Name: Predict Mortality/Death Rate.
Creator: Kaggle
License: https://creativecommons.org/licenses/by-sa/4.0/

About this Dataset

Predict Mortality/Death Rate.

Context:

**Annual Health Survey : Mortality Schedule **

This unit level dataset contains the details relating to death occurred to usual residents of sample household during the reference period and it includes information on sex of deceased, date of death, age at death, registration of death and source of medical attention received before death. For infant deaths, data related to symptoms preceding death is also provided. Mortality Schedule also includes information on various determinants of maternal mortality viz. case of deaths associated with pregnancy, information on factors leading/ contributing to death, symptoms preceding death, time between onset of complications and death, etc.

There are total of 770k observations and 121 variables in this dataset.

Survey:

Base line survey - 2010-11 (4.14 million households in the sample)
1st update - 2011-12 (4.28 million households in the sample)
2nd update - 2012-13 (4.32 million households in the sample)

The survey was conducted in the below 9 states.

A. Empowered Action Group (EAG) States

Uttarakhand (05)
Rajasthan (08)
Uttar Pradesh (09)
Bihar (10)
Jharkhand (20)
Odisha (21)
Chhattisgarh (22)
Madhya Pradesh (23)

B. Assam. (18)

These nine states, which account for about 48 percent of the total population, 59 percent of Births, 70 percent of Infant Deaths, 75 percent of Under 5 Deaths and 62 percent of Maternal Deaths in the country, are the high focus States in view of their relatively higher fertility and mortality.

Content:

The files contains the below columns.

Variable Names:

id
m_id
client_m_id
hl_id
house_no
house_hold_no
state
district
rural
stratum_code
psu_id
m_serial_no
deceased_sex
date_of_death
month_of_death
year_of_death
age_of_death_below_one_month
age_of_death_below_eleven_month
age_of_death_above_one_year
treatment_source
place_of_death
is_death_reg
is_death_certificate_received
serial_num_of_infant_mother
order_of_birth
death_symptoms
is_death_associated_with_pregnan
death_period
months_of_pregnancy
factors_contributing_death
factors_contributing_death_2
symptoms_of_death
time_between_onset_of_complicati
nearest_medical_facility
m_expall_status
field38
hh_id
client_hh_id
currently_dead_or_out_migrated
hh_serial_no
sex
usual_residance
relation_to_head
member_identity
father_serial_no
mother_serial_no
date_of_birth
month_of_birth
year_of_birth
age
religion
social_group_code
marital_status
date_of_marriage
month_of_marriage
year_of_marriage
currently_attending_school
reason_for_not_attending_school
highest_qualification
occupation_status
disability_status
injury_treatment_type
illness_type
symptoms_pertaining_illness
sought_medical_care
diagnosed_for
diagnosis_source
regular_treatment
regular_treatment_source
chew
smoke
alcohol
status
hh_expall_status
client_hl_id
serial_no
building_no
house_status
house_structure
owner_status
drinking_water_source
is_water_filter
water_filteration
toilet_used
is_toilet_shared
household_have_electricity
lighting_source
cooking_fuel
no_of_dwelling_rooms
kitchen_availability
is_radio
is_television
is_computer
is_telephone
is_washing_machine
is_refrigerator
is_sewing_machine
is_bicycle
is_scooter
is_car
is_tractor
is_water_pump
cart
land_possessed
hl_expall_status
fid
isdeadmigrated
residancial_status
iscoveredbyhealthscheme
healthscheme_1
healthscheme_2
housestatus
householdstatus
isheadchanged
fidh
fidx
as
wt
x
schedule_id
year

File content:
Mortality_data_dictionary.xlsx : This data dictionary excel work book has the detailed information about each and every column and codes used in the data.

Acknowledgements

Department of Health and Family Welfare, Govt. of India has published this dataset in Open Govt Data Platform India portal under Govt. Open Data License - India.

Tables

Mortality 05 Ut

@kaggle.rajanand_mortality.mortality_05_ut

4.1 MB
53,503 rows
122 columns

CREATE TABLE mortality_05_ut (
  "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" DOUBLE,
  "deceased_sex" BIGINT,
  "date_of_death" DOUBLE,
  "month_of_death" DOUBLE,
  "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
);

Mortality 08 Rj

@kaggle.rajanand_mortality.mortality_08_rj

3.95 MB
57,573 rows
122 columns

CREATE TABLE mortality_08_rj (
  "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" DOUBLE,
  "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
);

