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superset2/superset/examples/misc_charts/datasets/wb_health_population.yaml

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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
always_filter_main_dttm: false
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type: TIMESTAMP WITHOUT TIME ZONE
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python_date_format: null
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column_name: SP_POP_DPND
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python_date_format: null
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column_name: SP_POP_DPND_OL
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python_date_format: null
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column_name: SP_POP_DPND_YG
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python_date_format: null
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column_name: SP_POP_GROW
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python_date_format: null
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column_name: SP_POP_TOTL
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verbose_name: null
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column_name: SP_POP_TOTL_FE_ZS
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is_active: true
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python_date_format: null
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verbose_name: null
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column_name: SP_REG_BRTH_RU_ZS
description: null
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extra: null
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groupby: true
is_active: true
is_dttm: false
python_date_format: null
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verbose_name: null
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column_name: SP_REG_BRTH_UR_ZS
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column_name: SP_REG_BRTH_ZS
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python_date_format: null
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column_name: SP_REG_DTHS_ZS
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groupby: true
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is_dttm: false
python_date_format: null
type: FLOAT
verbose_name: null
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column_name: SP_RUR_TOTL
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python_date_format: null
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column_name: SP_RUR_TOTL_ZG
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column_name: SP_RUR_TOTL_ZS
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column_name: SP_URB_GROW
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python_date_format: null
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column_name: SP_URB_TOTL_IN_ZS
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is_active: true
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python_date_format: null
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verbose_name: null
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column_name: SP_UWT_TFRT
description: null
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data_file: wb_health_population.parquet
database_uuid: a2dc77af-e654-49bb-b321-40f6b559a1ee
default_endpoint: null
description: "<!--\nLicensed to the Apache Software Foundation (ASF) under one\nor\
\ more contributor license agreements. See the NOTICE file\ndistributed with this\
\ work for additional information\nregarding copyright ownership. The ASF licenses\
