Predict Mortality/Death Rate.

770k records & 121 variables of unit level survey data collected from 9 States.

@kaggle.rajanand_mortality

Table List

9 tables(55.61 MB)

Mortality 22 Ct

@kaggle.rajanand_mortality.mortality_22_ct

3.15 MB
44251 rows
122 columns
Only the first 100 columns are shown

id Id	m_id M Id	client_m_id Client M Id	hl_id Hl Id	house_no House No	house_hold_no House Hold No	state State	district District	rural Rural	stratum_code Stratum Code	psu_id Psu Id	m_serial_no M Serial No	deceased_sex Deceased Sex	date_of_death Date Of Death	month_of_death Month Of Death	year_of_death Year Of Death	age_of_death_above_one_year Age Of Death Above One Year	treatment_source Treatment Source	place_of_death Place Of Death	is_death_reg Is Death Reg	is_death_certificate_received Is Death Certificate Received	is_death_associated_with_pregnan Is Death Associated With Pregnan	m_expall_status M Expall Status	hh_id Hh Id	client_hh_id Client Hh Id	currently_dead_or_out_migrated Currently Dead Or Out Migrated	hh_serial_no Hh Serial No	sex Sex	usual_residance Usual Residance	relation_to_head Relation To Head	member_identity Member Identity	mother_serial_no Mother Serial No	date_of_birth Date Of Birth	month_of_birth Month Of Birth	year_of_birth Year Of Birth	age Age	religion Religion	social_group_code Social Group Code	marital_status Marital Status	date_of_marriage Date Of Marriage	month_of_marriage Month Of Marriage	year_of_marriage Year Of Marriage	highest_qualification Highest Qualification	occupation_status Occupation Status	illness_type Illness Type	symptoms_pertaining_illness Symptoms Pertaining Illness	sought_medical_care Sought Medical Care	diagnosed_for Diagnosed For	diagnosis_source Diagnosis Source	regular_treatment Regular Treatment	regular_treatment_source Regular Treatment Source	chew Chew	smoke Smoke	alcohol Alcohol	status Status	hh_expall_status Hh Expall Status	client_hl_id Client Hl Id	serial_no Serial No	building_no Building No	house_status House Status	house_structure House Structure	owner_status Owner Status	drinking_water_source Drinking Water Source	is_water_filter Is Water Filter	water_filteration Water Filteration	toilet_used Toilet Used	is_toilet_shared Is Toilet Shared	household_have_electricity Household Have Electricity	lighting_source Lighting Source	cooking_fuel Cooking Fuel	no_of_dwelling_rooms No Of Dwelling Rooms	kitchen_availability Kitchen Availability	is_radio Is Radio	is_television Is Television	is_computer Is Computer	is_telephone Is Telephone	is_washing_machine Is Washing Machine	is_refrigerator Is Refrigerator	is_sewing_machine Is Sewing Machine	is_bicycle Is Bicycle	is_scooter Is Scooter	is_car Is Car
396416	1306	442	20151	119	1	22	10	1	1	100659749	130	2	14	6	2008	56	9	3	1	1		1	71325	16420	2	1	1	1	1	618		4	7	1949	60	1	3	5	7	5	1968	6	1	7	1	2	8	8	2	8	5	4	3		1	5202	158	nan	1	2	1	3	1	4			1	1	1	3	1	1	1	3	2	2	2	2	1	2	2
396424	1313	449	20207	159	1	22	10	1	1	100659797	176	1	11	12	2008	65	8	1	1	1		1	71522	16617	2	1	1	1	1	809		5	6	1974	35	1	3	3	5	4	1998	4	2		11						5	1	2		1	5258	212	nan	1	2	1	3	1	4			1	1	1	2	1	2	1	3	2	2	2	2	1	2	2
396432	1321	457	20280	227	2	22	10	1	1	100659773	228	2	18	7	2007	70	9	1	1	2		1	71810	16905	2	1	1	1	1	1091		20	7	1961	48	1	3	3	20	9	1991	4	1		11						6	3	3		1	5331	286	nan	1	2	1	3	1	4			1	1	1	2	1	2	1	3	2	2	2	2	1	2	2
396440	1329	465	20372	306	1	22	10	1	1	100659786	302	1	12	10	2007	45		1	2			1	72189	17288	2	1	2	1	1	1455		4	5	1967	42	1	1	5	4	5	1984		1		4	1	19	8	2	8	5	4	4	1	1	5423	378	nan	1	2	1	3	1	4			1	1	1	2	1	2	2	3	2	2	2	2	1	2	2
396448	1336	472	20434	361	1	22	10	1	1	100659792	360	2	9	12	2007	65		1	2			1	72495	17594	2	1	1	1	1	1755		1	4	1969	40	1	3	3	4	5	1991	5	3		11						5	4	3		1	5485	441	nan	1	1	1	3	1	4			1	1	1	3	1	2	1	3	2	2	2	2	1	2	2
396456	1348	138	20556	107	1	22	10	2		100661593	80	1	8	11	2007	55	6	3	1	1		1	72850	1006	2	1	2	1	1	324	5			1958	51	1	3	5	13	3	1976	3	4		2	3	2	8	2	8	7	4	4		1	902	112	nan	1	1	1	2	1	4	2	2	1	1	6	2	1	1	1	3	2	2	1	1	1	2	2
396464	1358	157	20813	95	1	22	10	2		100660838	81	1	1	10	2008	45		1	1	1		1	73584	2045	2	1	1	1	1	342		22	4	1960	49	1	3	3			1985	3	3		11						7	4	2		1	1302	100	nan	1	3	1	2	1	4			1	1	4	2	1	2	1	3	4	2	2	1	1	2	2
396472	1363	162	20859	139	1	22	10	2		100660844	110	1	10	11	2009	39	6	1	2			1	73749	2210	2	1	1	1	1	515		10	10	1965	44	1	3	3	24	5	1984	3	3		11						5	1	4		1	1348	146	52	1	2	1	2	1	4	2	2	1	1	1	3	1	2	2	3	4	2	2	2	1	2	2
396480	1371	138	21176	7	1	22	10	2		100661141	6	2		7	2008	55	9	1	1	1		1	74733	1016	2	1	1	1	1	27				1944	65	1	3	5		4	1964	5	1		11						7	4	4		1	989	7	nan	1	2	1	2	1	4	2	2	1	1	6	3	1	2	1	3	2	1	1	1	2	1	2
396488	1377	144	21273	89	2	22	10	2		100661154	83	2		6	2008	48	6	3	1	2	2	1	75132	1503	2	1	1	1	1	413				1987	22	1	3	3		5	2005	3	3		11						4	1	1		1	1117	104	nan	1	2	2	2	2				2	2	3	1	1	2	1	3	2	2	2	2	2	2	2


