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Column Verbose Name Type Groupable Filterable Is temporal
country_name None VARCHAR(255)
country_code None VARCHAR(3)
region None VARCHAR(255)
year None TIMESTAMP WITHOUT TIME ZONE
NY_GNP_PCAP_CD None DOUBLE PRECISION
SE_ADT_1524_LT_FM_ZS None DOUBLE PRECISION
SE_ADT_1524_LT_MA_ZS None DOUBLE PRECISION
SE_ADT_1524_LT_ZS None DOUBLE PRECISION
SE_ADT_LITR_FE_ZS None DOUBLE PRECISION
SE_ADT_LITR_MA_ZS None DOUBLE PRECISION
SE_ADT_LITR_ZS None DOUBLE PRECISION
SE_ENR_ORPH None DOUBLE PRECISION
SE_PRM_CMPT_FE_ZS None DOUBLE PRECISION
SE_PRM_CMPT_MA_ZS None DOUBLE PRECISION
SE_PRM_CMPT_ZS None DOUBLE PRECISION
SE_PRM_ENRR None DOUBLE PRECISION
SE_PRM_ENRR_FE None DOUBLE PRECISION
SE_PRM_ENRR_MA None DOUBLE PRECISION
SE_PRM_NENR None DOUBLE PRECISION
SE_PRM_NENR_FE None DOUBLE PRECISION
SE_PRM_NENR_MA None DOUBLE PRECISION
SE_SEC_ENRR None DOUBLE PRECISION
SE_SEC_ENRR_FE None DOUBLE PRECISION
SE_SEC_ENRR_MA None DOUBLE PRECISION
SE_SEC_NENR None DOUBLE PRECISION
SE_SEC_NENR_FE None DOUBLE PRECISION
SE_SEC_NENR_MA None DOUBLE PRECISION
SE_TER_ENRR None DOUBLE PRECISION
SE_TER_ENRR_FE None DOUBLE PRECISION
SE_XPD_TOTL_GD_ZS None DOUBLE PRECISION
SH_ANM_CHLD_ZS None DOUBLE PRECISION
SH_ANM_NPRG_ZS None DOUBLE PRECISION
SH_CON_1524_FE_ZS None DOUBLE PRECISION
SH_CON_1524_MA_ZS None DOUBLE PRECISION
SH_CON_AIDS_FE_ZS None DOUBLE PRECISION
SH_CON_AIDS_MA_ZS None DOUBLE PRECISION
SH_DTH_COMM_ZS None DOUBLE PRECISION
SH_DTH_IMRT None DOUBLE PRECISION
SH_DTH_INJR_ZS None DOUBLE PRECISION
SH_DTH_MORT None DOUBLE PRECISION
SH_DTH_NCOM_ZS None DOUBLE PRECISION
SH_DTH_NMRT None DOUBLE PRECISION
SH_DYN_AIDS None DOUBLE PRECISION
SH_DYN_AIDS_DH None DOUBLE PRECISION
SH_DYN_AIDS_FE_ZS None DOUBLE PRECISION
SH_DYN_AIDS_ZS None DOUBLE PRECISION
SH_DYN_MORT None DOUBLE PRECISION
SH_DYN_MORT_FE None DOUBLE PRECISION
SH_DYN_MORT_MA None DOUBLE PRECISION
SH_DYN_NMRT None DOUBLE PRECISION
SH_FPL_SATI_ZS None DOUBLE PRECISION
SH_H2O_SAFE_RU_ZS None DOUBLE PRECISION
SH_H2O_SAFE_UR_ZS None DOUBLE PRECISION
SH_H2O_SAFE_ZS None DOUBLE PRECISION
SH_HIV_0014 None DOUBLE PRECISION
SH_HIV_1524_FE_ZS None DOUBLE PRECISION
SH_HIV_1524_KW_FE_ZS None DOUBLE PRECISION
SH_HIV_1524_KW_MA_ZS None DOUBLE PRECISION
SH_HIV_1524_MA_ZS None DOUBLE PRECISION
SH_HIV_ARTC_ZS None DOUBLE PRECISION
SH_HIV_KNOW_FE_ZS None DOUBLE PRECISION
SH_HIV_KNOW_MA_ZS None DOUBLE PRECISION
SH_HIV_ORPH None DOUBLE PRECISION
SH_HIV_TOTL None DOUBLE PRECISION
SH_IMM_HEPB None DOUBLE PRECISION
SH_IMM_HIB3 None DOUBLE PRECISION
SH_IMM_IBCG None DOUBLE PRECISION
SH_IMM_IDPT None DOUBLE PRECISION
SH_IMM_MEAS None DOUBLE PRECISION
SH_IMM_POL3 None DOUBLE PRECISION
SH_MED_BEDS_ZS None DOUBLE PRECISION
SH_MED_CMHW_P3 None DOUBLE PRECISION
SH_MED_NUMW_P3 None DOUBLE PRECISION
SH_MED_PHYS_ZS None DOUBLE PRECISION
SH_MLR_NETS_ZS None DOUBLE PRECISION
SH_MLR_PREG_ZS None DOUBLE PRECISION
SH_MLR_SPF2_ZS None DOUBLE PRECISION
SH_MLR_TRET_ZS None DOUBLE PRECISION
SH_MMR_DTHS None DOUBLE PRECISION
SH_MMR_LEVE None DOUBLE PRECISION
SH_MMR_RISK None DOUBLE PRECISION
SH_MMR_RISK_ZS None DOUBLE PRECISION
SH_MMR_WAGE_ZS None DOUBLE PRECISION
SH_PRG_ANEM None DOUBLE PRECISION
SH_PRG_ARTC_ZS None DOUBLE PRECISION
SH_PRG_SYPH_ZS None DOUBLE PRECISION
SH_PRV_SMOK_FE None DOUBLE PRECISION
SH_PRV_SMOK_MA None DOUBLE PRECISION
SH_STA_ACSN None DOUBLE PRECISION
SH_STA_ACSN_RU None DOUBLE PRECISION
SH_STA_ACSN_UR None DOUBLE PRECISION
SH_STA_ANV4_ZS None DOUBLE PRECISION
SH_STA_ANVC_ZS None DOUBLE PRECISION
SH_STA_ARIC_ZS None DOUBLE PRECISION
SH_STA_BFED_ZS None DOUBLE PRECISION
SH_STA_BRTC_ZS None DOUBLE PRECISION
SH_STA_BRTW_ZS None DOUBLE PRECISION
SH_STA_DIAB_ZS None DOUBLE PRECISION
SH_STA_IYCF_ZS None DOUBLE PRECISION
SH_STA_MALN_FE_ZS None DOUBLE PRECISION
SH_STA_MALN_MA_ZS None DOUBLE PRECISION
SH_STA_MALN_ZS None DOUBLE PRECISION
SH_STA_MALR None DOUBLE PRECISION
SH_STA_MMRT None DOUBLE PRECISION
SH_STA_MMRT_NE None DOUBLE PRECISION
SH_STA_ORCF_ZS None DOUBLE PRECISION
SH_STA_ORTH None DOUBLE PRECISION
SH_STA_OW15_FE_ZS None DOUBLE PRECISION
SH_STA_OW15_MA_ZS None DOUBLE PRECISION
SH_STA_OW15_ZS None DOUBLE PRECISION
SH_STA_OWGH_FE_ZS None DOUBLE PRECISION
SH_STA_OWGH_MA_ZS None DOUBLE PRECISION
SH_STA_OWGH_ZS None DOUBLE PRECISION
SH_STA_PNVC_ZS None DOUBLE PRECISION
SH_STA_STNT_FE_ZS None DOUBLE PRECISION
SH_STA_STNT_MA_ZS None DOUBLE PRECISION
SH_STA_STNT_ZS None DOUBLE PRECISION
SH_STA_WAST_FE_ZS None DOUBLE PRECISION
SH_STA_WAST_MA_ZS None DOUBLE PRECISION
SH_STA_WAST_ZS None DOUBLE PRECISION
