In [1]:
%load_ext autoreload
%autoreload 2
from synthpop.recipes.starter2 import Starter
from synthpop.synthesizer import synthesize_all, enable_logging
import os
import pandas as pd
#enable_logging()
In [2]:
def synthesize_counties(counties):
for county in counties:
starter = Starter(os.environ["CENSUS"], "CA", county)
synthesize_all(starter)
%time hh = synthesize_counties(["Santa Clara County", "Solano County", "San Mateo County", "Marin County", "San Francisco County", "Napa County", "Sonoma County", "Contra Costa County", "Alameda County"])
---------------------------------------------------------------------------
KeyboardInterrupt Traceback (most recent call last)
<timed exec> in <module>()
<ipython-input-2-ac36fb532fea> in synthesize_counties(counties)
1 def synthesize_counties(counties):
2 for county in counties:
----> 3 starter = Starter(os.environ["CENSUS"], "CA", county)
4 synthesize_all(starter)
5 get_ipython().run_line_magic('time', 'hh = synthesize_counties(["Santa Clara County", "Solano County", "San Mateo County", "Marin County", "San Francisco County", "Napa County", "Sonoma County", "Contra Costa County", "Alameda County"])')
c:\users\juan\documents\github\synthpop\synthpop\recipes\starter2.py in __init__(self, key, state, county, tract)
69 block_group_size_attr="B11005_001E",
70 tract_size_attr="B08201_001E",
---> 71 tract=tract)
72 self.h_acs = h_acs
73
c:\users\juan\documents\github\synthpop\synthpop\census_helpers.py in block_group_and_tract_query(self, block_group_columns, tract_columns, state, county, merge_columns, block_group_size_attr, tract_size_attr, tract, year)
110 tract_size_attr, tract=None, year=2016):
111 df2 = self.tract_query(tract_columns, state, county, tract=tract,
--> 112 year=year)
113 df1 = self.block_group_query(block_group_columns, state, county,
114 tract=tract, year=year)
c:\users\juan\documents\github\synthpop\synthpop\census_helpers.py in tract_query(self, census_columns, state, county, tract, year)
63 return self._query(census_columns, state, county,
64 forstr="tract:%s" % tract,
---> 65 year=year)
66
67 def _query(self, census_columns, state, county, forstr,
c:\users\juan\documents\github\synthpop\synthpop\census_helpers.py in _query(self, census_columns, state, county, forstr, tract, year)
69 c = self.c
70
---> 71 state, county = self.try_fips_lookup(state, county)
72
73 if tract is None:
c:\users\juan\documents\github\synthpop\synthpop\census_helpers.py in try_fips_lookup(self, state, county)
199
200 def try_fips_lookup(self, state, county=None):
--> 201 df = self._get_fips_lookup()
202
203 if county is None:
c:\users\juan\documents\github\synthpop\synthpop\census_helpers.py in _get_fips_lookup(self)
143 },
144 index_col=["State",
--> 145 "County Name"]
146 )
147 del self.fips_df["ANSI Cl"]
~\Anaconda3\envs\synpop_py3\lib\site-packages\pandas\io\parsers.py in parser_f(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)
707 skip_blank_lines=skip_blank_lines)
708
--> 709 return _read(filepath_or_buffer, kwds)
710
711 parser_f.__name__ = name
~\Anaconda3\envs\synpop_py3\lib\site-packages\pandas\io\parsers.py in _read(filepath_or_buffer, kwds)
431 compression = _infer_compression(filepath_or_buffer, compression)
432 filepath_or_buffer, _, compression = get_filepath_or_buffer(
--> 433 filepath_or_buffer, encoding, compression)