\ this file\nto you under the Apache License, Version 2.0 (the\n\"License\"); you\
\ may not use this file except in compliance\nwith the License. You may obtain\
\ a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\nUnless\
\ required by applicable law or agreed to in writing,\nsoftware distributed under\
\ the License is distributed on an\n\"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS\
\ OF ANY\nKIND, either express or implied. See the License for the\nspecific language\
\ governing permissions and limitations\nunder the License.\n-->\nThis data was\
\ downloaded from the\n[World's Health Organization's website](https://datacatalog.worldbank.org/dataset/health-nutrition-and-population-statistics)\n\
\nHere's the script that was used to massage the data:\n\n DIR = \"\"\n df_country\
\ = pd.read_csv(DIR + '/HNP_Country.csv')\n df_country.columns = ['country_code']\
\ + list(df_country.columns[1:])\n df_country = df_country[['country_code', 'Region']]\n\
\ df_country.columns = ['country_code', 'region']\n\n df = pd.read_csv(DIR\
\ + '/HNP_Data.csv')\n del df['Unnamed: 60']\n df.columns = ['country_name',\
\ 'country_code'] + list(df.columns[2:])\n ndf = df.merge(df_country, how='inner')\n\
\n dims = ('country_name', 'country_code', 'region')\n vv = [str(i) for i\
\ in range(1960, 2015)]\n mdf = pd.melt(ndf, id_vars=dims + ('Indicator Code',),\
\ value_vars=vv)\n mdf['year'] = mdf.variable + '-01-01'\n dims = dims + ('year',)\n\
\n pdf = mdf.pivot_table(values='value', columns='Indicator Code', index=dims)\n\
\ pdf = pdf.reset_index()\n pdf.to_csv(DIR + '/countries.csv')\n pdf.to_json(DIR\
\ + '/countries.json', orient='records')\n\nHere's the description of the metrics\
\ available:\n\nSeries | Code Indicator Name\n--- | ---\nNY.GNP.PCAP.CD | GNI per\
\ capita, Atlas method (current US$)\nSE.ADT.1524.LT.FM.ZS | Literacy rate, youth\
\ (ages 15-24), gender parity index (GPI)\nSE.ADT.1524.LT.MA.ZS | Literacy rate,\
\ youth male (% of males ages 15-24)\nSE.ADT.1524.LT.ZS | Literacy rate, youth total\
\ (% of people ages 15-24)\nSE.ADT.LITR.FE.ZS | Literacy rate, adult female (% of\
\ females ages 15 and above)\nSE.ADT.LITR.MA.ZS | Literacy rate, adult male (% of\
\ males ages 15 and above)\nSE.ADT.LITR.ZS | Literacy rate, adult total (% of people\
\ ages 15 and above)\nSE.ENR.ORPH | Ratio of school attendance of orphans to school\
\ attendance of non-orphans ages 10-14\nSE.PRM.CMPT.FE.ZS | Primary completion rate,\
\ female (% of relevant age group)\nSE.PRM.CMPT.MA.ZS | Primary completion rate,\
\ male (% of relevant age group)\nSE.PRM.CMPT.ZS | Primary completion rate, total\
\ (% of relevant age group)\nSE.PRM.ENRR | School enrollment, primary (% gross)\n\
SE.PRM.ENRR.FE | School enrollment, primary, female (% gross)\nSE.PRM.ENRR.MA |\
\ School enrollment, primary, male (% gross)\nSE.PRM.NENR | School enrollment, primary\
\ (% net)\nSE.PRM.NENR.FE | School enrollment, primary, female (% net)\nSE.PRM.NENR.MA\
\ | School enrollment, primary, male (% net)\nSE.SEC.ENRR | School enrollment, secondary\
\ (% gross)\nSE.SEC.ENRR.FE | School enrollment, secondary, female (% gross)\nSE.SEC.ENRR.MA\
\ | School enrollment, secondary, male (% gross)\nSE.SEC.NENR | School enrollment,\
\ secondary (% net)\nSE.SEC.NENR.FE | School enrollment, secondary, female (% net)\n\
SE.SEC.NENR.MA | School enrollment, secondary, male (% net)\nSE.TER.ENRR | School\
\ enrollment, tertiary (% gross)\nSE.TER.ENRR.FE | School enrollment, tertiary,\
\ female (% gross)\nSE.XPD.TOTL.GD.ZS | Government expenditure on education, total\
\ (% of GDP)\nSH.ANM.CHLD.ZS | Prevalence of anemia among children (% of children\