Mortality 09 Up

@kaggle.rajanand_mortality.mortality_09_up

16.46 MB
191,589 rows
122 columns

CREATE TABLE mortality_09_up (
  "id" BIGINT,
  "m_id" VARCHAR,
  "client_m_id" DOUBLE,
  "hl_id" VARCHAR,
  "house_no" BIGINT,
  "house_hold_no" BIGINT,
  "state" BIGINT,
  "district" BIGINT,
  "rural" BIGINT,
  "stratum_code" BIGINT,
  "psu_id" BIGINT,
  "m_serial_no" DOUBLE,
  "deceased_sex" BIGINT,
  "date_of_death" DOUBLE,
  "month_of_death" DOUBLE,
  "year_of_death" DOUBLE,
  "age_of_death_below_one_month" VARCHAR,
  "age_of_death_below_eleven_month" VARCHAR,
  "age_of_death_above_one_year" VARCHAR,
  "treatment_source" VARCHAR,
  "place_of_death" VARCHAR,
  "is_death_reg" DOUBLE,
  "is_death_certificate_received" VARCHAR,
  "serial_num_of_infant_mother" VARCHAR,
  "order_of_birth" VARCHAR,
  "death_symptoms" VARCHAR,
  "is_death_associated_with_pregnan" VARCHAR,
  "death_period" VARCHAR,
  "months_of_pregnancy" VARCHAR,
  "factors_contributing_death" VARCHAR,
  "factors_contributing_death_2" VARCHAR,
  "symptoms_of_death" VARCHAR,
  "time_between_onset_of_complicati" VARCHAR,
  "nearest_medical_facility" VARCHAR,
  "m_expall_status" DOUBLE,
  "field38" VARCHAR,
  "hh_id" VARCHAR,
  "client_hh_id" VARCHAR,
  "currently_dead_or_out_migrated" VARCHAR,
  "hh_serial_no" VARCHAR,
  "sex" VARCHAR,
  "usual_residance" VARCHAR,
  "relation_to_head" VARCHAR,
  "member_identity" VARCHAR,
  "father_serial_no" VARCHAR,
  "mother_serial_no" VARCHAR,
  "date_of_birth" VARCHAR,
  "month_of_birth" VARCHAR,
  "year_of_birth" VARCHAR,
  "age" VARCHAR,
  "religion" VARCHAR,
  "social_group_code" VARCHAR,
  "marital_status" VARCHAR,
  "date_of_marriage" VARCHAR,
  "month_of_marriage" VARCHAR,
  "year_of_marriage" VARCHAR,
  "currently_attending_school" VARCHAR,
  "reason_for_not_attending_school" VARCHAR,
  "highest_qualification" VARCHAR,
  "occupation_status" VARCHAR,
  "disability_status" VARCHAR,
  "injury_treatment_type" VARCHAR,
  "illness_type" VARCHAR,
  "symptoms_pertaining_illness" VARCHAR,
  "sought_medical_care" VARCHAR,
  "diagnosed_for" VARCHAR,
  "diagnosis_source" VARCHAR,
  "regular_treatment" VARCHAR,
  "regular_treatment_source" VARCHAR,
  "chew" VARCHAR,
  "smoke" VARCHAR,
  "alcohol" VARCHAR,
  "status" VARCHAR,
  "hh_expall_status" VARCHAR,
  "client_hl_id" VARCHAR,
  "serial_no" VARCHAR,
  "building_no" VARCHAR,
  "house_status" VARCHAR,
  "house_structure" VARCHAR,
  "owner_status" VARCHAR,
  "drinking_water_source" VARCHAR,
  "is_water_filter" VARCHAR,
  "water_filteration" VARCHAR,
  "toilet_used" VARCHAR,
  "is_toilet_shared" VARCHAR,
  "household_have_electricity" VARCHAR,
  "lighting_source" VARCHAR,
  "cooking_fuel" VARCHAR,
  "no_of_dwelling_rooms" VARCHAR,
  "kitchen_availability" VARCHAR,
  "is_radio" VARCHAR,
  "is_television" VARCHAR,
  "is_computer" VARCHAR,
  "is_telephone" VARCHAR,
  "is_washing_machine" VARCHAR,
  "is_refrigerator" VARCHAR,
  "is_sewing_machine" VARCHAR,
  "is_bicycle" VARCHAR,
  "is_scooter" VARCHAR,
  "is_car" VARCHAR
);

Mortality 10 Bh

@kaggle.rajanand_mortality.mortality_10_bh

7.45 MB
107,238 rows
122 columns

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
);

Mortality 18 As

@kaggle.rajanand_mortality.mortality_18_as

4.92 MB
71,003 rows
122 columns

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
);

Mortality 20 Jh

@kaggle.rajanand_mortality.mortality_20_jh

4.06 MB
59,062 rows
122 columns

CREATE TABLE mortality_20_jh (
  "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" DOUBLE,
  "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" 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
);