SH_SVR_WAST_FE_ZS None DOUBLE PRECISION
SH_SVR_WAST_MA_ZS None DOUBLE PRECISION
SH_SVR_WAST_ZS None DOUBLE PRECISION
SH_TBS_CURE_ZS None DOUBLE PRECISION
SH_TBS_DTEC_ZS None DOUBLE PRECISION
SH_TBS_INCD None DOUBLE PRECISION
SH_TBS_MORT None DOUBLE PRECISION
SH_TBS_PREV None DOUBLE PRECISION
SH_VAC_TTNS_ZS None DOUBLE PRECISION
SH_XPD_EXTR_ZS None DOUBLE PRECISION
SH_XPD_OOPC_TO_ZS None DOUBLE PRECISION
SH_XPD_OOPC_ZS None DOUBLE PRECISION
SH_XPD_PCAP None DOUBLE PRECISION
SH_XPD_PCAP_PP_KD None DOUBLE PRECISION
SH_XPD_PRIV None DOUBLE PRECISION
SH_XPD_PRIV_ZS None DOUBLE PRECISION
SH_XPD_PUBL None DOUBLE PRECISION
SH_XPD_PUBL_GX_ZS None DOUBLE PRECISION
SH_XPD_PUBL_ZS None DOUBLE PRECISION
SH_XPD_TOTL_CD None DOUBLE PRECISION
SH_XPD_TOTL_ZS None DOUBLE PRECISION
SI_POV_NAHC None DOUBLE PRECISION
SI_POV_RUHC None DOUBLE PRECISION
SI_POV_URHC None DOUBLE PRECISION
SL_EMP_INSV_FE_ZS None DOUBLE PRECISION
SL_TLF_TOTL_FE_ZS None DOUBLE PRECISION
SL_TLF_TOTL_IN None DOUBLE PRECISION
SL_UEM_TOTL_FE_ZS None DOUBLE PRECISION
SL_UEM_TOTL_MA_ZS None DOUBLE PRECISION
SL_UEM_TOTL_ZS None DOUBLE PRECISION
SM_POP_NETM None DOUBLE PRECISION
SN_ITK_DEFC None DOUBLE PRECISION
SN_ITK_DEFC_ZS None DOUBLE PRECISION
SN_ITK_SALT_ZS None DOUBLE PRECISION
SN_ITK_VITA_ZS None DOUBLE PRECISION
SP_ADO_TFRT None DOUBLE PRECISION
SP_DYN_AMRT_FE None DOUBLE PRECISION
SP_DYN_AMRT_MA None DOUBLE PRECISION
SP_DYN_CBRT_IN None DOUBLE PRECISION
SP_DYN_CDRT_IN None DOUBLE PRECISION
SP_DYN_CONU_ZS None DOUBLE PRECISION
SP_DYN_IMRT_FE_IN None DOUBLE PRECISION
SP_DYN_IMRT_IN None DOUBLE PRECISION
SP_DYN_IMRT_MA_IN None DOUBLE PRECISION
SP_DYN_LE00_FE_IN None DOUBLE PRECISION
SP_DYN_LE00_IN None DOUBLE PRECISION
SP_DYN_LE00_MA_IN None DOUBLE PRECISION
SP_DYN_SMAM_FE None DOUBLE PRECISION
SP_DYN_SMAM_MA None DOUBLE PRECISION
SP_DYN_TFRT_IN None DOUBLE PRECISION
SP_DYN_TO65_FE_ZS None DOUBLE PRECISION
SP_DYN_TO65_MA_ZS None DOUBLE PRECISION
SP_DYN_WFRT None DOUBLE PRECISION
SP_HOU_FEMA_ZS None DOUBLE PRECISION
SP_MTR_1519_ZS None DOUBLE PRECISION
SP_POP_0004_FE None DOUBLE PRECISION
SP_POP_0004_FE_5Y None DOUBLE PRECISION
SP_POP_0004_MA None DOUBLE PRECISION
SP_POP_0004_MA_5Y None DOUBLE PRECISION
SP_POP_0014_FE_ZS None DOUBLE PRECISION
SP_POP_0014_MA_ZS None DOUBLE PRECISION
SP_POP_0014_TO None DOUBLE PRECISION
SP_POP_0014_TO_ZS None DOUBLE PRECISION
SP_POP_0509_FE None DOUBLE PRECISION
SP_POP_0509_FE_5Y None DOUBLE PRECISION
SP_POP_0509_MA None DOUBLE PRECISION
SP_POP_0509_MA_5Y None DOUBLE PRECISION
SP_POP_1014_FE None DOUBLE PRECISION
SP_POP_1014_FE_5Y None DOUBLE PRECISION
SP_POP_1014_MA None DOUBLE PRECISION
SP_POP_1014_MA_5Y None DOUBLE PRECISION
SP_POP_1519_FE None DOUBLE PRECISION
SP_POP_1519_FE_5Y None DOUBLE PRECISION
SP_POP_1519_MA None DOUBLE PRECISION
SP_POP_1519_MA_5Y None DOUBLE PRECISION
SP_POP_1564_FE_ZS None DOUBLE PRECISION
SP_POP_1564_MA_ZS None DOUBLE PRECISION
SP_POP_1564_TO None DOUBLE PRECISION
SP_POP_1564_TO_ZS None DOUBLE PRECISION
SP_POP_2024_FE None DOUBLE PRECISION
SP_POP_2024_FE_5Y None DOUBLE PRECISION
SP_POP_2024_MA None DOUBLE PRECISION
SP_POP_2024_MA_5Y None DOUBLE PRECISION
SP_POP_2529_FE None DOUBLE PRECISION
SP_POP_2529_FE_5Y None DOUBLE PRECISION
SP_POP_2529_MA None DOUBLE PRECISION
SP_POP_2529_MA_5Y None DOUBLE PRECISION
SP_POP_3034_FE None DOUBLE PRECISION
SP_POP_3034_FE_5Y None DOUBLE PRECISION
SP_POP_3034_MA None DOUBLE PRECISION
SP_POP_3034_MA_5Y None DOUBLE PRECISION
SP_POP_3539_FE None DOUBLE PRECISION
SP_POP_3539_FE_5Y None DOUBLE PRECISION
SP_POP_3539_MA None DOUBLE PRECISION
SP_POP_3539_MA_5Y None DOUBLE PRECISION
SP_POP_4044_FE None DOUBLE PRECISION
SP_POP_4044_FE_5Y None DOUBLE PRECISION
SP_POP_4044_MA None DOUBLE PRECISION
SP_POP_4044_MA_5Y None DOUBLE PRECISION
SP_POP_4549_FE None DOUBLE PRECISION
SP_POP_4549_FE_5Y None DOUBLE PRECISION
SP_POP_4549_MA None DOUBLE PRECISION
SP_POP_4549_MA_5Y None DOUBLE PRECISION
SP_POP_5054_FE None DOUBLE PRECISION
SP_POP_5054_FE_5Y None DOUBLE PRECISION
SP_POP_5054_MA None DOUBLE PRECISION
SP_POP_5054_MA_5Y None DOUBLE PRECISION
SP_POP_5559_FE None DOUBLE PRECISION
SP_POP_5559_FE_5Y None DOUBLE PRECISION
SP_POP_5559_MA None DOUBLE PRECISION
SP_POP_5559_MA_5Y None DOUBLE PRECISION
SP_POP_6064_FE None DOUBLE PRECISION
SP_POP_6064_FE_5Y None DOUBLE PRECISION
SP_POP_6064_MA None DOUBLE PRECISION
SP_POP_6064_MA_5Y None DOUBLE PRECISION
SP_POP_6569_FE None DOUBLE PRECISION
SP_POP_6569_FE_5Y None DOUBLE PRECISION
SP_POP_6569_MA None DOUBLE PRECISION
SP_POP_6569_MA_5Y None DOUBLE PRECISION
SP_POP_65UP_FE_ZS None DOUBLE PRECISION