\ under 5)\nSH.ANM.NPRG.ZS | Prevalence of anemia among non-pregnant women (% of\
\ women ages 15-49)\nSH.CON.1524.FE.ZS | Condom use, population ages 15-24, female\
\ (% of females ages 15-24)\nSH.CON.1524.MA.ZS | Condom use, population ages 15-24,\
\ male (% of males ages 15-24)\nSH.CON.AIDS.FE.ZS | Condom use at last high-risk\
\ sex, adult female (% ages 15-49)\nSH.CON.AIDS.MA.ZS | Condom use at last high-risk\
\ sex, adult male (% ages 15-49)\nSH.DTH.COMM.ZS | Cause of death, by communicable\
\ diseases and maternal, prenatal and nutrition conditions (% of total)\nSH.DTH.IMRT\
\ | Number of infant deaths\nSH.DTH.INJR.ZS | Cause of death, by injury (% of total)\n\
SH.DTH.MORT | Number of under-five deaths\nSH.DTH.NCOM.ZS | Cause of death, by non-communicable\
\ diseases (% of total)\nSH.DTH.NMRT | Number of neonatal deaths\nSH.DYN.AIDS |\
\ Adults (ages 15+) living with HIV\nSH.DYN.AIDS.DH | AIDS estimated deaths (UNAIDS\
\ estimates)\nSH.DYN.AIDS.FE.ZS | Women's share of population ages 15+ living with\
\ HIV (%)\nSH.DYN.AIDS.ZS | Prevalence of HIV, total (% of population ages 15-49)\n\
SH.DYN.MORT | Mortality rate, under-5 (per 1,000 live births)\nSH.DYN.MORT.FE |\
\ Mortality rate, under-5, female (per 1,000 live births)\nSH.DYN.MORT.MA | Mortality\
\ rate, under-5, male (per 1,000 live births)\nSH.DYN.NMRT | Mortality rate, neonatal\
\ (per 1,000 live births)\nSH.FPL.SATI.ZS | Met need for contraception (% of married\
\ women ages 15-49)\nSH.H2O.SAFE.RU.ZS | Improved water source, rural (% of rural\
\ population with access)\nSH.H2O.SAFE.UR.ZS | Improved water source, urban (% of\
\ urban population with access)\nSH.H2O.SAFE.ZS | Improved water source (% of population\
\ with access)\nSH.HIV.0014 | Children (0-14) living with HIV\nSH.HIV.1524.FE.ZS\
\ | Prevalence of HIV, female (% ages 15-24)\nSH.HIV.1524.KW.FE.ZS | Comprehensive\
\ correct knowledge of HIV/AIDS, ages 15-24, female (2 prevent ways and reject 3\
\ misconceptions)\nSH.HIV.1524.KW.MA.ZS | Comprehensive correct knowledge of HIV/AIDS,\
\ ages 15-24, male (2 prevent ways and reject 3 misconceptions)\nSH.HIV.1524.MA.ZS\
\ | Prevalence of HIV, male (% ages 15-24)\nSH.HIV.ARTC.ZS | Antiretroviral therapy\
\ coverage (% of people living with HIV)\nSH.HIV.KNOW.FE.ZS | % of females ages\
\ 15-49 having comprehensive correct knowledge about HIV (2 prevent ways and reject\
\ 3 misconceptions)\nSH.HIV.KNOW.MA.ZS | % of males ages 15-49 having comprehensive\
\ correct knowledge about HIV (2 prevent ways and reject 3 misconceptions)\nSH.HIV.ORPH\
\ | Children orphaned by HIV/AIDS\nSH.HIV.TOTL | Adults (ages 15+) and children\
\ (0-14 years) living with HIV\nSH.IMM.HEPB | Immunization, HepB3 (% of one-year-old\
\ children)\nSH.IMM.HIB3 | Immunization, Hib3 (% of children ages 12-23 months)\n\
SH.IMM.IBCG | Immunization, BCG (% of one-year-old children)\nSH.IMM.IDPT | Immunization,\
\ DPT (% of children ages 12-23 months)\nSH.IMM.MEAS | Immunization, measles (%\
\ of children ages 12-23 months)\nSH.IMM.POL3 | Immunization, Pol3 (% of one-year-old\
\ children)\nSH.MED.BEDS.ZS | Hospital beds (per 1,000 people)\nSH.MED.CMHW.P3 |\
\ Community health workers (per 1,000 people)\nSH.MED.NUMW.P3 | Nurses and midwives\
\ (per 1,000 people)\nSH.MED.PHYS.ZS | Physicians (per 1,000 people)\nSH.MLR.NETS.ZS\
\ | Use of insecticide-treated bed nets (% of under-5 population)\nSH.MLR.PREG.ZS\
\ | Use of any antimalarial drug (% of pregnant women)\nSH.MLR.SPF2.ZS | Use of\
\ Intermittent Preventive Treatment of malaria, 2+ doses of SP/Fansidar (% of pregnant\
\ women)\nSH.MLR.TRET.ZS | Children with fever receiving antimalarial drugs (% of\
\ children under age 5 with fever)\nSH.MMR.DTHS | Number of maternal deaths\nSH.MMR.LEVE\
