_id", "timestamp",
"turnover"]].copy()
])
drawer.draw_kline(show=True, scale_value=scale_value)
else:
if schema_map_columns:
for schema in schema_map_columns:
columns = ["entity_id", "timestamp"
] + schema_map_columns.get(schema)
df = schema.query_data(entity_ids=entity_ids,
codes=codes,
columns=columns,
start_timestamp=start_timestamp)
dfs.append(df)
elif schema:
columns = ["entity_id", "timestamp"] + columns
df = schema.query_data(entity_ids=entity_ids,
codes=codes,
columns=columns,
start_timestamp=start_timestamp)
dfs.append(df)
all_df = pd.concat(dfs)
drawer = Drawer(main_df=all_df)
drawer.draw(main_chart=chart_type, show=True, scale_value=scale_value)