434 kwds['compression'] = compression
435
~\Anaconda3\envs\synpop_py3\lib\site-packages\pandas\io\common.py in get_filepath_or_buffer(filepath_or_buffer, encoding, compression)
188
189 if _is_url(filepath_or_buffer):
--> 190 req = _urlopen(filepath_or_buffer)
191 content_encoding = req.headers.get('Content-Encoding', None)
192 if content_encoding == 'gzip':
~\Anaconda3\envs\synpop_py3\lib\urllib\request.py in urlopen(url, data, timeout, cafile, capath, cadefault, context)
221 else:
222 opener = _opener
--> 223 return opener.open(url, data, timeout)
224
225 def install_opener(opener):
~\Anaconda3\envs\synpop_py3\lib\urllib\request.py in open(self, fullurl, data, timeout)
524 req = meth(req)
525
--> 526 response = self._open(req, data)
527
528 # post-process response
~\Anaconda3\envs\synpop_py3\lib\urllib\request.py in _open(self, req, data)
542 protocol = req.type
543 result = self._call_chain(self.handle_open, protocol, protocol +
--> 544 '_open', req)
545 if result:
546 return result
~\Anaconda3\envs\synpop_py3\lib\urllib\request.py in _call_chain(self, chain, kind, meth_name, *args)
502 for handler in handlers:
503 func = getattr(handler, meth_name)
--> 504 result = func(*args)
505 if result is not None:
506 return result
~\Anaconda3\envs\synpop_py3\lib\urllib\request.py in https_open(self, req)
1359 def https_open(self, req):
1360 return self.do_open(http.client.HTTPSConnection, req,
-> 1361 context=self._context, check_hostname=self._check_hostname)
1362
1363 https_request = AbstractHTTPHandler.do_request_
~\Anaconda3\envs\synpop_py3\lib\urllib\request.py in do_open(self, http_class, req, **http_conn_args)
1319 except OSError as err: # timeout error
1320 raise URLError(err)
-> 1321 r = h.getresponse()
1322 except:
1323 h.close()
~\Anaconda3\envs\synpop_py3\lib\http\client.py in getresponse(self)
1329 try:
1330 try:
-> 1331 response.begin()
1332 except ConnectionError:
1333 self.close()
~\Anaconda3\envs\synpop_py3\lib\http\client.py in begin(self)
295 # read until we get a non-100 response
296 while True:
--> 297 version, status, reason = self._read_status()
298 if status != CONTINUE:
299 break
~\Anaconda3\envs\synpop_py3\lib\http\client.py in _read_status(self)
256
257 def _read_status(self):
--> 258 line = str(self.fp.readline(_MAXLINE + 1), "iso-8859-1")
259 if len(line) > _MAXLINE:
260 raise LineTooLong("status line")
~\Anaconda3\envs\synpop_py3\lib\socket.py in readinto(self, b)
584 while True:
585 try:
--> 586 return self._sock.recv_into(b)
587 except timeout:
588 self._timeout_occurred = True
~\Anaconda3\envs\synpop_py3\lib\ssl.py in recv_into(self, buffer, nbytes, flags)
1007 "non-zero flags not allowed in calls to recv_into() on %s" %
1008 self.__class__)
-> 1009 return self.read(nbytes, buffer)
1010 else:
1011 return socket.recv_into(self, buffer, nbytes, flags)
~\Anaconda3\envs\synpop_py3\lib\ssl.py in read(self, len, buffer)
869 raise ValueError("Read on closed or unwrapped SSL socket.")
870 try:
--> 871 return self._sslobj.read(len, buffer)
872 except SSLError as x:
873 if x.args[0] == SSL_ERROR_EOF and self.suppress_ragged_eofs:
~\Anaconda3\envs\synpop_py3\lib\ssl.py in read(self, len, buffer)
629 """
630 if buffer is not None:
--> 631 v = self._sslobj.read(len, buffer)
632 else:
633 v = self._sslobj.read(len)
KeyboardInterrupt:
In [4]:
starter = Starter(os.environ["CENSUS"], "CA", "Santa Clara County")
In [5]:
ind = pd.Series(["06", "085", "508203", "3"], index=["state", "county", "tract", "block group"])
synthesize_all(starter, indexes=[ind])
Synthesizing at geog level: 'block_group' (number of geographies is 1075)
Synthesizing geog id:
state 06
county 085
tract 508203
block group 3
dtype: object
c:\users\juan\documents\github\synthpop\synthpop\ipu\ipu.py:190: RuntimeWarning: divide by zero encountered in double_scalars
adj = constraint / (column * weights).sum()
Drawing 770 households
Out[5]:
( serialno RT puma00 puma10 NP TYPE BLD TEN VEH HINCP \
0 2009001096088 H 2702 -9 4 1 3.0 3.0 0.0 226400.0
1 2009000797707 H 2702 -9 1 1 6.0 3.0 1.0 120000.0
2 2009000776447 H 2702 -9 1 1 9.0 3.0 1.0 187000.0
3 2009000034504 H 2702 -9 1 1 7.0 3.0 1.0 416000.0
4 2012000837531 H -9 8502 1 1 8.0 3.0 1.0 57000.0
5 2013000119247 H -9 8502 1 1 3.0 1.0 1.0 92000.0
6 2010000191477 H 2702 -9 1 1 3.0 4.0 1.0 390.0
7 2013000718037 H -9 8502 1 1 8.0 3.0 1.0 15500.0
8 2010000285540 H 2702 -9 2 1 5.0 3.0 1.0 0.0
9 2010000337473 H 2702 -9 4 1 8.0 3.0 1.0 32900.0
10 2010001167857 H 2702 -9 3 1 5.0 3.0 1.0 81200.0
11 2009001316324 H 2702 -9 2 1 5.0 3.0 1.0 4200.0
12 2009001316324 H 2702 -9 2 1 5.0 3.0 1.0 4200.0
13 2010000309566 H 2702 -9 3 1 3.0 3.0 2.0 110990.0
14 2009000875809 H 2702 -9 4 1 2.0 1.0 5.0 202000.0
15 2009000847427 H 2702 -9 3 1 2.0 1.0 3.0 192000.0
16 2009000842508 H 2702 -9 2 1 2.0 2.0 2.0 168000.0
17 2009001302282 H 2702 -9 2 1 3.0 2.0 2.0 150000.0
18 2009000938159 H 2702 -9 2 1 9.0 3.0 2.0 169500.0
19 2009000938159 H 2702 -9 2 1 9.0 3.0 2.0 169500.0
20 2009001025363 H 2702 -9 2 1 2.0 2.0 2.0 182000.0
21 2009001025363 H 2702 -9 2 1 2.0 2.0 2.0 182000.0
22 2010001128154 H 2702 -9 2 1 4.0 3.0 2.0 170000.0
23 2010001128154 H 2702 -9 2 1 4.0 3.0 2.0 170000.0
24 2010001128154 H 2702 -9 2 1 4.0 3.0 2.0 170000.0
25 2010001128154 H 2702 -9 2 1 4.0 3.0 2.0 170000.0
26 2012000917686 H -9 8502 2 1 2.0 1.0 2.0 280000.0
27 2012000917686 H -9 8502 2 1 2.0 1.0 2.0 280000.0
28 2012000917686 H -9 8502 2 1 2.0 1.0 2.0 280000.0
29 2012000917686 H -9 8502 2 1 2.0 1.0 2.0 280000.0
.. ... .. ... ... .. ... ... ... ... ...
740 2009000257552 H 2702 -9 3 1 5.0 3.0 2.0 156000.0
741 2010000224153 H 2702 -9 2 1 9.0 3.0 2.0 69000.0
742 2011000027489 H 2702 -9 2 1 4.0 3.0 2.0 33600.0
743 2010000554995 H 2702 -9 3 1 8.0 3.0 2.0 64200.0
744 2009000090585 H 2702 -9 2 1 9.0 3.0 1.0 36000.0
745 2009000991840 H 2702 -9 2 1 2.0 2.0 3.0 113000.0
746 2010001199295 H 2702 -9 1 1 6.0 3.0 1.0 110600.0
747 2010000531956 H 2702 -9 2 1 1.0 1.0 2.0 74000.0
748 2009000209747 H 2702 -9 2 1 2.0 3.0 2.0 142000.0
749 2011000989438 H 2702 -9 1 1 2.0 1.0 1.0 237400.0
750 2011000990235 H 2702 -9 3 1 1.0 2.0 3.0 151000.0
751 2012000497867 H -9 8502 2 1 2.0 2.0 3.0 136200.0
752 2013000393885 H -9 8502 1 1 2.0 3.0 5.0 69000.0
753 2009001089483 H 2702 -9 3 1 2.0 2.0 2.0 129850.0
754 2009000928777 H 2702 -9 2 1 2.0 2.0 3.0 188500.0
755 2009000935893 H 2702 -9 2 1 2.0 2.0 1.0 16500.0
756 2010000789913 H 2702 -9 2 1 9.0 3.0 2.0 60200.0
757 2012000643381 H -9 8502 4 1 5.0 3.0 2.0 251000.0
758 2011001475367 H 2702 -9 6 1 9.0 3.0 2.0 57000.0
759 2012000603952 H -9 8502 8 1 2.0 3.0 3.0 99230.0
760 2010000011387 H 2702 -9 2 1 2.0 1.0 1.0 220300.0
761 2010001283036 H 2702 -9 2 1 2.0 1.0 2.0 51001.0