\ | Number of weeks of maternity leave\nSH.MMR.RISK | Lifetime risk of maternal\
\ death (1 in: rate varies by country)\nSH.MMR.RISK.ZS | Lifetime risk of maternal\
\ death (%)\nSH.MMR.WAGE.ZS | Maternal leave benefits (% of wages paid in covered\
\ period)\nSH.PRG.ANEM | Prevalence of anemia among pregnant women (%)\nSH.PRG.ARTC.ZS\
\ | Antiretroviral therapy coverage (% of pregnant women living with HIV)\nSH.PRG.SYPH.ZS\
\ | Prevalence of syphilis (% of women attending antenatal care)\nSH.PRV.SMOK.FE\
\ | Smoking prevalence, females (% of adults)\nSH.PRV.SMOK.MA | Smoking prevalence,\
\ males (% of adults)\nSH.STA.ACSN | Improved sanitation facilities (% of population\
\ with access)\nSH.STA.ACSN.RU | Improved sanitation facilities, rural (% of rural\
\ population with access)\nSH.STA.ACSN.UR | Improved sanitation facilities, urban\
\ (% of urban population with access)\nSH.STA.ANV4.ZS | Pregnant women receiving\
\ prenatal care of at least four visits (% of pregnant women)\nSH.STA.ANVC.ZS |\
\ Pregnant women receiving prenatal care (%)\nSH.STA.ARIC.ZS | ARI treatment (%\
\ of children under 5 taken to a health provider)\nSH.STA.BFED.ZS | Exclusive breastfeeding\
\ (% of children under 6 months)\nSH.STA.BRTC.ZS | Births attended by skilled health\
\ staff (% of total)\nSH.STA.BRTW.ZS | Low-birthweight babies (% of births)\nSH.STA.DIAB.ZS\
\ | Diabetes prevalence (% of population ages 20 to 79)\nSH.STA.IYCF.ZS | Infant\
\ and young child feeding practices, all 3 IYCF (% children ages 6-23 months)\n\
SH.STA.MALN.FE.ZS | Prevalence of underweight, weight for age, female (% of children\
\ under 5)\nSH.STA.MALN.MA.ZS | Prevalence of underweight, weight for age, male\
\ (% of children under 5)\nSH.STA.MALN.ZS | Prevalence of underweight, weight for\
\ age (% of children under 5)\nSH.STA.MALR | Malaria cases reported\nSH.STA.MMRT\
\ | Maternal mortality ratio (modeled estimate, per 100,000 live births)\nSH.STA.MMRT.NE\
\ | Maternal mortality ratio (national estimate, per 100,000 live births)\nSH.STA.ORCF.ZS\
\ | Diarrhea treatment (% of children under 5 receiving oral rehydration and continued\
\ feeding)\nSH.STA.ORTH | Diarrhea treatment (% of children under 5 who received\
\ ORS packet)\nSH.STA.OW15.FE.ZS | Prevalence of overweight, female (% of female\
\ adults)\nSH.STA.OW15.MA.ZS | Prevalence of overweight, male (% of male adults)\n\
SH.STA.OW15.ZS | Prevalence of overweight (% of adults)\nSH.STA.OWGH.FE.ZS | Prevalence\
\ of overweight, weight for height, female (% of children under 5)\nSH.STA.OWGH.MA.ZS\
\ | Prevalence of overweight, weight for height, male (% of children under 5)\n\
SH.STA.OWGH.ZS | Prevalence of overweight, weight for height (% of children under\
\ 5)\nSH.STA.PNVC.ZS | Postnatal care coverage (% mothers)\nSH.STA.STNT.FE.ZS |\
\ Prevalence of stunting, height for age, female (% of children under 5)\nSH.STA.STNT.MA.ZS\
\ | Prevalence of stunting, height for age, male (% of children under 5)\nSH.STA.STNT.ZS\
\ | Prevalence of stunting, height for age (% of children under 5)\nSH.STA.WAST.FE.ZS\
\ | Prevalence of wasting, weight for height, female (% of children under 5)\nSH.STA.WAST.MA.ZS\
\ | Prevalence of wasting, weight for height, male (% of children under 5)\nSH.STA.WAST.ZS\
\ | Prevalence of wasting, weight for height (% of children under 5)\nSH.SVR.WAST.FE.ZS\
\ | Prevalence of severe wasting, weight for height, female (% of children under\
\ 5)\nSH.SVR.WAST.MA.ZS | Prevalence of severe wasting, weight for height, male\
\ (% of children under 5)\nSH.SVR.WAST.ZS | Prevalence of severe wasting, weight\
\ for height (% of children under 5)\nSH.TBS.CURE.ZS | Tuberculosis treatment success\