SP_POP_65UP_MA_ZS None DOUBLE PRECISION
SP_POP_65UP_TO None DOUBLE PRECISION
SP_POP_65UP_TO_ZS None DOUBLE PRECISION
SP_POP_7074_FE None DOUBLE PRECISION
SP_POP_7074_FE_5Y None DOUBLE PRECISION
SP_POP_7074_MA None DOUBLE PRECISION
SP_POP_7074_MA_5Y None DOUBLE PRECISION
SP_POP_7579_FE None DOUBLE PRECISION
SP_POP_7579_FE_5Y None DOUBLE PRECISION
SP_POP_7579_MA None DOUBLE PRECISION
SP_POP_7579_MA_5Y None DOUBLE PRECISION
SP_POP_80UP_FE None DOUBLE PRECISION
SP_POP_80UP_FE_5Y None DOUBLE PRECISION
SP_POP_80UP_MA None DOUBLE PRECISION
SP_POP_80UP_MA_5Y None DOUBLE PRECISION
SP_POP_AG00_FE_IN None DOUBLE PRECISION
SP_POP_AG00_MA_IN None DOUBLE PRECISION
SP_POP_AG01_FE_IN None DOUBLE PRECISION
SP_POP_AG01_MA_IN None DOUBLE PRECISION
SP_POP_AG02_FE_IN None DOUBLE PRECISION
SP_POP_AG02_MA_IN None DOUBLE PRECISION
SP_POP_AG03_FE_IN None DOUBLE PRECISION
SP_POP_AG03_MA_IN None DOUBLE PRECISION
SP_POP_AG04_FE_IN None DOUBLE PRECISION
SP_POP_AG04_MA_IN None DOUBLE PRECISION
SP_POP_AG05_FE_IN None DOUBLE PRECISION
SP_POP_AG05_MA_IN None DOUBLE PRECISION
SP_POP_AG06_FE_IN None DOUBLE PRECISION
SP_POP_AG06_MA_IN None DOUBLE PRECISION
SP_POP_AG07_FE_IN None DOUBLE PRECISION
SP_POP_AG07_MA_IN None DOUBLE PRECISION
SP_POP_AG08_FE_IN None DOUBLE PRECISION
SP_POP_AG08_MA_IN None DOUBLE PRECISION
SP_POP_AG09_FE_IN None DOUBLE PRECISION
SP_POP_AG09_MA_IN None DOUBLE PRECISION
SP_POP_AG10_FE_IN None DOUBLE PRECISION
SP_POP_AG10_MA_IN None DOUBLE PRECISION
SP_POP_AG11_FE_IN None DOUBLE PRECISION
SP_POP_AG11_MA_IN None DOUBLE PRECISION
SP_POP_AG12_FE_IN None DOUBLE PRECISION
SP_POP_AG12_MA_IN None DOUBLE PRECISION
SP_POP_AG13_FE_IN None DOUBLE PRECISION
SP_POP_AG13_MA_IN None DOUBLE PRECISION
SP_POP_AG14_FE_IN None DOUBLE PRECISION
SP_POP_AG14_MA_IN None DOUBLE PRECISION
SP_POP_AG15_FE_IN None DOUBLE PRECISION
SP_POP_AG15_MA_IN None DOUBLE PRECISION
SP_POP_AG16_FE_IN None DOUBLE PRECISION
SP_POP_AG16_MA_IN None DOUBLE PRECISION
SP_POP_AG17_FE_IN None DOUBLE PRECISION
SP_POP_AG17_MA_IN None DOUBLE PRECISION
SP_POP_AG18_FE_IN None DOUBLE PRECISION
SP_POP_AG18_MA_IN None DOUBLE PRECISION
SP_POP_AG19_FE_IN None DOUBLE PRECISION
SP_POP_AG19_MA_IN None DOUBLE PRECISION
SP_POP_AG20_FE_IN None DOUBLE PRECISION
SP_POP_AG20_MA_IN None DOUBLE PRECISION
SP_POP_AG21_FE_IN None DOUBLE PRECISION
SP_POP_AG21_MA_IN None DOUBLE PRECISION
SP_POP_AG22_FE_IN None DOUBLE PRECISION
SP_POP_AG22_MA_IN None DOUBLE PRECISION
SP_POP_AG23_FE_IN None DOUBLE PRECISION
SP_POP_AG23_MA_IN None DOUBLE PRECISION
SP_POP_AG24_FE_IN None DOUBLE PRECISION
SP_POP_AG24_MA_IN None DOUBLE PRECISION
SP_POP_AG25_FE_IN None DOUBLE PRECISION
SP_POP_AG25_MA_IN None DOUBLE PRECISION
SP_POP_BRTH_MF None DOUBLE PRECISION
SP_POP_DPND None DOUBLE PRECISION
SP_POP_DPND_OL None DOUBLE PRECISION
SP_POP_DPND_YG None DOUBLE PRECISION
SP_POP_GROW None DOUBLE PRECISION
SP_POP_TOTL None DOUBLE PRECISION
SP_POP_TOTL_FE_IN None DOUBLE PRECISION
SP_POP_TOTL_FE_ZS None DOUBLE PRECISION
SP_POP_TOTL_MA_IN None DOUBLE PRECISION
SP_POP_TOTL_MA_ZS None DOUBLE PRECISION
SP_REG_BRTH_RU_ZS None DOUBLE PRECISION
SP_REG_BRTH_UR_ZS None DOUBLE PRECISION
SP_REG_BRTH_ZS None DOUBLE PRECISION
SP_REG_DTHS_ZS None DOUBLE PRECISION
SP_RUR_TOTL None DOUBLE PRECISION
SP_RUR_TOTL_ZG None DOUBLE PRECISION
SP_RUR_TOTL_ZS None DOUBLE PRECISION
SP_URB_GROW None DOUBLE PRECISION
SP_URB_TOTL None DOUBLE PRECISION
SP_URB_TOTL_IN_ZS None DOUBLE PRECISION
SP_UWT_TFRT None DOUBLE PRECISION
Record Count: 328
Metric Verbose Name Type
sum__SP_POP_TOTL None None
sum__SH_DYN_AIDS None None
sum__SP_RUR_TOTL_ZS None None
sum__SP_DYN_LE00_IN None None
sum__SP_RUR_TOTL None None
count COUNT(*) count
Record Count: 6
Table Name wb_health_population
Sql None
Enable Filter Select True
Fetch Values Predicate None
Database examples
Schema None
Description <!-- 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. --> This data was downloaded from the [World's Health Organization's website](https://datacatalog.worldbank.org/dataset/health-nutrition-and-population-statistics) Here's the script that was used to massage the data: DIR = "" df_country = pd.read_csv(DIR + '/HNP_Country.csv') df_country.columns = ['country_code'] + list(df_country.columns[1:]) df_country = df_country[['country_code', 'Region']] df_country.columns = ['country_code', 'region'] df = pd.read_csv(DIR + '/HNP_Data.csv') del df['Unnamed: 60'] df.columns = ['country_name', 'country_code'] + list(df.columns[2:]) ndf = df.merge(df_country, how='inner') dims = ('country_name', 'country_code', 'region') vv = [str(i) for i in range(1960, 2015)] mdf = pd.melt(ndf, id_vars=dims + ('Indicator Code',), value_vars=vv) mdf['year'] = mdf.variable + '-01-01' dims = dims + ('year',) pdf = mdf.pivot_table(values='value', columns='Indicator Code', index=dims) pdf = pdf.reset_index() pdf.to_csv(DIR + '/countries.csv') pdf.to_json(DIR + '/countries.json', orient='records') Here's the description of the metrics available: Series | Code Indicator Name --- | --- NY.GNP.PCAP.CD | GNI per capita, Atlas method (current US$) SE.ADT.1524.LT.FM.ZS | Literacy rate, youth (ages 15-24), gender parity index (GPI) SE.ADT.1524.LT.MA.ZS | Literacy rate, youth male (% of males ages 15-24) SE.ADT.1524.LT.ZS | Literacy rate, youth total (% of people ages 15-24) SE.ADT.LITR.FE.ZS | Literacy rate, adult female (% of females ages 15 and above) SE.ADT.LITR.MA.ZS | Literacy rate, adult male (% of males ages 15 and above) SE.ADT.LITR.ZS | Literacy rate, adult total (% of people ages 15 and above) SE.ENR.ORPH | Ratio of school attendance of orphans to school attendance of non-orphans ages 10-14 SE.PRM.CMPT.FE.ZS | Primary completion rate, female (% of relevant age group) SE.PRM.CMPT.MA.ZS | Primary completion rate, male (% of relevant age group) SE.PRM.CMPT.ZS | Primary completion rate, total (% of relevant age group) SE.PRM.ENRR | School enrollment, primary (% gross) SE.PRM.ENRR.FE | School enrollment, primary, female (% gross) SE.PRM.ENRR.MA | School enrollment, primary, male (% gross) SE.PRM.NENR | School enrollment, primary (% net) SE.PRM.NENR.FE | School enrollment, primary, female (% net) SE.PRM.NENR.MA | School enrollment, primary, male (% net) SE.SEC.ENRR | School enrollment, secondary (% gross) SE.SEC.ENRR.FE | School enrollment, secondary, female (% gross) SE.SEC.ENRR.MA | School enrollment, secondary, male (% gross) SE.SEC.NENR | School enrollment, secondary (% net) SE.SEC.NENR.FE | School enrollment, secondary, female (% net) SE.SEC.NENR.MA | School enrollment, secondary, male (% net) SE.TER.ENRR | School enrollment, tertiary (% gross) SE.TER.ENRR.FE | School enrollment, tertiary, female (% gross) SE.XPD.TOTL.GD.ZS | Government expenditure on education, total (% of GDP) SH.ANM.CHLD.ZS | Prevalence of anemia among children (% of children under 5) SH.ANM.NPRG.ZS | Prevalence of anemia among non-pregnant women (% of women ages 15-49) SH.CON.1524.FE.ZS | Condom use, population ages 15-24, female (% of females ages 15-24) SH.CON.1524.MA.ZS | Condom use, population ages 15-24, male (% of males ages 15-24) SH.CON.AIDS.FE.ZS | Condom use at last high-risk sex, adult female (% ages 15-49) SH.CON.AIDS.MA.ZS | Condom use at last high-risk sex, adult male (% ages 15-49) SH.DTH.COMM.ZS | Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total) SH.DTH.IMRT | Number of infant deaths SH.DTH.INJR.ZS | Cause of death, by injury (% of total) SH.DTH.MORT | Number of under-five deaths SH.DTH.NCOM.ZS | Cause of death, by non-communicable diseases (% of total) SH.DTH.NMRT | Number of neonatal deaths SH.DYN.AIDS | Adults (ages 15+) living with HIV SH.DYN.AIDS.DH | AIDS estimated deaths (UNAIDS estimates) SH.DYN.AIDS.FE.ZS | Women's share of population ages 15+ living with HIV (%) SH.DYN.AIDS.ZS | Prevalence of HIV, total (% of population ages 15-49) SH.DYN.MORT | Mortality rate, under-5 (per 1,000 live births) SH.DYN.MORT.FE | Mortality rate, under-5, female (per 1,000 live births) SH.DYN.MORT.MA | Mortality rate, under-5, male (per 1,000 live births) SH.DYN.NMRT | Mortality rate, neonatal (per 1,000 live births) SH.FPL.SATI.ZS | Met need for contraception (% of married women ages 15-49) SH.H2O.SAFE.RU.ZS | Improved water source, rural (% of rural population with access) SH.H2O.SAFE.UR.ZS | Improved water source, urban (% of urban population with access) SH.H2O.SAFE.ZS | Improved water source (% of population with access) SH.HIV.0014 | Children (0-14) living with HIV SH.HIV.1524.FE.ZS | Prevalence of HIV, female (% ages 15-24) SH.HIV.1524.KW.FE.ZS | Comprehensive correct knowledge of HIV/AIDS, ages 15-24, female (2 prevent ways and reject 3 misconceptions) SH.HIV.1524.KW.MA.ZS | Comprehensive correct knowledge of HIV/AIDS, ages 15-24, male (2 prevent ways and reject 3 misconceptions) SH.HIV.1524.MA.ZS | Prevalence of HIV, male (% ages 15-24) SH.HIV.ARTC.ZS | Antiretroviral therapy coverage (% of people living with HIV) SH.HIV.KNOW.FE.ZS | % of females ages 15-49 having comprehensive correct knowledge about HIV (2 prevent ways and reject 3 misconceptions) SH.HIV.KNOW.MA.ZS | % of males ages 15-49 having