Mortality 21 Or

@kaggle.rajanand_mortality.mortality_21_or

6.22 MB
94,619 rows
122 columns

CREATE TABLE mortality_21_or (
  "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" DOUBLE,
  "deceased_sex" BIGINT,
  "date_of_death" DOUBLE,
  "month_of_death" DOUBLE,
  "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
);

Mortality 22 Ct

@kaggle.rajanand_mortality.mortality_22_ct

3.31 MB
44,251 rows
122 columns

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
);

Mortality 23 Mp

@kaggle.rajanand_mortality.mortality_23_mp

7.85 MB
90,744 rows
122 columns

CREATE TABLE mortality_23_mp (
  "id" BIGINT,
  "m_id" VARCHAR,
  "client_m_id" VARCHAR,
  "hl_id" VARCHAR,
  "house_no" BIGINT,
  "house_hold_no" BIGINT,
  "state" BIGINT,
  "district" BIGINT,
  "rural" BIGINT,
  "stratum_code" BIGINT,
  "psu_id" BIGINT,
  "m_serial_no" VARCHAR,
  "deceased_sex" BIGINT,
  "date_of_death" DOUBLE,
  "month_of_death" VARCHAR,
  "year_of_death" DOUBLE,
  "age_of_death_below_one_month" VARCHAR,
  "age_of_death_below_eleven_month" VARCHAR,
  "age_of_death_above_one_year" VARCHAR,
  "treatment_source" DOUBLE,
  "place_of_death" DOUBLE,
  "is_death_reg" DOUBLE,
  "is_death_certificate_received" VARCHAR,
  "serial_num_of_infant_mother" VARCHAR,
  "order_of_birth" VARCHAR,
  "death_symptoms" VARCHAR,
  "is_death_associated_with_pregnan" VARCHAR,
  "death_period" VARCHAR,
  "months_of_pregnancy" VARCHAR,
  "factors_contributing_death" VARCHAR,
  "factors_contributing_death_2" VARCHAR,
  "symptoms_of_death" VARCHAR,
  "time_between_onset_of_complicati" VARCHAR,
  "nearest_medical_facility" VARCHAR,
  "m_expall_status" DOUBLE,
  "field38" VARCHAR,
  "hh_id" VARCHAR,
  "client_hh_id" VARCHAR,
  "currently_dead_or_out_migrated" VARCHAR,
  "hh_serial_no" VARCHAR,
  "sex" VARCHAR,
  "usual_residance" VARCHAR,
  "relation_to_head" VARCHAR,
  "member_identity" VARCHAR,
  "father_serial_no" VARCHAR,
  "mother_serial_no" VARCHAR,
  "date_of_birth" VARCHAR,
  "month_of_birth" VARCHAR,
  "year_of_birth" VARCHAR,
  "age" VARCHAR,
  "religion" VARCHAR,
  "social_group_code" VARCHAR,
  "marital_status" VARCHAR,
  "date_of_marriage" VARCHAR,
  "month_of_marriage" VARCHAR,
  "year_of_marriage" VARCHAR,
  "currently_attending_school" VARCHAR,
  "reason_for_not_attending_school" VARCHAR,
  "highest_qualification" VARCHAR,
  "occupation_status" VARCHAR,
  "disability_status" VARCHAR,
  "injury_treatment_type" VARCHAR,
  "illness_type" VARCHAR,
  "symptoms_pertaining_illness" VARCHAR,
  "sought_medical_care" VARCHAR,
  "diagnosed_for" VARCHAR,
  "diagnosis_source" VARCHAR,
  "regular_treatment" VARCHAR,
  "regular_treatment_source" VARCHAR,
  "chew" VARCHAR,
  "smoke" VARCHAR,
  "alcohol" VARCHAR,
  "status" VARCHAR,
  "hh_expall_status" VARCHAR,
  "client_hl_id" VARCHAR,
  "serial_no" VARCHAR,
  "building_no" VARCHAR,
  "house_status" VARCHAR,
  "house_structure" VARCHAR,
  "owner_status" VARCHAR,
  "drinking_water_source" VARCHAR,
  "is_water_filter" VARCHAR,
  "water_filteration" VARCHAR,
  "toilet_used" VARCHAR,
  "is_toilet_shared" VARCHAR,
  "household_have_electricity" VARCHAR,
  "lighting_source" VARCHAR,
  "cooking_fuel" VARCHAR,
  "no_of_dwelling_rooms" VARCHAR,
  "kitchen_availability" VARCHAR,
  "is_radio" VARCHAR,
  "is_television" VARCHAR,
  "is_computer" VARCHAR,
  "is_telephone" VARCHAR,
  "is_washing_machine" VARCHAR,
  "is_refrigerator" VARCHAR,
  "is_sewing_machine" VARCHAR,
  "is_bicycle" VARCHAR,
  "is_scooter" VARCHAR,
  "is_car" VARCHAR
);