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 10 Bh

@kaggle.rajanand_mortality.mortality_10_bh

7.11 MB
107238 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	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	father_serial_no Father 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	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	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
3256	1650	216	18640	45	1	10	11	1	2	100330753	50	1		9	2008	55		2	1	1	1	80834	4330	2	1	2	1	1	245			4	1959	50	1	3	5		3	1975		10	11						7	4	4		1	1798	50	nan	1	1	1	3	2			2	2	2	2	3	2	2	3	2	2	2	2	1	2	2
3264	1658	224	18783	140	1	10	11	1	2	100330778	193	2		12	2007	69		1	2		1	81413	4911	2	1	2	1	1	803	6		6	1975	34	1	3	3		3	1991		10	11						7	4	4	1	1	1941	193	nan	1	3	1	3	2			2	2	2	1	3	2	2	3	4	2	2	2	1	2	2
3272	1666	232	18845	177	2	10	11	1	2	100330763	256	1	4	12	2007	43	8	1	1	2	1	81689	5187	2	1	2	1	1	1049			7	1969	40	2	3	5		2	1983	1	10	2	2	4	8	3		7	4	4	1	1	2003	257	nan	1	1	1	3	2			2	2	2	1	3	2	2	3	4	2	2	2	2	2	2
3280			18935	247	2	10	11	1	2	100330797	309	1	18	3	2008	65	99	3	1	1	1	82117	5615	2	1	2	1	1	1415		7	4	1981	28	2	3	3	23	1	1997		10	11						7	4	4	1	1	2093	348	nan	1	1	1	3	2			2	2	2	1	3	2	2	3	4	2	2	2	2	2	2
3288	1676	242	19041	325	1	10	11	1	2	100330766	456	2	20	1	2008	70	8	1	2		1	82630	6128	2	1	1	1	1	1873			4	1971	38	1	3	3	1	6	1995	4	3	11						7	4	4		1	2199	455	nan	1	3	1	3	2			2	2	1	1	4	2	2	3	4	2	2	2	1	2	2
3296	1685	251	19120	386	2	10	11	1	2	100330775	537	2	25	9	2008	60	8	1	2		1	82996	6494	2	1	1	1	1	2221			6	1974	35	1	3	3	5	7	1996	1	4	11						1	4	4		1	2278	537	nan	1	1	1	3	2			2	2	2	1	3	2	2	3	4	2	2	2	2	2	2
3304	1699	139	19165	31	2	10	11	2		100333317	35	2		12	2009	70	8	1	2		1	83193	851	2	1	2	1	1	164				1950	59	1	3	5			1968		10	11						7	4	4		1	825	35	nan	1	1	1	3	2	2	2	1	1	1	1	3	2	2	3	4	2	2	2	2	2	2
3312	1706	269	19209	18	1	10	11	2		100332444	22	2	7	2	2008	56	6	1	1	1	1	83386	6417	2	1	2	1	1	109		15	8	1957	52	1	3	5	12	5	1971		2	1	2	3	8	2	8	7	1	4		1	2102	23	nan	1	1	1	3	2			2	2	2	1	1	2	2	3	4	2	2	2	2	2	2
3320	1713	276	19275	54	1	10	11	2		100332467	88	1		3	2008	45	6	3	1	1	1	83685	6716	2	1	1	1	1	408		19	8	1982	27	1	3	3	16	6	2004	4	3	11						1	4	2		1	2169	89	nan	1	1	1	3	2	2	1	1	2	6	1	1	2	2	3	2	2	2	2	1	2	2
3328	1721	284	19322	90	1	10	11	2		100332443	133	1	7	11	2009	15		2	2		1	83885	6950	2	1	1	1	1	604		17	2	1952	57	1	1	3	2	3	1974	6	7	5	1	21	8	1	8	5	2	2		1	2216	136	nan	1	1	1	3	2	2	1	1	2	6	1	2	2	1	1	2	2	2	1	1	1	1


CREATE TABLE mortality_10_bh (
  "id" BIGINT,
  "m_id" DOUBLE,
  "client_m_id" DOUBLE,
  "hl_id" DOUBLE,
  "house_no" BIGINT,
  "house_hold_no" BIGINT,
  "state" BIGINT,
  "district" BIGINT,
  "rural" DOUBLE,
  "stratum_code" BIGINT,
  "psu_id" BIGINT,
  "m_serial_no" DOUBLE,
  "deceased_sex" BIGINT,
  "date_of_death" DOUBLE,
  "month_of_death" BIGINT,
  "year_of_death" DOUBLE,
  "age_of_death_below_one_month" DOUBLE,
  "age_of_death_below_eleven_month" DOUBLE,
  "age_of_death_above_one_year" DOUBLE,
  "treatment_source" DOUBLE,
  "place_of_death" DOUBLE,
  "is_death_reg" DOUBLE,
  "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
);