comprehensive correct knowledge about HIV (2 prevent ways and reject 3 misconceptions) SH.HIV.ORPH | Children orphaned by HIV/AIDS SH.HIV.TOTL | Adults (ages 15+) and children (0-14 years) living with HIV SH.IMM.HEPB | Immunization, HepB3 (% of one-year-old children) SH.IMM.HIB3 | Immunization, Hib3 (% of children ages 12-23 months) SH.IMM.IBCG | Immunization, BCG (% of one-year-old children) SH.IMM.IDPT | Immunization, DPT (% of children ages 12-23 months) SH.IMM.MEAS | Immunization, measles (% of children ages 12-23 months) SH.IMM.POL3 | Immunization, Pol3 (% of one-year-old children) SH.MED.BEDS.ZS | Hospital beds (per 1,000 people) SH.MED.CMHW.P3 | Community health workers (per 1,000 people) SH.MED.NUMW.P3 | Nurses and midwives (per 1,000 people) SH.MED.PHYS.ZS | Physicians (per 1,000 people) SH.MLR.NETS.ZS | Use of insecticide-treated bed nets (% of under-5 population) SH.MLR.PREG.ZS | Use of any antimalarial drug (% of pregnant women) SH.MLR.SPF2.ZS | Use of Intermittent Preventive Treatment of malaria, 2+ doses of SP/Fansidar (% of pregnant women) SH.MLR.TRET.ZS | Children with fever receiving antimalarial drugs (% of children under age 5 with fever) SH.MMR.DTHS | Number of maternal deaths SH.MMR.LEVE | Number of weeks of maternity leave SH.MMR.RISK | Lifetime risk of maternal death (1 in: rate varies by country) SH.MMR.RISK.ZS | Lifetime risk of maternal death (%) SH.MMR.WAGE.ZS | Maternal leave benefits (% of wages paid in covered period) SH.PRG.ANEM | Prevalence of anemia among pregnant women (%) SH.PRG.ARTC.ZS | Antiretroviral therapy coverage (% of pregnant women living with HIV) SH.PRG.SYPH.ZS | Prevalence of syphilis (% of women attending antenatal care) SH.PRV.SMOK.FE | Smoking prevalence, females (% of adults) SH.PRV.SMOK.MA | Smoking prevalence, males (% of adults) SH.STA.ACSN | Improved sanitation facilities (% of population with access) SH.STA.ACSN.RU | Improved sanitation facilities, rural (% of rural population with access) SH.STA.ACSN.UR | Improved sanitation facilities, urban (% of urban population with access) SH.STA.ANV4.ZS | Pregnant women receiving prenatal care of at least four visits (% of pregnant women) SH.STA.ANVC.ZS | Pregnant women receiving prenatal care (%) SH.STA.ARIC.ZS | ARI treatment (% of children under 5 taken to a health provider) SH.STA.BFED.ZS | Exclusive breastfeeding (% of children under 6 months) SH.STA.BRTC.ZS | Births attended by skilled health staff (% of total) SH.STA.BRTW.ZS | Low-birthweight babies (% of births) SH.STA.DIAB.ZS | Diabetes prevalence (% of population ages 20 to 79) SH.STA.IYCF.ZS | Infant and young child feeding practices, all 3 IYCF (% children ages 6-23 months) SH.STA.MALN.FE.ZS | Prevalence of underweight, weight for age, female (% of children under 5) SH.STA.MALN.MA.ZS | Prevalence of underweight, weight for age, male (% of children under 5) SH.STA.MALN.ZS | Prevalence of underweight, weight for age (% of children under 5) SH.STA.MALR | Malaria cases reported SH.STA.MMRT | Maternal mortality ratio (modeled estimate, per 100,000 live births) SH.STA.MMRT.NE | Maternal mortality ratio (national estimate, per 100,000 live births) SH.STA.ORCF.ZS | Diarrhea treatment (% of children under 5 receiving oral rehydration and continued feeding) SH.STA.ORTH | Diarrhea treatment (% of children under 5 who received ORS packet) SH.STA.OW15.FE.ZS | Prevalence of overweight, female (% of female adults) SH.STA.OW15.MA.ZS | Prevalence of overweight, male (% of male adults) SH.STA.OW15.ZS | Prevalence of overweight (% of adults) SH.STA.OWGH.FE.ZS | Prevalence of overweight, weight for height, female (% of children under 5) SH.STA.OWGH.MA.ZS | Prevalence of overweight, weight for height, male (% of children under 5) SH.STA.OWGH.ZS | Prevalence of overweight, weight for height (% of children under 5) SH.STA.PNVC.ZS | Postnatal care coverage (% mothers) SH.STA.STNT.FE.ZS | Prevalence of stunting, height for age, female (% of children under 5) SH.STA.STNT.MA.ZS | Prevalence of stunting, height for age, male (% of children under 5) SH.STA.STNT.ZS | Prevalence of stunting, height for age (% of children under 5) SH.STA.WAST.FE.ZS | Prevalence of wasting, weight for height, female (% of children under 5) SH.STA.WAST.MA.ZS | Prevalence of wasting, weight for height, male (% of children under 5) SH.STA.WAST.ZS | Prevalence of wasting, weight for height (% of children under 5) SH.SVR.WAST.FE.ZS | Prevalence of severe wasting, weight for height, female (% of children under 5) SH.SVR.WAST.MA.ZS | Prevalence of severe