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 18 As

@kaggle.rajanand_mortality.mortality_18_as

4.69 MB
71003 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_below_eleven_month Age Of Death Below Eleven Month	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	serial_num_of_infant_mother Serial Num Of Infant Mother	order_of_birth Order Of Birth	death_symptoms Death Symptoms	is_death_associated_with_pregnan Is Death Associated With Pregnan	death_period Death Period	months_of_pregnancy Months Of Pregnancy	factors_contributing_death Factors Contributing Death	factors_contributing_death_2 Factors Contributing Death 2	symptoms_of_death Symptoms Of Death	time_between_onset_of_complicati Time Between Onset Of Complicati	nearest_medical_facility Nearest Medical Facility	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	mother_serial_no Mother Serial No	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	disability_status Disability Status	symptoms_pertaining_illness Symptoms Pertaining Illness	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
170553	129	348	1420	397	1	18	1	1	2	100441813	37	2		7	2009		8	5	1	2		2	1	15									1	6286	15471	2	1	1	1	1	1678	3	4	1979	30	1	3	3			2000		1		11	1	3	2		1	5097	403	nan	1	3	1	3	2				2	2	1	2	3	2	2	3	4	2	2	2	1	2	2
170561	137	356	1506	449	1	18	1	1	2	100441828	45	1	15	8	2009		32	99	1	1	1												1	6541	15726	2	1	1	1	1	1922			1986	23	1	2	3		2	2009	4	1		11	1	4	2		1	5186	456	nan	1	2	1	3	2				2	2	1	2	3	2	2	3	2	2	2	2	1	2	2
170569	147	153	1600	94	1	18	1	1	1	100441497	94	1		10	2009		90	99	1	2													1	7145	2310	2	1	1	1	1	447			1969	40	1	2	3			1997	6	1		11	1	4	2		1	1142	94	nan	1	2	1	3	2				1	3	1	2	3	2	2	3	4	2	2	2	1	2	2
170577	154	477	1670	49	1	18	1	1	2	100441163	49	1	7	10	2008		70	99	1	2													1	7439	15666	2	1	1	1	1	174			1949	60	3	2	5			1967	1	10		11	2	4	4		1	4670	49	nan	1	2	1	3	1	1			2	2	1	2	3	2	2	3	2	2	2	2	1	2	2
170585	160	483	1768	147	1	18	1	1	2	100441190	147	1		1	2007		50	99	1	2													1	7933	16160	2	1	2	1	1	658			1961	48	1	2	5			1983		10	4	11	2	4	4	1	1	4777	147	nan	1	4	1	9	2				2	2	1	1	3	2	2	3	4	2	2	2	2	2	2
170593	168	491	1799	179	1	18	1	1	2	100441191	179	1		4	2008		48	99	1	2													1	8057	16285	2	1	2	1	1	777			1964	45	1	2	5			1980		10		11	2	4	4	1	1	4808	179	nan	1	3	1	5	2				2	2	1	1	3	2	2	3	4	2	2	2	2	2	2
170601	426	507	1886	265	1	18	1	1	2	100441226	338	1		1	2008	5		6	3	1	1	2	2	10									1	8436	22309	2	1	1	1	1	1152			1984	25	1	2	3			2004	3	3		11	2	2	4		1	6334	265	nan	1	2	1	9	2				2	2	1	1	3	2	2	3	4	2	2	2	2	2	2
170609	182	505	1931	310	1	18	1	1	2	100441192	310	1	1	1	2009		48	6	1	2													1	8632	22505	2	1	2	1	1	1342			1964	45	1	2	5			1983	2	10		11	2	4	4	1	1	6379	310	nan	1	2	1	3	2				2	2	1	2	3	1	2	3	2	2	2	2	1	2	2
170617	190	328	1990	26	1	18	1	1	1	100441339	27	1		12	2009		5	6	3	2													1	8865	14972	2	1	1	1	1	120			1979	30	2	3	3	20	10	2003	4	4		11	1	4	4		1	4511	27	nan	1	3	1	6	2				2	2	1	1	3	2	2	3	4	2	2	2	1	2	2
170625	197	335	2060	96	1	18	1	1	1	100441310	97	2		12	2009		35	5	1	2				9	1	3	3	4	4	9	3	9	1	9213	15321	2	1	1	1	1	470			1957	52	2	3	4		8	1991		3		11	2	4	4		1	4581	97	nan	1	2	1	6	2		7	2	2	2	1	1	3	2	2	3	4	2	2	2	1	2	2


CREATE TABLE mortality_18_as (
  "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" DOUBLE,
  "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" 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
);