\ rate (% of new cases)\nSH.TBS.DTEC.ZS | Tuberculosis case detection rate (%, all\
\ forms)\nSH.TBS.INCD | Incidence of tuberculosis (per 100,000 people)\nSH.TBS.MORT\
\ | Tuberculosis death rate (per 100,000 people)\nSH.TBS.PREV | Prevalence of tuberculosis\
\ (per 100,000 population)\nSH.VAC.TTNS.ZS | Newborns protected against tetanus\
\ (%)\nSH.XPD.EXTR.ZS | External resources for health (% of total expenditure on\
\ health)\nSH.XPD.OOPC.TO.ZS | Out-of-pocket health expenditure (% of total expenditure\
\ on health)\nSH.XPD.OOPC.ZS | Out-of-pocket health expenditure (% of private expenditure\
\ on health)\nSH.XPD.PCAP | Health expenditure per capita (current US$)\nSH.XPD.PCAP.PP.KD\
\ | Health expenditure per capita, PPP (constant 2011 international $)\nSH.XPD.PRIV\
\ | Health expenditure, private (% of total health expenditure)\nSH.XPD.PRIV.ZS\
\ | Health expenditure, private (% of GDP)\nSH.XPD.PUBL | Health expenditure, public\
\ (% of total health expenditure)\nSH.XPD.PUBL.GX.ZS | Health expenditure, public\
\ (% of government expenditure)\nSH.XPD.PUBL.ZS | Health expenditure, public (%\
\ of GDP)\nSH.XPD.TOTL.CD | Health expenditure, total (current US$)\nSH.XPD.TOTL.ZS\
\ | Health expenditure, total (% of GDP)\nSI.POV.NAHC | Poverty headcount ratio\
\ at national poverty lines (% of population)\nSI.POV.RUHC | Rural poverty headcount\
\ ratio at national poverty lines (% of rural population)\nSI.POV.URHC | Urban poverty\
\ headcount ratio at national poverty lines (% of urban population)\nSL.EMP.INSV.FE.ZS\
\ | Share of women in wage employment in the nonagricultural sector (% of total\
\ nonagricultural employment)\nSL.TLF.TOTL.FE.ZS | Labor force, female (% of total\
\ labor force)\nSL.TLF.TOTL.IN | Labor force, total\nSL.UEM.TOTL.FE.ZS | Unemployment,\
\ female (% of female labor force) (modeled ILO estimate)\nSL.UEM.TOTL.MA.ZS | Unemployment,\
\ male (% of male labor force) (modeled ILO estimate)\nSL.UEM.TOTL.ZS | Unemployment,\
\ total (% of total labor force) (modeled ILO estimate)\nSM.POP.NETM | Net migration\n\
SN.ITK.DEFC | Number of people who are undernourished\nSN.ITK.DEFC.ZS | Prevalence\
\ of undernourishment (% of population)\nSN.ITK.SALT.ZS | Consumption of iodized\
\ salt (% of households)\nSN.ITK.VITA.ZS | Vitamin A supplementation coverage rate\
\ (% of children ages 6-59 months)\nSP.ADO.TFRT | Adolescent fertility rate (births\
\ per 1,000 women ages 15-19)\nSP.DYN.AMRT.FE | Mortality rate, adult, female (per\
\ 1,000 female adults)\nSP.DYN.AMRT.MA | Mortality rate, adult, male (per 1,000\
\ male adults)\nSP.DYN.CBRT.IN | Birth rate, crude (per 1,000 people)\nSP.DYN.CDRT.IN\
\ | Death rate, crude (per 1,000 people)\nSP.DYN.CONU.ZS | Contraceptive prevalence\
\ (% of women ages 15-49)\nSP.DYN.IMRT.FE.IN | Mortality rate, infant, female (per\
\ 1,000 live births)\nSP.DYN.IMRT.IN | Mortality rate, infant (per 1,000 live births)\n\
SP.DYN.IMRT.MA.IN | Mortality rate, infant, male (per 1,000 live births)\nSP.DYN.LE00.FE.IN\
\ | Life expectancy at birth, female (years)\nSP.DYN.LE00.IN | Life expectancy at\
\ birth, total (years)\nSP.DYN.LE00.MA.IN | Life expectancy at birth, male (years)\n\
SP.DYN.SMAM.FE | Mean age at first marriage, female\nSP.DYN.SMAM.MA | Mean age at\
\ first marriage, male\nSP.DYN.TFRT.IN | Fertility rate, total (births per woman)\n\
SP.DYN.TO65.FE.ZS | Survival to age 65, female (% of cohort)\nSP.DYN.TO65.MA.ZS\
\ | Survival to age 65, male (% of cohort)\nSP.DYN.WFRT | Wanted fertility rate\
\ (births per woman)\nSP.HOU.FEMA.ZS | Female headed households (% of households\
\ with a female head)\nSP.MTR.1519.ZS | Teenage mothers (% of women ages 15-19 who\
