25 datasets found
  1. Wealthiest cities Philippines 2023, by asset value

    • statista.com
    Updated Aug 8, 2025
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    Statista (2025). Wealthiest cities Philippines 2023, by asset value [Dataset]. https://www.statista.com/statistics/1019020/wealthiest-cities-philippines-asset-value/
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    Dataset updated
    Aug 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Philippines
    Description

    In 2023, Quezon was the wealthiest city in the Philippines, with approximately 449 billion Philippine pesos worth of assets. Following by a large margin was Makati City. In that year, the province of Cebu was the wealthiest province in the country.

  2. P

    Philippines Population Density: NCR: City of Manila

    • ceicdata.com
    Updated Apr 15, 2018
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    CEICdata.com (2018). Philippines Population Density: NCR: City of Manila [Dataset]. https://www.ceicdata.com/en/philippines/population-and-population-density-census/population-density-ncr-city-of-manila
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    Dataset updated
    Apr 15, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1975 - Dec 1, 2015
    Area covered
    Philippines
    Variables measured
    Population
    Description

    Philippines Population Density: NCR: City of Manila data was reported at 71,263.000 Person/sq km in 2015. This records an increase from the previous number of 66,140.000 Person/sq km for 2010. Philippines Population Density: NCR: City of Manila data is updated yearly, averaging 65,706.000 Person/sq km from Dec 1975 (Median) to 2015, with 8 observations. The data reached an all-time high of 71,263.000 Person/sq km in 2015 and a record low of 59,164.640 Person/sq km in 1975. Philippines Population Density: NCR: City of Manila data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G005: Population Density.

  3. H

    Philippines - Open, validated health, climate, environment and socioeconomic...

    • data.humdata.org
    • data.amerigeoss.org
    csv
    Updated Apr 15, 2025
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    Thinking Machines Data Science (2025). Philippines - Open, validated health, climate, environment and socioeconomic data [Dataset]. https://data.humdata.org/dataset/project-cchain
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    csv(800364), csv(6729620), csv(750695), csv(3826558), csv(7026921), csv(1285254), csv(3708547), csv(12794497), csv(2661009), csv(96406), csv(276107164), csv(1438233), csv(243949312), csv(570037886), csv(327051), csv(776), csv(204709), csv(456724950), csv(92790), csv(2760), csv(3585969), csv(112257), csv(1110609), csv(268986130), csv(80360), csv(131488), csv(1027362), csv(146011), csv(5837932), csv(70190)Available download formats
    Dataset updated
    Apr 15, 2025
    Dataset provided by
    Thinking Machines Data Science
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Philippines
    Description

    The Project Climate Change, Health, and Artificial Intelligence (Project CCHAIN) dataset is a validated, open-sourced linked dataset containing 20 years (2003-2022) of climate, environmental, socioeconomic, and health dimensions at the barangay (village) level across twelve Philippine cities (Dagupan, Palayan, Navotas, Mandaluyong, Muntinlupa, Legazpi, Iloilo, Mandaue, Tacloban, Zamboanga, Cagayan de Oro, Davao).

    The full documentation can be accessed here.

    The tables are designed in a way that users can choose variables that are most relevant to their focus city and use case, and link these variables to form a single dataset by merging using standard geography codes and calendar dates. This can be done using the provided linking notebook, or offline using the user's own code.

    Here are some tips on how make most use of this dataset:

    • Focus on one location. Starting with a detailed analysis of one location allows for a better understanding of the local dynamics, which may differ across locations.

    • Choose one health data source. Pick one of either a central or local data source. Using two different data health sources is not advised because it will lead to double/overcounting of disease cases.

    • Do not use all variables at once- do a literature review first to identify possible key variables. to identify possible key variables. More often than not, using all variables is not necessary and may even yield subpar results.

    • Check data availability on your focus location and make sure they fit the requirements of your study.

    This dataset also includes household surveys tables (see schema here and here) done on partner informal settlement communities in the cities of Muntinlupa, Davao, Iloilo, and Mandaue and administered on various dates up to 2024. Due to the sensitive nature of surveys and the vulnerability of the subjects involved, requests for access must be submitted for review and approval by the Philippine Action for Community-Led Shelter Initiatives, Inc. (PACSII). To submit a request, please use this form.

