Closed SPTKL closed 4 years ago
In the social table: for geoid = 1015100 and variable=DfHsUS
geoid = 1015100
variable=DfHsUS
Based on the variable look up
"DfHsUS": [ "DP02_0080" ],
pulling pre-calculation data:
>>> dff = df.loc[df.GEO_ID=='1400000US36061015100', ['DP02_0080E', 'DP02_0080M', 'DP02_0080PE', 'DP02_0080PM']] >>> dff DP02_0080E DP02_0080M DP02_0080PE DP02_0080PM 2283 1000.0 402.0 12.0 4.6
In this case, we are taking PE and PM directly from ACS without calculation, so it's a mistake from population? (assuming the variable mapping is correct)
The estimate and margin of error match the database, the percent and percent MOE should be calculated off of DfHs2. Is that what you are using?
In the social table: for
geoid = 1015100
andvariable=DfHsUS
Based on the variable look up
pulling pre-calculation data:
In this case, we are taking PE and PM directly from ACS without calculation, so it's a mistake from population? (assuming the variable mapping is correct)