def build_erf_aggregates(variables=None, year=2006, unit=1e6):
"""
Fetch the relevant aggregates from erf data
"""
erf = DataCollection(year=year)
if variables is not None and "wprm" not in variables:
variables.append("wprm")
print 'Fetching aggregates from erf %s data' % str(year)
df = erf.get_of_values(variables=variables, table="erf_menage")
of2erf = get_of2erf()
erf2of = get_erf2of()
df.rename(columns=erf2of, inplace=True)
wprm = df["wprm"]
for col in df.columns:
try:
df[col] = df[col].astype(np.float64)
except:
pass
df = df.mul(wprm, axis=0)
for col in list(set(df.columns) - set(['ident', 'wprm'])):
try:
df[col] = df[col].sum() / 1e6
except:
pass
return df.ix[0:1] # Aggregate so we only need 1 row
def build_erf_aggregates(variables = None, year = 2006, unit = 1e6):
"""
Fetch the relevant aggregates from erf data
"""
erf = DataCollection(year=year)
if variables is not None and "wprm" not in variables:
variables.append("wprm")
print 'Fetching aggregates from erf %s data' %str(year)
df = erf.get_of_values(variables=variables, table = "erf_menage")
of2erf = get_of2erf()
erf2of = get_erf2of()
df.rename(columns = erf2of, inplace = True)
wprm = df["wprm"]
for col in df.columns:
try:
df[col] = df[col].astype(np.float64)
except:
pass
df = df.mul(wprm, axis = 0)
for col in list(set(df.columns) - set(['ident', 'wprm'])):
try:
df[col] = df[col].sum()/1e6
except:
pass
return df.ix[0:1] # Aggregate so we only need 1 row
def get_of_values(self, variables=None, table=None):
"""
Get values
Parameters
----------
variables : list of strings, default None
list of variables names, if None return the whole table
table : string, default None
name of the table where to get the variables
Returns
-------
df : DataFrame, default None
A DataFrame containing the variables
"""
store = HDFStore(self.hdf5_filename)
df = store[str(self.year) + "/" + table]
# If no variables read the whole table
if variables is None:
return df
from openfisca_france.data.erf import get_erf2of, get_of2erf
of2erf = get_of2erf()
to_be_renamed_variables = set(of2erf.keys()).intersection(variables)
renamed_variables = []
for variable in to_be_renamed_variables:
renamed_variables.append(of2erf[variable])
if renamed_variables:
variables = list(
set(variables).difference(
to_be_renamed_variables)) + renamed_variables
# if table is None:
# for test_table in self.tables.keys:
# if set(variables) < set(self.tables[test_table].columns):
# table = test_table
# print "using guessed table :", table
# break
#
# if table is None:
# print "varname not found in any tables"
# df = None
# else:
variables = list(set(variables).intersection(df.columns))
df = df[variables]
# rename variables according to their name in openfisca
erf2of = get_erf2of()
to_be_renamed_variables = set(erf2of.values()).intersection(variables)
if to_be_renamed_variables:
for var in to_be_renamed_variables:
df.rename(columns={var: erf2of[var]}, inplace=True)
return df
def get_of_values(self, variables=None, table=None):
"""
Get values
Parameters
----------
variables : list of strings, default None
list of variables names, if None return the whole table
table : string, default None
name of the table where to get the variables
Returns
-------
df : DataFrame, default None
A DataFrame containing the variables
"""
store = HDFStore(self.hdf5_filename)
df = store[str(self.year)+"/"+table]
# If no variables read the whole table
if variables is None:
return df
from openfisca_france.data.erf import get_erf2of, get_of2erf
of2erf = get_of2erf()
to_be_renamed_variables = set(of2erf.keys()).intersection(variables)
renamed_variables = []
for variable in to_be_renamed_variables:
renamed_variables.append(of2erf[variable])
if renamed_variables:
variables = list( set(variables).difference(to_be_renamed_variables)) + renamed_variables
# if table is None:
# for test_table in self.tables.keys:
# if set(variables) < set(self.tables[test_table].columns):
# table = test_table
# print "using guessed table :", table
# break
#
# if table is None:
# print "varname not found in any tables"
# df = None
# else:
variables = list( set(variables).intersection(df.columns))
df = df[variables]
# rename variables according to their name in openfisca
erf2of = get_erf2of()
to_be_renamed_variables = set(erf2of.values()).intersection(variables)
if to_be_renamed_variables:
for var in to_be_renamed_variables:
df.rename(columns = {var: erf2of[var]}, inplace=True)
return df