  4. ELI – Empire East City Development – Philippines

    • store.globaldata.com
    Updated Jun 5, 2018
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    GlobalData UK Ltd. (2018). ELI – Empire East City Development – Philippines [Dataset]. https://store.globaldata.com/report/eli-empire-east-city-development-philippines/
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    Dataset updated
    Jun 5, 2018
    Dataset provided by
    GlobalDatahttps://www.globaldata.com/
    Authors
    GlobalData UK Ltd.
    License

    https://www.globaldata.com/privacy-policy/https://www.globaldata.com/privacy-policy/

    Time period covered
    2018 - 2022
    Area covered
    Asia-Pacific, Philippines
    Description

    Empire East Land Holdings Inc. (ELI), a subsidiary of Megaworld Corporation, is planning to undertake the construction of a mixed-use facility in the Philippines.The project involves the construction of a mixed-use facility on a 23ha area. It includes the construction of residential units, retail facilities, swimming pool, commercial facilities, parking facility and access roads, and the installation of elevators, safety and security systems. ELI is in the process of finalizing the master plan. Read More

  5. i

    National Demographic and Health Survey 2022 - Philippines

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Jun 7, 2023
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    Philippine Statistics Authority (PSA) (2023). National Demographic and Health Survey 2022 - Philippines [Dataset]. https://catalog.ihsn.org/catalog/11340
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    Dataset updated
    Jun 7, 2023
    Dataset authored and provided by
    Philippine Statistics Authority (PSA)
    Time period covered
    2022
    Area covered
    Philippines
    Description

    Abstract

    The 2022 Philippines National Demographic and Health Survey (NDHS) was implemented by the Philippine Statistics Authority (PSA). Data collection took place from May 2 to June 22, 2022.

    The primary objective of the 2022 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, fertility preferences, family planning practices, childhood mortality, maternal and child health, nutrition, knowledge and attitudes regarding HIV/AIDS, violence against women, child discipline, early childhood development, and other health issues.

    The information collected through the NDHS is intended to assist policymakers and program managers in designing and evaluating programs and strategies for improving the health of the country’s population. The 2022 NDHS also provides indicators anchored to the attainment of the Sustainable Development Goals (SDGs) and the new Philippine Development Plan for 2023 to 2028.

    Geographic coverage

    National coverage

    Analysis unit

    • Household
    • Individual
    • Children age 0-5
    • Woman age 15-49

    Universe

    The survey covered all de jure household members (usual residents), all women aged 15-49, and all children aged 0-4 resident in the household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling scheme provides data representative of the country as a whole, for urban and rural areas separately, and for each of the country’s administrative regions. The sample selection methodology for the 2022 NDHS was based on a two-stage stratified sample design using the Master Sample Frame (MSF) designed and compiled by the PSA. The MSF was constructed based on the listing of households from the 2010 Census of Population and Housing and updated based on the listing of households from the 2015 Census of Population. The first stage involved a systematic selection of 1,247 primary sampling units (PSUs) distributed by province or HUC. A PSU can be a barangay, a portion of a large barangay, or two or more adjacent small barangays.

    In the second stage, an equal take of either 22 or 29 sample housing units were selected from each sampled PSU using systematic random sampling. In situations where a housing unit contained one to three households, all households were interviewed. In the rare situation where a housing unit contained more than three households, no more than three households were interviewed. The survey interviewers were instructed to interview only the preselected housing units. No replacements and no changes of the preselected housing units were allowed in the implementing stage in order to prevent bias. Survey weights were calculated, added to the data file, and applied so that weighted results are representative estimates of indicators at the regional and national levels.

    All women age 15–49 who were either usual residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Among women eligible for an individual interview, one woman per household was selected for a module on women’s safety.

    For further details on sample design, see APPENDIX A of the final report.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    Two questionnaires were used for the 2022 NDHS: the Household Questionnaire and the Woman’s Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to the Philippines. Input was solicited from various stakeholders representing government agencies, academe, and international agencies. The survey protocol was reviewed by the ICF Institutional Review Board.