CREATE TABLE mortality_22_ct (
  "id" BIGINT,
  "m_id" DOUBLE,
  "client_m_id" DOUBLE,
  "hl_id" DOUBLE,
  "house_no" BIGINT,
  "house_hold_no" BIGINT,
  "state" BIGINT,
  "district" BIGINT,
  "rural" BIGINT,
  "stratum_code" BIGINT,
  "psu_id" BIGINT,
  "m_serial_no" BIGINT,
  "deceased_sex" BIGINT,
  "date_of_death" BIGINT,
  "month_of_death" BIGINT,
  "year_of_death" BIGINT,
  "age_of_death_below_one_month" DOUBLE,
  "age_of_death_below_eleven_month" DOUBLE,
  "age_of_death_above_one_year" DOUBLE,
  "treatment_source" BIGINT,
  "place_of_death" BIGINT,
  "is_death_reg" BIGINT,
  "is_death_certificate_received" DOUBLE,
  "serial_num_of_infant_mother" DOUBLE,
  "order_of_birth" DOUBLE,
  "death_symptoms" DOUBLE,
  "is_death_associated_with_pregnan" DOUBLE,
  "death_period" DOUBLE,
  "months_of_pregnancy" DOUBLE,
  "factors_contributing_death" DOUBLE,
  "factors_contributing_death_2" DOUBLE,
  "symptoms_of_death" DOUBLE,
  "time_between_onset_of_complicati" DOUBLE,
  "nearest_medical_facility" DOUBLE,
  "m_expall_status" DOUBLE,
  "field38" VARCHAR,
  "hh_id" DOUBLE,
  "client_hh_id" DOUBLE,
  "currently_dead_or_out_migrated" DOUBLE,
  "hh_serial_no" DOUBLE,
  "sex" DOUBLE,
  "usual_residance" DOUBLE,
  "relation_to_head" DOUBLE,
  "member_identity" DOUBLE,
  "father_serial_no" DOUBLE,
  "mother_serial_no" DOUBLE,
  "date_of_birth" DOUBLE,
  "month_of_birth" DOUBLE,
  "year_of_birth" DOUBLE,
  "age" DOUBLE,
  "religion" DOUBLE,
  "social_group_code" DOUBLE,
  "marital_status" DOUBLE,
  "date_of_marriage" DOUBLE,
  "month_of_marriage" DOUBLE,
  "year_of_marriage" DOUBLE,
  "currently_attending_school" DOUBLE,
  "reason_for_not_attending_school" DOUBLE,
  "highest_qualification" DOUBLE,
  "occupation_status" DOUBLE,
  "disability_status" DOUBLE,
  "injury_treatment_type" DOUBLE,
  "illness_type" DOUBLE,
  "symptoms_pertaining_illness" DOUBLE,
  "sought_medical_care" DOUBLE,
  "diagnosed_for" DOUBLE,
  "diagnosis_source" DOUBLE,
  "regular_treatment" DOUBLE,
  "regular_treatment_source" DOUBLE,
  "chew" DOUBLE,
  "smoke" DOUBLE,
  "alcohol" DOUBLE,
  "status" DOUBLE,
  "hh_expall_status" DOUBLE,
  "client_hl_id" DOUBLE,
  "serial_no" DOUBLE,
  "building_no" VARCHAR,
  "house_status" DOUBLE,
  "house_structure" DOUBLE,
  "owner_status" DOUBLE,
  "drinking_water_source" DOUBLE,
  "is_water_filter" DOUBLE,
  "water_filteration" DOUBLE,
  "toilet_used" DOUBLE,
  "is_toilet_shared" DOUBLE,
  "household_have_electricity" DOUBLE,
  "lighting_source" DOUBLE,
  "cooking_fuel" DOUBLE,
  "no_of_dwelling_rooms" DOUBLE,
  "kitchen_availability" DOUBLE,
  "is_radio" DOUBLE,
  "is_television" DOUBLE,
  "is_computer" DOUBLE,
  "is_telephone" DOUBLE,
  "is_washing_machine" DOUBLE,
  "is_refrigerator" DOUBLE,
  "is_sewing_machine" DOUBLE,
  "is_bicycle" DOUBLE,
  "is_scooter" DOUBLE,
  "is_car" DOUBLE
);