762 2010001108709 H 2702 -9 2 1 2.0 1.0 2.0 77700.0
763 2013001259539 H -9 8502 1 1 3.0 3.0 2.0 20000.0
764 2011000656960 H 2702 -9 3 1 2.0 3.0 2.0 70000.0
765 2009000208025 H 2702 -9 2 1 8.0 3.0 0.0 54100.0
766 2011000236562 H 2702 -9 4 1 2.0 1.0 4.0 53300.0
767 2010000805810 H 2702 -9 3 1 2.0 2.0 2.0 1000.0
768 2010000255137 H 2702 -9 1 1 9.0 3.0 1.0 1800.0
769 2013000496979 H -9 8502 2 1 3.0 1.0 3.0 375304.0
... hh_size hh_workers seniors sf_detached \
0 ... four or more two or more no no
1 ... one one no no
2 ... one one no no
3 ... one one no no
4 ... one one no no
5 ... one one no no
6 ... one none no no
7 ... one one no no
8 ... two none no no
9 ... four or more one yes no
10 ... three one no no
11 ... two none no no
12 ... two none no no
13 ... three one no no
14 ... four or more two or more no yes
15 ... three two or more no yes
16 ... two none no yes
17 ... two one no no
18 ... two one no no
19 ... two one no no
20 ... two one no yes
21 ... two one no yes
22 ... two two or more no no
23 ... two two or more no no
24 ... two two or more no no
25 ... two two or more no no
26 ... two two or more no yes
27 ... two two or more no yes
28 ... two two or more no yes
29 ... two two or more no yes
.. ... ... ... ... ...
740 ... three one no no
741 ... two one no no
742 ... two one no no
743 ... three one no no
744 ... two one no no
745 ... two one no yes
746 ... one one no no
747 ... two two or more no no
748 ... two one yes yes
749 ... one one no yes
750 ... three one yes no
751 ... two none yes yes
752 ... one none yes yes
753 ... three two or more no yes
754 ... two one yes yes
755 ... two one no yes
756 ... two two or more yes no
757 ... four or more two or more no no
758 ... four or more one no no
759 ... four or more two or more no yes
760 ... two two or more no yes
761 ... two two or more yes yes
762 ... two none yes yes
763 ... one one no no
764 ... three two or more no yes
765 ... two one yes no
766 ... four or more one no yes
767 ... three none no yes
768 ... one none yes no
769 ... two two or more no no
tenure_mover cat_id state county tract block group
0 rent not recent 9282 06 085 508203 3
1 rent not recent 15490 06 085 508203 3
2 rent not recent 17026 06 085 508203 3
3 rent not recent 18178 06 085 508203 3
4 rent not recent 18562 06 085 508203 3
5 own not recent 20096 06 085 508203 3
6 rent not recent 21602 06 085 508203 3
7 rent not recent 21634 06 085 508203 3
8 rent not recent 21794 06 085 508203 3
9 rent not recent 26154 06 085 508203 3
10 rent not recent 27874 06 085 508203 3
11 rent not recent 29474 06 085 508203 3
12 rent not recent 29474 06 085 508203 3
13 rent not recent 30946 06 085 508203 3
14 own not recent 32324 06 085 508203 3
15 own not recent 32516 06 085 508203 3
16 own not recent 32548 06 085 508203 3
17 own not recent 32576 06 085 508203 3
18 rent not recent 32578 06 085 508203 3
19 rent not recent 32578 06 085 508203 3
20 own not recent 32580 06 085 508203 3
21 own not recent 32580 06 085 508203 3
22 rent not recent 32610 06 085 508203 3
23 rent not recent 32610 06 085 508203 3
24 rent not recent 32610 06 085 508203 3
25 rent not recent 32610 06 085 508203 3
26 own not recent 32612 06 085 508203 3
27 own not recent 32612 06 085 508203 3
28 own not recent 32612 06 085 508203 3
29 own not recent 32612 06 085 508203 3
.. ... ... ... ... ... ...