    After all questionnaires were finalized in English, they were translated into six major languages: Tagalog, Cebuano, Ilocano, Bikol, Hiligaynon, and Waray. The Household and Woman’s Questionnaires were programmed into tablet computers to allow for computer-assisted personal interviewing (CAPI) for data collection purposes, with the capability to choose any of the languages for each questionnaire.

    Cleaning operations

    Processing the 2022 NDHS data began almost as soon as fieldwork started, and data security procedures were in place in accordance with confidentiality of information as provided by Philippine laws. As data collection was completed in each PSU or cluster, all electronic data files were transferred securely via SyncCloud to a server maintained by the PSA Central Office in Quezon City. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors while still in the area of assignment. Timely generation of field check tables allowed for effective monitoring of fieldwork, including tracking questionnaire completion rates. Only the field teams, project managers, and NDHS supervisors in the provincial, regional, and central offices were given access to the CAPI system and the SyncCloud server.

    A team of secondary editors in the PSA Central Office carried out secondary editing, which involved resolving inconsistencies and recoding “other” responses; the former was conducted during data collection, and the latter was conducted following the completion of the fieldwork. Data editing was performed using the CSPro software package. The secondary editing of the data was completed in August 2022. The final cleaning of the data set was carried out by data processing specialists from The DHS Program in September 2022.

    Response rate

    A total of 35,470 households were selected for the 2022 NDHS sample, of which 30,621 were found to be occupied. Of the occupied households, 30,372 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 28,379 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 27,821 women, yielding a response rate of 98%.

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and in data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2022 Philippines National Demographic and Health Survey (2022 NDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

    Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2022 NDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

    A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

    If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2022 NDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

    A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

    Data appraisal

    Data Quality Tables

    • Household age distribution
    • Age distribution of eligible and interviewed women
    • Age displacement at age 14/15
    • Age displacement at age 49/50
    • Pregnancy outcomes by years preceding the survey
    • Completeness of reporting
    • Observation of handwashing facility
    • School attendance by single year of age
    • Vaccination cards photographed
    • Population pyramid
    • Five-year mortality rates

    See details of the data quality tables in Appendix C of the final report.

  6. g

    Archival Version

    • datasearch.gesis.org
    Updated Aug 5, 2015
    + more versions
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    Averch, H. A.; Koehler, J.E.; Denton, F.H. (2015). Archival Version [Dataset]. http://doi.org/10.3886/ICPSR05901
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    Dataset updated
    Aug 5, 2015
    Dataset provided by
    da|ra (Registration agency for social science and economic data)
    Authors
    Averch, H. A.; Koehler, J.E.; Denton, F.H.
    Area covered
    Philippines
    Description

    This data collection contains information for the following ten major topic areas. PART 1. Survey (Pegasus) File. 182 variables for 1,550 respondents in 1969. Variables cover attitudes toward Philippine government, social, economic, and political conditions, attitudes toward and knowledge of dissidents and exposure to crime and violence. Sample was stratified by language and restricted to those between the ages of 21 and 65. PART 2. General Province Data. This file contains the data used in the factor analyses reported in Chapter II of The Matrix of Policy in the Philippines. Because the data are drawn from so many different sources, the descriptions contain notes on origins. 110 variables for 49 provinces on general socioeconomic, political, cultural, and agricultural variables for various years, 1918-1968 are included. PART 3. Province Election Data. This file contains 157 variables for 49 provinces on voting in elections since 1948 and corresponding population characteristics. Data on elections are from the relevant Commission on Elections (COMELEC) reports, population and agricultural data are from the censuses, income and labor force data are from the Philippine Statistical Survey of Households, municipal expenditures are taken from reports of the Auditor General. PART 4. City Voting Data. This file contains data on voting in 36 Philippine chartered cities. The data sources are the same as those for the Province Election file with the addition of estimates of population by mother tongue calculated from the 0.5 percent sample of the 1960 Census. There are 153 variables on election returns since 1953, some socioeconomic data for 1960 and government revenue, aid, and appropriations for 1961-68. PART 5. Municipio Data. This file contains data used in analysis of Huk control in 57 municipios. The data on 84 variables are drawn from Philippine Constabulary intelligence reports, COMELEC election results, and census data. PART 6. Barrio Data. This file contains data for 24 variables on 302 barrios in central Luzon, including all of the barrios reported by the Philippine Constabulary (PC) as controlled and a random sample of the rest. The data are drawn from PC intelligence reports, censuses, and maps. PART 7. City Socioeconomic Data. This file contains 37 variables relating to 1967-1968 for 51 Philippine chartered cities on socioeconomic indicators and crime statistics. PART 8. Province Crime Data. This file contains 55 variables on crime rates and socioeconomic data for 48 provinces. Manila is omitted. Data are for 1962-67. PART 9. Province Economic Data. This file contains data taken from the economic censuses of 1948 and 1961. In most cases detail is given for provinces, where disclosure considerations prevented such detail, regions are the geographical unit. There are some 37 variables measuring attributes of various industries. PART 10. Province Manufacturing Data. This file contains data by province (49) from various rounds of the survey of manufacturers. In this case, the sample universe is large establishments as defined for survey purposes. There are 11 variables measuring aspects of major businesses in 1956, 1958-60, and 1962.

