def to_frame(tables, cfg, additional_columns=[]):
cfg = yaml_to_class(cfg).from_yaml(str_or_buffer=cfg)
tables = [t for t in tables if t is not None]
columns = misc.column_list(tables, cfg.columns_used()) + additional_columns
if len(tables) > 1:
df = sim.merge_tables(target=tables[0].name,
tables=tables, columns=columns)
else:
df = tables[0].to_frame(columns)
df = deal_with_nas(df)
return df
def to_frame(tables, cfg, additional_columns=[]):
cfg = yaml_to_class(cfg).from_yaml(str_or_buffer=cfg)
tables = [t for t in tables if t is not None]
columns = misc.column_list(tables, cfg.columns_used()) + additional_columns
if len(tables) > 1:
df = orca.merge_tables(target=tables[0].name,
tables=tables, columns=columns)
else:
df = tables[0].to_frame(columns)
df = deal_with_nas(df)
return df
def to_frame(tbl, join_tbls, cfg, additional_columns=[]):
"""
Leverage all the built in functionality of the sim framework to join to
the specified tables, only accessing the columns used in cfg (the model
yaml configuration file), an any additionally passed columns (the sim
framework is smart enough to figure out which table to grab the column
off of)
Parameters
----------
tbl : DataFrameWrapper
The table to join other tables to
join_tbls : list of DataFrameWrappers or strs
A list of tables to join to "tbl"
cfg : str
The filename of a yaml configuration file from which to parse the
strings which are actually used by the model
additional_columns : list of strs
A list of additional columns to include
Returns
-------
A single DataFrame with the index from tbl and the columns used by cfg
and any additional columns specified
"""
join_tbls = join_tbls if isinstance(join_tbls, list) else [join_tbls]
tables = [tbl] + join_tbls
cfg = yaml_to_class(cfg).from_yaml(str_or_buffer=cfg)
tables = [t for t in tables if t is not None]
columns = misc.column_list(tables, cfg.columns_used()) + additional_columns
if len(tables) > 1:
df = orca.merge_tables(target=tables[0].name,
tables=tables,
columns=columns)
else:
df = tables[0].to_frame(columns)
check_nas(df)
return df
def to_frame(tbl, join_tbls, cfg, additional_columns=[]):
"""
Leverage all the built in functionality of the sim framework to join to
the specified tables, only accessing the columns used in cfg (the model
yaml configuration file), an any additionally passed columns (the sim
framework is smart enough to figure out which table to grab the column
off of)
Parameters
----------
tbl : DataFrameWrapper
The table to join other tables to
join_tbls : list of DataFrameWrappers or strs
A list of tables to join to "tbl"
cfg : str
The filename of a yaml configuration file from which to parse the
strings which are actually used by the model
additional_columns : list of strs
A list of additional columns to include
Returns
-------
A single DataFrame with the index from tbl and the columns used by cfg
and any additional columns specified
"""
join_tbls = join_tbls if isinstance(join_tbls, list) else [join_tbls]
tables = [tbl] + join_tbls
cfg = yaml_to_class(cfg).from_yaml(str_or_buffer=cfg)
tables = [t for t in tables if t is not None]
columns = misc.column_list(tables, cfg.columns_used()) + additional_columns
if len(tables) > 1:
df = orca.merge_tables(target=tables[0].name,
tables=tables, columns=columns)
else:
df = tables[0].to_frame(columns)
check_nas(df)
return df