\ have had children or are currently pregnant)\nSP.POP.0004.FE | Population ages\
\ 0-4, female\nSP.POP.0004.FE.5Y | Population ages 0-4, female (% of female population)\n\
SP.POP.0004.MA | Population ages 0-4, male\nSP.POP.0004.MA.5Y | Population ages\
\ 0-4, male (% of male population)\nSP.POP.0014.FE.ZS | Population ages 0-14, female\
\ (% of total)\nSP.POP.0014.MA.ZS | Population ages 0-14, male (% of total)\nSP.POP.0014.TO\
\ | Population ages 0-14, total\nSP.POP.0014.TO.ZS | Population ages 0-14 (% of\
\ total)\nSP.POP.0509.FE | Population ages 5-9, female\nSP.POP.0509.FE.5Y | Population\
\ ages 5-9, female (% of female population)\nSP.POP.0509.MA | Population ages 5-9,\
\ male\nSP.POP.0509.MA.5Y | Population ages 5-9, male (% of male population)\nSP.POP.1014.FE\
\ | Population ages 10-14, female\nSP.POP.1014.FE.5Y | Population ages 10-14, female\
\ (% of female population)\nSP.POP.1014.MA | Population ages 10-14, male\nSP.POP.1014.MA.5Y\
\ | Population ages 10-14, male (% of male population)\nSP.POP.1519.FE | Population\
\ ages 15-19, female\nSP.POP.1519.FE.5Y | Population ages 15-19, female (% of female\
\ population)\nSP.POP.1519.MA | Population ages 15-19, male\nSP.POP.1519.MA.5Y |\
\ Population ages 15-19, male (% of male population)\nSP.POP.1564.FE.ZS | Population\
\ ages 15-64, female (% of total)\nSP.POP.1564.MA.ZS | Population ages 15-64, male\
\ (% of total)\nSP.POP.1564.TO | Population ages 15-64, total\nSP.POP.1564.TO.ZS\
\ | Population ages 15-64 (% of total)\nSP.POP.2024.FE | Population ages 20-24,\
\ female\nSP.POP.2024.FE.5Y | Population ages 20-24, female (% of female population)\n\
SP.POP.2024.MA | Population ages 20-24, male\nSP.POP.2024.MA.5Y | Population ages\
\ 20-24, male (% of male population)\nSP.POP.2529.FE | Population ages 25-29, female\n\
SP.POP.2529.FE.5Y | Population ages 25-29, female (% of female population)\nSP.POP.2529.MA\
\ | Population ages 25-29, male\nSP.POP.2529.MA.5Y | Population ages 25-29, male\
\ (% of male population)\nSP.POP.3034.FE | Population ages 30-34, female\nSP.POP.3034.FE.5Y\
\ | Population ages 30-34, female (% of female population)\nSP.POP.3034.MA | Population\
\ ages 30-34, male\nSP.POP.3034.MA.5Y | Population ages 30-34, male (% of male population)\n\
SP.POP.3539.FE | Population ages 35-39, female\nSP.POP.3539.FE.5Y | Population ages\
\ 35-39, female (% of female population)\nSP.POP.3539.MA | Population ages 35-39,\
\ male\nSP.POP.3539.MA.5Y | Population ages 35-39, male (% of male population)\n\
SP.POP.4044.FE | Population ages 40-44, female\nSP.POP.4044.FE.5Y | Population ages\
\ 40-44, female (% of female population)\nSP.POP.4044.MA | Population ages 40-44,\
\ male\nSP.POP.4044.MA.5Y | Population ages 40-44, male (% of male population)\n\
SP.POP.4549.FE | Population ages 45-49, female\nSP.POP.4549.FE.5Y | Population ages\
\ 45-49, female (% of female population)\nSP.POP.4549.MA | Population ages 45-49,\
\ male\nSP.POP.4549.MA.5Y | Population ages 45-49, male (% of male population)\n\
SP.POP.5054.FE | Population ages 50-54, female\nSP.POP.5054.FE.5Y | Population ages\
\ 50-54, female (% of female population)\nSP.POP.5054.MA | Population ages 50-54,\
\ male\nSP.POP.5054.MA.5Y | Population ages 50-54, male (% of male population)\n\
SP.POP.5559.FE | Population ages 55-59, female\nSP.POP.5559.FE.5Y | Population ages\
\ 55-59, female (% of female population)\nSP.POP.5559.MA | Population ages 55-59,\
\ male\nSP.POP.5559.MA.5Y | Population ages 55-59, male (% of male population)\n\
SP.POP.6064.FE | Population ages 60-64, female\nSP.POP.6064.FE.5Y | Population ages\
\ 60-64, female (% of female population)\nSP.POP.6064.MA | Population ages 60-64,\
\ male\nSP.POP.6064.MA.5Y | Population ages 60-64, male (% of male population)\n\