  7. i

    Census of Population 2015 - Philippines

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    Updated Oct 10, 2017
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    Philippine Statistics Authority (2017). Census of Population 2015 - Philippines [Dataset]. https://datacatalog.ihsn.org/catalog/7186
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    Dataset updated
    Oct 10, 2017
    Dataset authored and provided by
    Philippine Statistics Authority
    Time period covered
    2015
    Area covered
    Philippines
    Description

    Abstract

    Philippines Population Census 2015 was designed to take an inventory of the total population in the country and collect information about its characteristics. The census of population is the source of information on the size, distribution, and composition of the population in each barangay, city/municipality, province, and region in the country, as well as information about its demographic, social, and economic characteristics. These indicators are vital in the formulation of rational plans and programs towards national and local development.

    Specifically, POPCEN 2015 gathered data on: - size and geographic distribution of the population; - population composition in terms of age, sex, and marital status; - religious affiliation; - school attendance, literacy, highest grade/year completed, and technical/vocational course obtained; - usual activity/occupation, and whether overseas worker for members 15 years old and over; - registration of birth and death; - household-level characteristics such as fuel used for lighting and source of water supply for drinking and cooking; - housing characteristics such as the type of building, construction materials of the roof of the building, construction materials of the outer walls of the building/housing unit, and tenure status of the housing unit/lot; and - barangay characteristics such as the presence of selected facilities and establishments; and presence of informal settlers, relocation areas, and in-movers in the barangay due to natural and man-made disasters.

    August 1, 2015 was designated as Census Day for the POPCEN 2015, on which date the enumeration of the population in the Philippines was referred. For the purpose of this census, all information collected about the population were as of 12:01 a.m., Saturday, August 1, 2015.

    Enumeration lasted for about 25 days, from 10 August to 6 September 2015. In some areas, enumeration was extended until 15 September 2015 for large provinces.

    Geographic coverage

    The population count is available at the barangay, city/municipal, provincial, regional, and national levels. Demographic, social, and economic characteristics are tabulated at the city/municipal, provincial, regional, and national levels.

    Analysis unit

    The following are the units of analysis in POPCEN 2015: 1. Individual person 2. Household 3. Housing unit 4. Institutional Population 5. Barangay

    Universe

    The POPCEN 2015 covered all persons who were alive as of 12:01 a.m. August 1, 2015, and who were members of the household and institution as follows:

    Persons Enumerated as Members of the Household:

    1. Those who were present at the time of visit and whose usual place of residence was the housing unit where the household lived;

    2. Family members who were overseas workers and who were away at the time of the census and were expected to be back within five years from the date of last departure. These included household members who may or may not have had a specific work contract or had been presently at home on vacation but had an existing overseas employment to return to. Undocumented overseas workers were still considered as members of the household for as long as they had been away for not more than five years. Immigrants, however, were excluded from the census.