wasting, weight for height, male (% of children under 5) SH.SVR.WAST.ZS | Prevalence of severe wasting, weight for height (% of children under 5) SH.TBS.CURE.ZS | Tuberculosis treatment success rate (% of new cases) SH.TBS.DTEC.ZS | Tuberculosis case detection rate (%, all forms) SH.TBS.INCD | Incidence of tuberculosis (per 100,000 people) SH.TBS.MORT | Tuberculosis death rate (per 100,000 people) SH.TBS.PREV | Prevalence of tuberculosis (per 100,000 population) SH.VAC.TTNS.ZS | Newborns protected against tetanus (%) SH.XPD.EXTR.ZS | External resources for health (% of total expenditure on health) SH.XPD.OOPC.TO.ZS | Out-of-pocket health expenditure (% of total expenditure on health) SH.XPD.OOPC.ZS | Out-of-pocket health expenditure (% of private expenditure on health) SH.XPD.PCAP | Health expenditure per capita (current US$) SH.XPD.PCAP.PP.KD | Health expenditure per capita, PPP (constant 2011 international $) SH.XPD.PRIV | Health expenditure, private (% of total health expenditure) SH.XPD.PRIV.ZS | Health expenditure, private (% of GDP) SH.XPD.PUBL | Health expenditure, public (% of total health expenditure) SH.XPD.PUBL.GX.ZS | Health expenditure, public (% of government expenditure) SH.XPD.PUBL.ZS | Health expenditure, public (% of GDP) SH.XPD.TOTL.CD | Health expenditure, total (current US$) SH.XPD.TOTL.ZS | Health expenditure, total (% of GDP) SI.POV.NAHC | Poverty headcount ratio at national poverty lines (% of population) SI.POV.RUHC | Rural poverty headcount ratio at national poverty lines (% of rural population) SI.POV.URHC | Urban poverty headcount ratio at national poverty lines (% of urban population) SL.EMP.INSV.FE.ZS | Share of women in wage employment in the nonagricultural sector (% of total nonagricultural employment) SL.TLF.TOTL.FE.ZS | Labor force, female (% of total labor force) SL.TLF.TOTL.IN | Labor force, total SL.UEM.TOTL.FE.ZS | Unemployment, female (% of female labor force) (modeled ILO estimate) SL.UEM.TOTL.MA.ZS | Unemployment, male (% of male labor force) (modeled ILO estimate) SL.UEM.TOTL.ZS | Unemployment, total (% of total labor force) (modeled ILO estimate) SM.POP.NETM | Net migration SN.ITK.DEFC | Number of people who are undernourished SN.ITK.DEFC.ZS | Prevalence of undernourishment (% of population) SN.ITK.SALT.ZS | Consumption of iodized salt (% of households) SN.ITK.VITA.ZS | Vitamin A supplementation coverage rate (% of children ages 6-59 months) SP.ADO.TFRT | Adolescent fertility rate (births per 1,000 women ages 15-19) SP.DYN.AMRT.FE | Mortality rate, adult, female (per 1,000 female adults) SP.DYN.AMRT.MA | Mortality rate, adult, male (per 1,000 male adults) SP.DYN.CBRT.IN | Birth rate, crude (per 1,000 people) SP.DYN.CDRT.IN | Death rate, crude (per 1,000 people) SP.DYN.CONU.ZS | Contraceptive prevalence (% of women ages 15-49) SP.DYN.IMRT.FE.IN | Mortality rate, infant, female (per 1,000 live births) SP.DYN.IMRT.IN | Mortality rate, infant (per 1,000 live births) SP.DYN.IMRT.MA.IN | Mortality rate, infant, male (per 1,000 live births) SP.DYN.LE00.FE.IN | Life expectancy at birth, female (years) SP.DYN.LE00.IN | Life expectancy at birth, total (years) SP.DYN.LE00.MA.IN | Life expectancy at birth, male (years) SP.DYN.SMAM.FE | Mean age at first marriage, female SP.DYN.SMAM.MA | Mean age at first marriage, male SP.DYN.TFRT.IN | Fertility rate, total (births per woman) SP.DYN.TO65.FE.ZS | Survival to age 65, female (% of cohort) SP.DYN.TO65.MA.ZS | Survival to age 65, male (% of cohort) SP.DYN.WFRT | Wanted fertility rate (births per woman) SP.HOU.FEMA.ZS | Female headed households (% of households with a female head) SP.MTR.1519.ZS | Teenage mothers (% of women ages 15-19 who have had children or are currently pregnant) SP.POP.0004.FE | Population ages 0-4, female SP.POP.0004.FE.5Y | Population ages 0-4, female (% of female population) SP.POP.0004.MA | Population ages 0-4, male SP.POP.0004.MA.5Y | Population ages 0-4, male (% of male population) SP.POP.0014.FE.ZS | Population ages 0-14, female (% of total) SP.POP.0014.MA.ZS | Population ages 0-14, male (% of total) SP.POP.0014.TO | Population ages 0-14, total SP.POP.0014.TO.ZS | Population ages 0-14 (% of total) SP.POP.0509.FE | Population ages 5-9, female SP.POP.0509.FE.5Y | Population ages 5-9, female (% of female population) SP.POP.0509.MA | Population ages 5-9, male SP.POP.0509.MA.5Y | Population ages 5-9, male (% of male population) SP.POP.1014.FE | Population ages 10-14, female SP.POP.1014.FE.5Y | Population ages 10-14, female (% of female population) SP.POP.1014.MA | Population ages 10-14, male SP.POP.1014.MA.5Y | Population ages 10-14, male (% of male population) SP.POP.1519.FE | Population ages 15-19, female SP.POP.1519.FE.5Y | Population ages 15-19, female (% of female population) SP.POP.1519.MA | Population ages 15-19, male SP.POP.1519.MA.5Y | Population ages 15-19, male (% of male population) SP.POP.1564.FE.ZS | Population ages 15-64, female (% of total) SP.POP.1564.MA.ZS | Population ages 15-64, male (% of total) SP.POP.1564.TO | Population ages 15-64, total SP.POP.1564.TO.ZS | Population ages 15-64 (% of total) SP.POP.2024.FE | Population ages 20-24, female SP.POP.2024.FE.5Y | Population ages 20-24, female (% of female population) SP.POP.2024.MA | Population ages 20-24, male SP.POP.2024.MA.5Y | Population ages 20-24, male (% of male population) SP.POP.2529.FE | Population ages 25-29, female SP.POP.2529.FE.5Y | Population ages 25-29, female (% of female population) SP.POP.2529.MA | Population ages 25-29, male SP.POP.2529.MA.5Y | Population ages 25-29, male (% of male population) SP.POP.3034.FE | Population ages 30-34, female SP.POP.3034.FE.5Y | Population ages 30-34, female (% of female population) SP.POP.3034.MA | Population ages 30-34, male SP.POP.3034.MA.5Y | Population ages 30-34, male (% of male population) SP.POP.3539.FE | Population ages 35-39, female SP.POP.3539.FE.5Y | Population ages 35-39, female (% of female population) SP.POP.3539.MA | Population ages 35-39, male SP.POP.3539.MA.5Y | Population ages 35-39, male (% of male population) SP.POP.4044.FE | Population ages 40-44, female SP.POP.4044.FE.5Y | Population ages 40-44, female (% of female population) SP.POP.4044.MA | Population ages 40-44, male SP.POP.4044.MA.5Y | Population ages 40-44, male (% of male population) SP.POP.4549.FE | Population ages 45-49, female SP.POP.4549.FE.5Y | Population ages 45-49, female (% of female population) SP.POP.4549.MA | Population ages 45-49, male SP.POP.4549.MA.5Y | Population ages 45-49, male (% of male population) SP.POP.5054.FE | Population ages 50-54, female SP.POP.5054.FE.5Y | Population ages 50-54, female (% of female population) SP.POP.5054.MA | Population ages 50-54, male SP.POP.5054.MA.5Y | Population ages 50-54, male (% of male population) SP.POP.5559.FE | Population ages 55-59, female SP.POP.5559.FE.5Y | Population ages 55-59, female (% of female population) SP.POP.5559.MA | Population ages 55-59, male SP.POP.5559.MA.5Y | Population ages 55-59, male (% of male population) SP.POP.6064.FE | Population ages 60-64, female SP.POP.6064.FE.5Y | Population ages 60-64, female (% of female population) SP.POP.6064.MA | Population ages 60-64, male SP.POP.6064.MA.5Y | Population ages 60-64, male (% of male population) SP.POP.6569.FE | Population ages 65-69, female SP.POP.6569.FE.5Y | Population ages 65-69, female (% of female population) SP.POP.6569.MA | Population ages 65-69, male SP.POP.6569.MA.5Y | Population ages 65-69, male (% of male population) SP.POP.65UP.FE.ZS | Population ages 65 and above, female (% of total) SP.POP.65UP.MA.ZS | Population ages 65 and above, male (% of total) SP.POP.65UP.TO | Population ages 65 and above, total SP.POP.65UP.TO.ZS | Population ages 65 and above (% of total) SP.POP.7074.FE | Population ages 70-74, female SP.POP.7074.FE.5Y | Population ages 70-74, female (% of female population) SP.POP.7074.MA | Population ages 70-74, male SP.POP.7074.MA.5Y | Population ages 70-74, male (% of male population) SP.POP.7579.FE | Population ages 75-79, female SP.POP.7579.FE.5Y | Population ages 75-79, female (% of female population) SP.POP.7579.MA | Population ages 75-79, male SP.POP.7579.MA.5Y | Population ages 75-79, male (% of male population) SP.POP.80UP.FE | Population ages 80 and above, female SP.POP.80UP.FE.5Y | Population ages 80 and above, female (% of female population) SP.POP.80UP.MA | Population ages 80 and above, male SP.POP.80UP.MA.5Y | Population ages 80 and above, male (% of male population) SP.POP.AG00.FE.IN | Age population, age 0, female, interpolated SP.POP.AG00.MA.IN | Age population, age 0, male, interpolated SP.POP.AG01.FE.IN | Age population, age 01, female, interpolated SP.POP.AG01.MA.IN | Age population, age 01, male, interpolated SP.POP.AG02.FE.IN | Age population, age 02, female, interpolated SP.POP.AG02.MA.IN | Age population, age 02, male, interpolated SP.POP.AG03.FE.IN | Age population, age 03, female, interpolated SP.POP.AG03.MA.IN | Age population, age 03, male, interpolated SP.POP.AG04.FE.IN | Age population, age 04, female, interpolated SP.POP.AG04.MA.IN | Age population, age 04, male, interpolated SP.POP.AG05.FE.IN | Age population, age 05, female, interpolated SP.POP.AG05.MA.IN | Age population, age 05, male, interpolated SP.POP.AG06.FE.IN | Age population, age 06, female, interpolated SP.POP.AG06.MA.IN | Age population, age 06, male, interpolated SP.POP.AG07.FE.IN | Age population, age 07, female, interpolated SP.POP.AG07.MA.IN | Age population, age 07, male, interpolated SP.POP.AG08.FE.IN | Age population, age 08, female, interpolated SP.POP.AG08.MA.IN | Age population, age 08, male, interpolated SP.POP.AG09.FE.IN | Age population, age 09, female, interpolated SP.POP.AG09.MA.IN | Age population, age 09, male, interpolated SP.POP.AG10.FE.IN | Age population, age 10, female, interpolated SP.POP.AG10.MA.IN | Age population, age 10, male SP.POP.AG11.FE.IN | Age population, age 11, female, interpolated SP.POP.AG11.MA.IN | Age population, age 11, male SP.POP.AG12.FE.IN | Age population, age 12, female, interpolated SP.POP.AG12.MA.IN | Age population, age 12, male SP.POP.AG13.FE.IN | Age population, age 13, female, interpolated SP.POP.AG13.MA.IN | Age population, age 13, male SP.POP.AG14.FE.IN | Age population, age 14, female, interpolated SP.POP.AG14.MA.IN | Age population, age 14, male SP.POP.AG15.FE.IN | Age population, age 15, female, interpolated SP.POP.AG15.MA.IN | Age population, age 15, male, interpolated SP.POP.AG16.FE.IN | Age population, age 16, female, interpolated SP.POP.AG16.MA.IN | Age population, age 16, male, interpolated SP.POP.AG17.FE.IN | Age population, age 17, female, interpolated SP.POP.AG17.MA.IN | Age population, age 17, male, interpolated SP.POP.AG18.FE.IN | Age population, age 18, female, interpolated SP.POP.AG18.MA.IN | Age population, age 18, male, interpolated SP.POP.AG19.FE.IN | Age population, age 19, female, interpolated SP.POP.AG19.MA.IN | Age population, age 19, male, interpolated SP.POP.AG20.FE.IN | Age population, age 20, female, interpolated SP.POP.AG20.MA.IN | Age population, age 20, male, interpolated SP.POP.AG21.FE.IN | Age population, age 21, female, interpolated SP.POP.AG21.MA.IN | Age population, age 21, male, interpolated SP.POP.AG22.FE.IN | Age population, age 22, female, interpolated SP.POP.AG22.MA.IN | Age population, age 22, male, interpolated SP.POP.AG23.FE.IN | Age population, age 23, female, interpolated SP.POP.AG23.MA.IN | Age population, age 23, male, interpolated SP.POP.AG24.FE.IN | Age population, age 24, female, interpolated SP.POP.AG24.MA.IN | Age population, age 24, male, interpolated SP.POP.AG25.FE.IN | Age population, age 25, female, interpolated SP.POP.AG25.MA.IN | Age population, age 25, male, interpolated SP.POP.BRTH.MF | Sex ratio at birth (male births per female births) SP.POP.DPND | Age dependency ratio (% of working-age population) SP.POP.DPND.OL | Age dependency ratio, old (% of working-age population) SP.POP.DPND.YG | Age dependency ratio, young (% of working-age population) SP.POP.GROW | Population growth (annual %) SP.POP.TOTL | Population, total SP.POP.TOTL.FE.IN | Population, female SP.POP.TOTL.FE.ZS | Population, female (% of total) SP.POP.TOTL.MA.IN | Population, male SP.POP.TOTL.MA.ZS | Population, male (% of total) SP.REG.BRTH.RU.ZS | Completeness of birth registration, rural (%) SP.REG.BRTH.UR.ZS | Completeness of birth registration, urban (%) SP.REG.BRTH.ZS | Completeness of birth registration (%) SP.REG.DTHS.ZS | Completeness of death registration with cause-of-death information (%) SP.RUR.TOTL | Rural population SP.RUR.TOTL.ZG | Rural population growth (annual %) SP.RUR.TOTL.ZS | Rural population (% of total population) SP.URB.GROW | Urban population growth (annual %) SP.URB.TOTL | Urban population SP.URB.TOTL.IN.ZS | Urban population (% of total) SP.UWT.TFRT | Unmet need for contraception (% of married women ages 15-49)
Owners []
Main Datetime Column year
Default Endpoint None
Offset 0
Cache Timeout None
SQL Lab View False
Template parameters None
Perm [examples].[wb_health_population](id:2)
Associated Charts [Region Filter, World's Population, Most Populated Countries, Growth Rate, % Rural, Life Expectancy VS Rural %, Rural Breakdown, World's Pop Growth, Box plot, Treemap, Parallel Coordinates, World Map, Number of HIV+ people out of the total world population, Health Filter, World Map, Health Filter, filter box, SML_worldmap, Population Total, chitthal_Malaria cases reported, SML_worldmap_2, chitthal_Number of people who are undernourished, Number of people who are undernourished, Malaria cases reported, malaria case reported]