SP.POP.6569.FE | Population ages 65-69, female\nSP.POP.6569.FE.5Y | Population ages\
\ 65-69, female (% of female population)\nSP.POP.6569.MA | Population ages 65-69,\
\ male\nSP.POP.6569.MA.5Y | Population ages 65-69, male (% of male population)\n\
SP.POP.65UP.FE.ZS | Population ages 65 and above, female (% of total)\nSP.POP.65UP.MA.ZS\
\ | Population ages 65 and above, male (% of total)\nSP.POP.65UP.TO | Population\
\ ages 65 and above, total\nSP.POP.65UP.TO.ZS | Population ages 65 and above (%\
\ of total)\nSP.POP.7074.FE | Population ages 70-74, female\nSP.POP.7074.FE.5Y |\
\ Population ages 70-74, female (% of female population)\nSP.POP.7074.MA | Population\
\ ages 70-74, male\nSP.POP.7074.MA.5Y | Population ages 70-74, male (% of male population)\n\
SP.POP.7579.FE | Population ages 75-79, female\nSP.POP.7579.FE.5Y | Population ages\
\ 75-79, female (% of female population)\nSP.POP.7579.MA | Population ages 75-79,\
\ male\nSP.POP.7579.MA.5Y | Population ages 75-79, male (% of male population)\n\
SP.POP.80UP.FE | Population ages 80 and above, female\nSP.POP.80UP.FE.5Y | Population\
\ ages 80 and above, female (% of female population)\nSP.POP.80UP.MA | Population\
\ ages 80 and above, male\nSP.POP.80UP.MA.5Y | Population ages 80 and above, male\
\ (% of male population)\nSP.POP.AG00.FE.IN | Age population, age 0, female, interpolated\n\
SP.POP.AG00.MA.IN | Age population, age 0, male, interpolated\nSP.POP.AG01.FE.IN\
\ | Age population, age 01, female, interpolated\nSP.POP.AG01.MA.IN | Age population,\
\ age 01, male, interpolated\nSP.POP.AG02.FE.IN | Age population, age 02, female,\
\ interpolated\nSP.POP.AG02.MA.IN | Age population, age 02, male, interpolated\n\
SP.POP.AG03.FE.IN | Age population, age 03, female, interpolated\nSP.POP.AG03.MA.IN\
\ | Age population, age 03, male, interpolated\nSP.POP.AG04.FE.IN | Age population,\
\ age 04, female, interpolated\nSP.POP.AG04.MA.IN | Age population, age 04, male,\
\ interpolated\nSP.POP.AG05.FE.IN | Age population, age 05, female, interpolated\n\
SP.POP.AG05.MA.IN | Age population, age 05, male, interpolated\nSP.POP.AG06.FE.IN\
\ | Age population, age 06, female, interpolated\nSP.POP.AG06.MA.IN | Age population,\
\ age 06, male, interpolated\nSP.POP.AG07.FE.IN | Age population, age 07, female,\
\ interpolated\nSP.POP.AG07.MA.IN | Age population, age 07, male, interpolated\n\
SP.POP.AG08.FE.IN | Age population, age 08, female, interpolated\nSP.POP.AG08.MA.IN\
\ | Age population, age 08, male, interpolated\nSP.POP.AG09.FE.IN | Age population,\
\ age 09, female, interpolated\nSP.POP.AG09.MA.IN | Age population, age 09, male,\
\ interpolated\nSP.POP.AG10.FE.IN | Age population, age 10, female, interpolated\n\
SP.POP.AG10.MA.IN | Age population, age 10, male\nSP.POP.AG11.FE.IN | Age population,\
\ age 11, female, interpolated\nSP.POP.AG11.MA.IN | Age population, age 11, male\n\
SP.POP.AG12.FE.IN | Age population, age 12, female, interpolated\nSP.POP.AG12.MA.IN\
\ | Age population, age 12, male\nSP.POP.AG13.FE.IN | Age population, age 13, female,\
\ interpolated\nSP.POP.AG13.MA.IN | Age population, age 13, male\nSP.POP.AG14.FE.IN\
\ | Age population, age 14, female, interpolated\nSP.POP.AG14.MA.IN | Age population,\
\ age 14, male\nSP.POP.AG15.FE.IN | Age population, age 15, female, interpolated\n\
SP.POP.AG15.MA.IN | Age population, age 15, male, interpolated\nSP.POP.AG16.FE.IN\
\ | Age population, age 16, female, interpolated\nSP.POP.AG16.MA.IN | Age population,\
\ age 16, male, interpolated\nSP.POP.AG17.FE.IN | Age population, age 17, female,\
\ interpolated\nSP.POP.AG17.MA.IN | Age population, age 17, male, interpolated\n\