    3. Those whose usual place of residence was the place where the household lived but were temporarily away at the time of the census for any of the following reasons: a. on vacation, business/pleasure trip, or training somewhere in the Philippines and was expected to be back within six months from the date of departure. An example was a person on training with the Armed Forces of the Philippines for not more than six months; b. on vacation, business/pleasure trip, on study/training abroad and was expected to be back within a year from the date of departure; c. working or attending school outside their usual place of residence but usually came home at least once a week; d. confined in hospitals for a period of not more than six months as of the time of enumeration, except when they were confined as patients in mental hospitals, leprosaria/leper colonies or drug rehabilitation centers, regardless of the duration of their confinement; e. detained in national/provincial/city/municipal jails or in military camps for a period of not more than six months as of the time of enumeration, except when their sentence or detentionwas expected to exceed six months; f. on board coastal, interisland, or fishing vessels within Philippine territories; and g. on board oceangoing vessels but expected to be back within five years from the date of departure.

    4. Boarders/lodgers of the household or employees of household-operated businesses who did not return/go home to their respective households weekly;

    5. Citizens of foreign countries who resided or were expected to reside in the Philippines for at least a year from their arrival, except members of diplomatic missions and non-Filipino members of international organizations;

    6. Filipino balikbayans with usual place of residence in a foreign country but resided or were expected to reside in the Philippines for at least a year from their arrival; and

    7. Persons temporarily staying with the household who had no usual place of residence or who were not certain to be enumerated elsewhere.

    Persons Enumerated as Members of the Institutional Population:

    1. Permanent lodgers in boarding houses;

    2. Dormitory residents who did not usually go home to their respective households at least once a week;

    3. Hotel residents who stayed in the hotel for more than six months at the time of the census;

    4. Boarders in residential houses, provided that their number was 10 or more. However, if the number of boarders in a house was less than 10, they were considered as members of regular households, not of institutions;

    5. Patients in hospitals who were confined for more than six months;

    6. Patients confined in mental hospitals, leprosaria or leper colonies, and drug rehabilitation centers, regardless of the length of their confinement;

    7. Wards in orphanages, homes for the aged, and other welfare institutions;

    8. Prisoners of corrective and penal institutions;

    9. Seminarians, nuns in convents, monks, and postulants;

    10. Soldiers residing in military camps; and

    11. Workers in mining and similar camps.

    All Filipinos in Philippine embassies, missions, and consulates abroad were also included in the enumeration.

    Kind of data

    Census/enumeration data [cen]

    Sampling procedure

    The POPCEN 2015 is a complete enumeration of all persons, households and institutional population in the country. No sampling was done.

    Mode of data collection

    Face-to-face interview [f2f] and self-administered; Paper and Pencil

    Research instrument

    Listed below are the basic census forms that were used during the field enumeration:

    • CP Form 1 - Listing Booklet This booklet was used to list the buildings, housing units, households, and ILQs within an EA. It was also used to record other information such as the address of the household head or ILQ, total population, and number of males and females corresponding to each household and ILQ listed.

    • CP Form 2 - Household Questionnaire This four-page questionnaire was used to record information about the households. Specifically, this form was used to gather information on selected demographic and socio-economic characteristics of the population and some information on housing characteristics.

    • CP Form 4 - Institutional Population Questionnaire This four-page questionnaire was used to record information on selected demographic and socio-economic characteristics of the population residing in ILQs.

    • CP Form 5 - Barangay Schedule This four-page questionnaire was used to record the physical characteristics (e.g. street pattern) and the presence of service facilities and establishments by kind and emplyment size in the barangay. It was also used to record the presence of informal settlers, relocation areas, and in-movers in the barangay due to natural and man-made disasters.

    • CP Form 7 - Household Self-Administered Questionnaire Instructions This form contains specific and detailed instructions on how to fill out/accomplish each item in CP Form 2. It was used as guide/reference by respondents who were not, for some reasons, personally interviewed by the EN.

    • CP Form 8 - Institutional Population Self-Administered Questionnaire Instructions This form contains specific and detailed instructions for the managers/administrators to guide them in accomplishing each item in CP Form 4. It was used as guide/reference by managers or administrators of an ILQ.

