def test_dump_all(self):
from ambry import get_library
from censuslib.dimensions import classify
l = get_library()
p = l.partition('census.gov-acs-p5ye2014-b01001')
for c in p.table.columns:
if c.name == 'id':
continue
if not c.name.endswith('_m90'):
print c.name, classify(c)
def dim_columns(self, pred):
"""
Return a list of columns that have a particular value for age,
sex and race_eth. The `pred` parameter is a string of python
code which is evaled, with the classification dict as the local
variable context, so the code string can access these variables:
- sex
- age
- race-eth
- col_num
Col_num is the number in the last three digits of the column name
Some examples of predicate strings:
- "sex == 'male' and age != 'na' "
:param pred: A string of python code that is executed to find column matches.
"""
from censuslib.dimensions import classify
out_cols = []
for i, c in enumerate(self.partition.table.columns):
if c.name.endswith('_m90'):
continue
if i < 9:
continue
cf = classify(c)
cf['col_num'] = int(c.name[-3:])
if eval(pred, {}, cf):
out_cols.append(c.name)
return out_cols