SP.POP.AG18.FE.IN | Age population, age 18, female, interpolated\nSP.POP.AG18.MA.IN\
\ | Age population, age 18, male, interpolated\nSP.POP.AG19.FE.IN | Age population,\
\ age 19, female, interpolated\nSP.POP.AG19.MA.IN | Age population, age 19, male,\
\ interpolated\nSP.POP.AG20.FE.IN | Age population, age 20, female, interpolated\n\
SP.POP.AG20.MA.IN | Age population, age 20, male, interpolated\nSP.POP.AG21.FE.IN\
\ | Age population, age 21, female, interpolated\nSP.POP.AG21.MA.IN | Age population,\
\ age 21, male, interpolated\nSP.POP.AG22.FE.IN | Age population, age 22, female,\
\ interpolated\nSP.POP.AG22.MA.IN | Age population, age 22, male, interpolated\n\
SP.POP.AG23.FE.IN | Age population, age 23, female, interpolated\nSP.POP.AG23.MA.IN\
\ | Age population, age 23, male, interpolated\nSP.POP.AG24.FE.IN | Age population,\
\ age 24, female, interpolated\nSP.POP.AG24.MA.IN | Age population, age 24, male,\
\ interpolated\nSP.POP.AG25.FE.IN | Age population, age 25, female, interpolated\n\
SP.POP.AG25.MA.IN | Age population, age 25, male, interpolated\nSP.POP.BRTH.MF |\
\ Sex ratio at birth (male births per female births)\nSP.POP.DPND | Age dependency\
\ ratio (% of working-age population)\nSP.POP.DPND.OL | Age dependency ratio, old\
\ (% of working-age population)\nSP.POP.DPND.YG | Age dependency ratio, young (%\
\ of working-age population)\nSP.POP.GROW | Population growth (annual %)\nSP.POP.TOTL\
\ | Population, total\nSP.POP.TOTL.FE.IN | Population, female\nSP.POP.TOTL.FE.ZS\
\ | Population, female (% of total)\nSP.POP.TOTL.MA.IN | Population, male\nSP.POP.TOTL.MA.ZS\
\ | Population, male (% of total)\nSP.REG.BRTH.RU.ZS | Completeness of birth registration,\
\ rural (%)\nSP.REG.BRTH.UR.ZS | Completeness of birth registration, urban (%)\n\
SP.REG.BRTH.ZS | Completeness of birth registration (%)\nSP.REG.DTHS.ZS | Completeness\
\ of death registration with cause-of-death information (%)\nSP.RUR.TOTL | Rural\
\ population\nSP.RUR.TOTL.ZG | Rural population growth (annual %)\nSP.RUR.TOTL.ZS\
\ | Rural population (% of total population)\nSP.URB.GROW | Urban population growth\
\ (annual %)\nSP.URB.TOTL | Urban population\nSP.URB.TOTL.IN.ZS | Urban population\
\ (% of total)\nSP.UWT.TFRT | Unmet need for contraception (% of married women ages\
\ 15-49)\n"
extra: null
fetch_values_predicate: null
filter_select_enabled: true
folders: null
main_dttm_col: year
metrics:
- currency: null
d3format: null
description: null
expression: sum("SP_POP_TOTL")
extra: null
metric_name: sum__SP_POP_TOTL
metric_type: null
verbose_name: null
warning_text: null
- currency: null
d3format: null
description: null
expression: sum("SH_DYN_AIDS")
extra: null
metric_name: sum__SH_DYN_AIDS
metric_type: null
verbose_name: null
warning_text: null
- currency: null
d3format: null
description: null
expression: sum("SP_RUR_TOTL_ZS")
extra: null
metric_name: sum__SP_RUR_TOTL_ZS
metric_type: null
verbose_name: null
warning_text: null
- currency: null
d3format: null
description: null
expression: sum("SP_DYN_LE00_IN")
extra: null
metric_name: sum__SP_DYN_LE00_IN
metric_type: null
verbose_name: null
warning_text: null
- currency: null
d3format: null
description: null
expression: sum("SP_RUR_TOTL")
extra: null
metric_name: sum__SP_RUR_TOTL
metric_type: null
verbose_name: null
warning_text: null
- currency: null
d3format: null
description: null
expression: COUNT(*)
extra: null
metric_name: count
metric_type: count
verbose_name: COUNT(*)
warning_text: null
normalize_columns: false
offset: 0
params: null
schema: null
sql: null
table_name: wb_health_population
template_params: null
uuid: 69e9de42-fe7f-4948-946a-f7913227aee8
version: 1.0.0
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