740 rent not recent 132322 06 085 508203 3
741 rent not recent 36802 06 085 508203 3
742 rent not recent 127426 06 085 508203 3
743 rent not recent 43618 06 085 508203 3
744 rent recent 110915 06 085 508203 3
745 own not recent 31044 06 085 508203 3
746 rent not recent 108802 06 085 508203 3
747 own not recent 36832 06 085 508203 3
748 rent not recent 78286 06 085 508203 3
749 own not recent 18180 06 085 508203 3
750 own not recent 79736 06 085 508203 3
751 own not recent 78252 06 085 508203 3
752 rent not recent 82670 06 085 508203 3
753 own not recent 38660 06 085 508203 3
754 own not recent 79820 06 085 508203 3
755 own not recent 21828 06 085 508203 3
756 rent not recent 82154 06 085 508203 3
757 rent recent 132163 06 085 508203 3
758 rent not recent 42674 06 085 508203 3
759 rent not recent 44230 06 085 508203 3
760 own not recent 18404 06 085 508203 3
761 own not recent 81388 06 085 508203 3
762 own not recent 36780 06 085 508203 3
763 rent not recent 38146 06 085 508203 3
764 rent not recent 136598 06 085 508203 3
765 rent not recent 49482 06 085 508203 3
766 own not recent 33828 06 085 508203 3
767 own not recent 37060 06 085 508203 3
768 rent not recent 68858 06 085 508203 3
769 own not recent 124768 06 085 508203 3
[770 rows x 32 columns],
serialno puma00 puma10 AGEP RELP SEX ESR HISP RAC1P hispanic \
0 2012000024049 -9 8502 47 1 2 6.0 1 6 no
1 2012000024049 -9 8502 47 1 2 6.0 1 6 no
2 2012000024049 -9 8502 47 1 2 6.0 1 6 no
3 2012000024049 -9 8502 53 0 1 1.0 1 6 no
4 2012000024049 -9 8502 53 0 1 1.0 1 6 no
5 2012000024049 -9 8502 53 0 1 1.0 1 6 no
6 2012000024049 -9 8502 17 2 1 6.0 1 6 no
7 2012000024049 -9 8502 17 2 1 6.0 1 6 no
8 2012000024049 -9 8502 17 2 1 6.0 1 6 no
9 2012000024049 -9 8502 6 2 2 NaN 1 6 no
10 2012000024049 -9 8502 6 2 2 NaN 1 6 no
11 2012000024049 -9 8502 6 2 2 NaN 1 6 no
12 2012000038026 -9 8502 37 1 2 3.0 1 6 no
13 2012000038026 -9 8502 48 0 1 1.0 1 6 no
14 2012000038026 -9 8502 6 2 1 NaN 1 6 no
15 2012000038026 -9 8502 4 2 2 NaN 1 6 no
16 2012000076386 -9 8502 43 0 2 6.0 1 6 no
17 2012000076386 -9 8502 43 0 2 6.0 1 6 no
18 2012000076386 -9 8502 43 0 2 6.0 1 6 no
19 2012000076386 -9 8502 46 1 1 1.0 1 6 no
20 2012000076386 -9 8502 46 1 1 1.0 1 6 no
21 2012000076386 -9 8502 46 1 1 1.0 1 6 no
22 2012000076386 -9 8502 12 2 1 NaN 1 6 no
23 2012000076386 -9 8502 12 2 1 NaN 1 6 no
24 2012000076386 -9 8502 12 2 1 NaN 1 6 no
25 2012000076386 -9 8502 16 2 2 6.0 1 6 no
26 2012000076386 -9 8502 16 2 2 6.0 1 6 no
27 2012000076386 -9 8502 16 2 2 6.0 1 6 no
28 2012000176039 -9 8502 58 1 2 1.0 1 6 no
29 2012000176039 -9 8502 27 2 1 1.0 1 6 no
... ... ... ... ... ... ... ... ... ... ...
