From 094b2da61d191977fd67238d1d2f4a1012cc23ea Mon Sep 17 00:00:00 2001 From: Andy Eschbacher Date: Thu, 14 Apr 2016 13:23:04 -0400 Subject: [PATCH] adding new data fixtures subset --- ...2e1111ad3177676471d66bb8036e6d057f271b.sql | 12 ++ ...038198aaab3f3cb055758638ee4de28ad70146.sql | 129 ++++++++++++++++++ 2 files changed, 141 insertions(+) create mode 100644 src/pg/test/fixtures/obs_a92e1111ad3177676471d66bb8036e6d057f271b.sql create mode 100644 src/pg/test/fixtures/obs_ab038198aaab3f3cb055758638ee4de28ad70146.sql diff --git a/src/pg/test/fixtures/obs_a92e1111ad3177676471d66bb8036e6d057f271b.sql b/src/pg/test/fixtures/obs_a92e1111ad3177676471d66bb8036e6d057f271b.sql new file mode 100644 index 0000000..b19ac2a --- /dev/null +++ b/src/pg/test/fixtures/obs_a92e1111ad3177676471d66bb8036e6d057f271b.sql @@ -0,0 +1,12 @@ + +CREATE TABLE IF NOT EXISTS obs_a92e1111ad3177676471d66bb8036e6d057f271b ( + cartodb_id integer, + the_geom geometry(Geometry,4326), + the_geom_webmercator geometry(Geometry,3857), + geoid text +); + +INSERT INTO obs_a92e1111ad3177676471d66bb8036e6d057f271b (cartodb_id, the_geom, the_geom_webmercator, geoid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observatory; +ALTER TABLE obs_a92e1111ad3177676471d66bb8036e6d057f271b SET SCHEMA observatory; diff --git a/src/pg/test/fixtures/obs_ab038198aaab3f3cb055758638ee4de28ad70146.sql b/src/pg/test/fixtures/obs_ab038198aaab3f3cb055758638ee4de28ad70146.sql new file mode 100644 index 0000000..705fc30 --- /dev/null +++ b/src/pg/test/fixtures/obs_ab038198aaab3f3cb055758638ee4de28ad70146.sql @@ -0,0 +1,129 @@ + +CREATE TABLE IF NOT EXISTS obs_ab038198aaab3f3cb055758638ee4de28ad70146 ( + cartodb_id integer, + the_geom geometry(Geometry,4326), + the_geom_webmercator geometry(Geometry,3857), + geoid text, + total_pop double precision, + male_pop double precision, + female_pop double precision, + median_age double precision, + white_pop double precision, + black_pop double precision, + asian_pop double precision, + hispanic_pop double precision, + amerindian_pop double precision, + other_race_pop double precision, + two_or_more_races_pop double precision, + not_hispanic_pop double precision, + not_us_citizen_pop double precision, + workers_16_and_over double precision, + commuters_by_car_truck_van double precision, + commuters_drove_alone double precision, + commuters_by_carpool double precision, + commuters_by_public_transportation double precision, + commuters_by_bus double precision, + commuters_by_subway_or_elevated double precision, + walked_to_work double precision, + worked_at_home double precision, + children double precision, + households double precision, + population_3_years_over double precision, + in_school double precision, + in_grades_1_to_4 double precision, + in_grades_5_to_8 double precision, + in_grades_9_to_12 double precision, + in_undergrad_college double precision, + pop_25_years_over double precision, + high_school_diploma double precision, + less_one_year_college double precision, + one_year_more_college double precision, + associates_degree double precision, + bachelors_degree double precision, + masters_degree double precision, + pop_5_years_over double precision, + speak_only_english_at_home double precision, + speak_spanish_at_home double precision, + pop_determined_poverty_status double precision, + poverty double precision, + median_income double precision, + gini_index double precision, + income_per_capita double precision, + housing_units double precision, + vacant_housing_units double precision, + vacant_housing_units_for_rent double precision, + vacant_housing_units_for_sale double precision, + median_rent double precision, + percent_income_spent_on_rent double precision, + owner_occupied_housing_units double precision, + million_dollar_housing_units double precision, + mortgaged_housing_units double precision, + families_with_young_children double precision, + two_parent_families_with_young_children double precision, + two_parents_in_labor_force_families_with_young_children double precision, + two_parents_father_in_labor_force_families_with_young_children double precision, + two_parents_mother_in_labor_force_families_with_young_children double precision, + two_parents_not_in_labor_force_families_with_young_children double precision, + one_parent_families_with_young_children double precision, + father_one_parent_families_with_young_children double precision, + men_45_to_64 double precision, + men_45_to_49 double precision, + men_50_to_54 double precision, + men_55_to_59 double precision, + men_60_61 double precision, + men_62_64 double precision, + black_men_45_54 double precision, + black_men_55_64 double precision, + hispanic_men_45_54 double precision, + hispanic_men_55_64 double precision, + white_men_45_54 double precision, + white_men_55_64 double precision, + asian_men_45_54 double precision, + asian_men_55_64 double precision, + men_45_64_less_than_9_grade double precision, + men_45_64_grade_9_12 double precision, + men_45_64_high_school