CODEBOOK: censuspop
==============================================================

All values are SIMULATED. No figure describes any real
person, household, city, or country.
Appendix B explains how each dataset was built and what it is
for.

Categorical variables are stored as integer codes; the
mapping is given below. Sentinel missing codes (97, 98,
99) are left in place, NOT converted to NA -- recoding
them is an exercise in several chapters.

Rows: 50000    Columns: 14
--------------------------------------------------------------

pid              Person identifier  [Integer]

hid              Household identifier  [Integer]

hh_size          People in the household  [Numeric]

age              Age in years  [Numeric]

sex              Sex  [Coded]
                   1 = Female; 2 = Male

province         Province  [Coded]
                   A--H, in descending population order. Lettered because these are not real jurisdictions

urban            Community type  [Coded]
                   1 = Urban; 2 = Suburban; 3 = Rural

educ             Highest level completed  [Coded]
                   1--5, as socsurvey; 1 for those under 18

occupation       Occupational group  [Coded]
                   0 = Not applicable (under 18); 1 = Management; 2 = Business, finance and administration; 3 = Sciences and engineering; 4 = Health; 5 = Education, law and social services; 6 = Sales, service and trades

income           Annual income, simulated dollars  [Integer]
                   ; 0 for those under 18; top-coded

immigrant        Born outside the country  [Coded]
                   0 = No; 1 = Yes. Share varies by province

lang_home        Language spoken at home  [Coded]
                   1 = First official language; 2 = Second official language; 3 = A non-official language; 4 = More than one language equally

tenure           Housing tenure  [Coded]
                   1 = Owns; 2 = Rents

commute_min      Daily commute, minutes  [Numeric]
                   ; 0 for those who do not commute