2244 2009001006831 2702 -9 34 0 1 1.0 2 1 yes
2245 2009001006831 2702 -9 4 2 1 NaN 2 1 yes
2246 2009001006831 2702 -9 4 2 1 NaN 2 1 yes
2247 2009001006831 2702 -9 2 2 2 NaN 2 1 yes
2248 2009001006831 2702 -9 2 2 2 NaN 2 1 yes
2249 2011000656960 2702 -9 26 1 2 1.0 2 1 yes
2250 2011000656960 2702 -9 26 1 2 1.0 2 1 yes
2251 2011000656960 2702 -9 27 0 1 1.0 2 1 yes
2252 2011000656960 2702 -9 27 0 1 1.0 2 1 yes
2253 2011000656960 2702 -9 1 2 1 NaN 2 1 yes
2254 2011000656960 2702 -9 1 2 1 NaN 2 1 yes
2255 2013000583586 -9 8502 34 0 1 1.0 2 1 yes
2256 2011000482661 2702 -9 34 2 1 1.0 2 1 yes
2257 2011000482661 2702 -9 67 0 1 6.0 2 1 yes
2258 2011000482661 2702 -9 8 7 2 NaN 2 1 yes
2259 2011000482661 2702 -9 73 1 2 6.0 2 1 yes
2260 2010000789913 2702 -9 60 1 2 1.0 1 2 no
2261 2010000789913 2702 -9 68 0 1 1.0 1 2 no
2262 2012000306986 -9 8502 83 0 1 6.0 1 6 no
2263 2013001102796 -9 8502 74 0 1 6.0 1 6 no
2264 2009000183391 2702 -9 63 0 1 1.0 1 6 no
2265 2012001080872 -9 8502 93 0 1 6.0 2 1 yes
2266 2012001080872 -9 8502 80 1 2 6.0 2 1 yes
2267 2012001247807 -9 8502 88 0 1 6.0 3 1 yes
2268 2012001247807 -9 8502 93 1 2 6.0 3 1 yes
2269 2013000619824 -9 8502 77 1 1 6.0 2 1 yes
2270 2013000619824 -9 8502 77 0 2 6.0 2 1 yes
2271 2010000396495 2702 -9 61 0 1 1.0 20 1 yes
2272 2010000396495 2702 -9 61 1 2 1.0 20 1 yes
2273 2010000255137 2702 -9 84 0 2 6.0 3 1 yes
person_age person_sex race cat_id hh_id
0 35 to 60 female asian 138256 98
1 35 to 60 female asian 138256 106
2 35 to 60 female asian 138256 107
3 35 to 60 male asian 138260 98
4 35 to 60 male asian 138260 106
5 35 to 60 male asian 138260 107
6 19 and under male asian 138244 98
7 19 and under male asian 138244 106
8 19 and under male asian 138244 107
9 19 and under female asian 138240 98
10 19 and under female asian 138240 106
11 19 and under female asian 138240 107
12 35 to 60 female asian 138256 54
13 35 to 60 male asian 138260 54
14 19 and under male asian 138244 54
15 19 and under female asian 138240 54
16 35 to 60 female asian 138256 75
17 35 to 60 female asian 138256 80
18 35 to 60 female asian 138256 84
19 35 to 60 male asian 138260 75
20 35 to 60 male asian 138260 80
21 35 to 60 male asian 138260 84
22 19 and under male asian 138244 75
23 19 and under male asian 138244 80
24 19 and under male asian 138244 84
25 19 and under female asian 138240 75
26 19 and under female asian 138240 80
27 19 and under female asian 138240 84
28 35 to 60 female asian 138256 631
29 20 to 35 male asian 138252 631
... ... ... ... ... ...
2244 20 to 35 male white 138287 607
2245 19 and under male white 138279 356
2246 19 and under male white 138279 607
2247 19 and under female white 138275 356
2248 19 and under female white 138275 607
2249 20 to 35 female white 138283 447
2250 20 to 35 female white 138283 764
2251 20 to 35 male white 138287 447
2252 20 to 35 male white 138287 764
2253 19 and under male white 138279 447
2254 19 and under male white 138279 764
2255 20 to 35 male white 138287 564
2256 20 to 35 male white 138287 718
2257 above 60 male white 138303 718
2258 19 and under female white 138275 718
2259 above 60 female white 138299 718
2260 35 to 60 female black 138257 756
2261 above 60 male black 138269 756
2262 above 60 male asian 138268 571
2263 above 60 male asian 138268 452
2264 above 60 male asian 138268 701
2265 above 60 male white 138303 563
2266 above 60 female white 138299 563
2267 above 60 male white 138303 574
2268 above 60 female white 138299 574
2269 above 60 male white 138303 533
2270 above 60 female white 138299 533
2271 above 60 male white 138303 713
2272 above 60 female white 138299 713
2273 above 60 female white 138299 768
[2274 rows x 15 columns],
{BlockGroupID(state='06', county='085', tract='508203', block_group='3'): FitQuality(people_chisq=50.53639934882075, people_p=0.37362753869683724)})
In [ ]:
Content source: UDST/synthpop
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