double precision, + men_45_64_some_college double precision, + men_45_64_associates_degree double precision, + men_45_64_bachelors_degree double precision, + men_45_64_graduate_degree double precision, + father_in_labor_force_one_parent_families_with_young_children double precision, + pop_15_and_over double precision, + pop_never_married double precision, + pop_now_married double precision, + pop_separated double precision, + pop_widowed double precision, + pop_divorced double precision, + commuters_16_over double precision, + commute_less_10_mins double precision, + commute_10_14_mins double precision, + commute_15_19_mins double precision, + commute_20_24_mins double precision, + commute_25_29_mins double precision, + commute_30_34_mins double precision, + commute_35_44_mins double precision, + commute_45_59_mins double precision, + commute_60_more_mins double precision, + aggregate_travel_time_to_work double precision, + income_less_10000 double precision, + income_10000_14999 double precision, + income_15000_19999 double precision, + income_20000_24999 double precision, + income_25000_29999 double precision, + income_30000_34999 double precision, + income_35000_39999 double precision, + income_40000_44999 double precision, + income_45000_49999 double precision, + income_50000_59999 double precision, + income_60000_74999 double precision, + income_75000_99999 double precision, + income_100000_124999 double precision, + income_125000_149999 double precision, + income_150000_199999 double precision, + income_200000_or_more double precision +); + +INSERT INTO obs_ab038198aaab3f3cb055758638ee4de28ad70146 (cartodb_id, the_geom, the_geom_webmercator, geoid, total_pop, male_pop, female_pop, median_age, white_pop, black_pop, asian_pop, hispanic_pop, amerindian_pop, other_race_pop, two_or_more_races_pop, not_hispanic_pop, not_us_citizen_pop, workers_16_and_over, commuters_by_car_truck_van, commuters_drove_alone, commuters_by_carpool, commuters_by_public_transportation, commuters_by_bus, commuters_by_subway_or_elevated, walked_to_work, worked_at_home, children, households, population_3_years_over, in_school, in_grades_1_to_4, in_grades_5_to_8, in_grades_9_to_12, in_undergrad_college, pop_25_years_over, high_school_diploma, less_one_year_college, one_year_more_college, associates_degree, bachelors_degree, masters_degree, pop_5_years_over, speak_only_english_at_home, speak_spanish_at_home, pop_determined_poverty_status, poverty, median_income, gini_index, income_per_capita, housing_units, vacant_housing_units, vacant_housing_units_for_rent, vacant_housing_units_for_sale, median_rent, percent_income_spent_on_rent, owner_occupied_housing_units, million_dollar_housing_units, mortgaged_housing_units, families_with_young_children, two_parent_families_with_young_children, two_parents_in_labor_force_families_with_young_children, two_parents_father_in_labor_force_families_with_young_children, two_parents_mother_in_labor_force_families_with_young_children, two_parents_not_in_labor_force_families_with_young_children, one_parent_families_with_young_children, father_one_parent_families_with_young_children, men_45_to_64, men_45_to_49, men_50_to_54, men_55_to_59, men_60_61, men_62_64, black_men_45_54, black_men_55_64, hispanic_men_45_54, hispanic_men_55_64, white_men_45_54, white_men_55_64, asian_men_45_54, asian_men_55_64, men_45_64_less_than_9_grade, men_45_64_grade_9_12, men_45_64_high_school, men_45_64_some_college, men_45_64_associates_degree, men_45_64_bachelors_degree, men_45_64_graduate_degree, father_in_labor_force_one_parent_families_with_young_children, pop_15_and_over, pop_never_married, pop_now_married, pop_separated, pop_widowed, pop_divorced, commuters_16_over, commute_less_10_mins, commute_10_14_mins, commute_15_19_mins, commute_20_24_mins, commute_25_29_mins, commute_30_34_mins, commute_35_44_mins, commute_45_59_mins, commute_60_more_mins, aggregate_travel_time_to_work, income_less_10000, income_10000_14999, income_15000_19999, income_20000_24999, income_25000_29999, income_30000_34999, income_35000_39999, income_40000_44999, income_45000_49999, income_50000_59999, income_60000_74999, income_75000_99999, income_100000_124999, income_125000_149999, income_150000_199999, income_200000_or_more) VALUES (44715, NULL, NULL, '36047048500', 2794, 1793, 1001, 28, 1528, 80, 100, 1066, 0, 14, 6, 1728, 316, 1996, 117, 101, 16, 1453, 46, 1394, 145, 81, 174, 897, 2728, 554, 20, 13, 35, 182, 2064, 335, 19, 197, 109, 801, 299, 2715, 1696, 839, 2794, 564, 73170, 0.38919999999999999, 29516, 1009, 112, 21, 0, 1733, 29.3999999999999986, 106, 0, 74, 91, 61, 22, 25, 0, 14, 30, 17, 150, 31, 67, 6, 15, 31, 0, 0, 37, 52, 61, 0, 0, 0, 18, 6, 53, 6, 16, 23, 28, 17, 2627, 2035, 393, 65, 35, 19, 1915, 82, 24, 77, 172, 169, 461, 457, 297, 176, 67175, 10, 11, 37, 96, 29, 52, 19, 24, 11, 57, 123, 151, 68, 94, 45, 70); + +CREATE SCHEMA IF NOT EXISTS observatory; +ALTER TABLE obs_ab038198aaab3f3cb055758638ee4de28ad70146 SET SCHEMA observatory;