    Listed below are the major administrative and accomplishment forms that were also used to facilitate data collection and supervision, and monitoring of enumeration and personnel:

    • Mapping Form This form was used to plot buildings, either occupied by households or vacant, ILQs and important physical landmarks in the area. It was also used to enlarge a map or a block of an EA/barangay if the area being enumerated is too large or congested. CP Form 1 - Listing Booklet

    • CP Form 6 - Notice of Listing/Enumeration This form is a sticker. After listing and interviewing a household or ILQ, this sticker was posted in a very conspicuous place, preferably in front of the house or at the gate of the building. This form was used for control and monitoring purposes as its presence indicates that a particular housing unit or ILQ had already been listed/interviewed.

    • CP Form 9 - Appointment Slip to the Household/Institution/Barangay Official This form was used to set an appointment with the

  8. CCC – N Bacalso Avenue Cebu City Medical Center – Philippines

    • store.globaldata.com
    Updated Oct 25, 2017
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    GlobalData UK Ltd. (2017). CCC – N Bacalso Avenue Cebu City Medical Center – Philippines [Dataset]. https://store.globaldata.com/report/ccc-n-bacalso-avenue-cebu-city-medical-center-philippines-2/
    Explore at:
    Dataset updated
    Oct 25, 2017
    Dataset provided by
    GlobalDatahttps://www.globaldata.com/
    Authors
    GlobalData UK Ltd.
    License

    https://www.globaldata.com/privacy-policy/https://www.globaldata.com/privacy-policy/

    Time period covered
    2017 - 2021
    Area covered
    Cebu City, Natalio B. Bacalso Avenue, Philippines, Asia-Pacific
    Description

    Cebu City Council (CCC) is undertaking the construction of a hospital at the former Cebu city medical center (CCMC) in Cebu, the Philippines.The project involves the construction of a 10-story, 1,000-bed hospital on 1.5ha of land. The project is being developed in phases.It includes the construction of rooms, operating theaters, out-patient wards, in-patient wards, a pharmacy, a cafeteria, emergency department and parking facilities, and the installation of related medical equipment, safety and security systems.In February 2014, demolition works were completed.As of June 2015, six contractors have submitted their letter of intent to the Special Bids and Awards Committee (BAC) for the CCMC. The contractors are CE Padilla Construction, Dakay Construction, WTG Construction and Development Corp. in a joint venture with A.M. Oreta Construction, EM Cuerpo Inc, SCDI-MCEI joint venture and BF Corp. in a joint venture with Philab Industries Inc. BAC will open the bid documents submitted by the contractors on June 18, 2015.In July 2015, Cebu City’s Bids and Awards Committee (BAC) awarded the contract to C.E. Padilla Construction Incorporated for the first phase of the project. On July 4, 2015, groundbreaking ceremony of the “People’s Hospital” was held and commenced construction works.As of February 2017, constructions works on the first phase are 50% completed.Construction of the first phase will be completed by the first quarter of 2018.Cebu City Medical Center is expected to complete by the end of 2018. Read More

  9. Salinity and temperature record from the harbour of Cebu City, Philippines

    • doi.pangaea.de
    • search.dataone.org
    html, tsv
    Updated May 26, 1999
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    Jürgen Pätzold (1999). Salinity and temperature record from the harbour of Cebu City, Philippines [Dataset]. http://doi.org/10.1594/PANGAEA.55285
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    html, tsvAvailable download formats
    Dataset updated
    May 26, 1999
    Dataset provided by
    PANGAEA
    Authors
    Jürgen Pätzold
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Time period covered
    Jul 27, 1977 - Sep 30, 1978
    Area covered
    Variables measured
    Salinity, DATE/TIME, DEPTH, water, Temperature, water
    Description

    This dataset is about: Salinity and temperature record from the harbour of Cebu City, Philippines. Please consult parent dataset @ https://doi.org/10.1594/PANGAEA.873030 for more information.

  10. A Community-Based Validation Study of the Short-Form 36 Version 2...

    • plos.figshare.com
    docx
    Updated Jun 1, 2023
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    Nina T. Castillo-Carandang; Olivia T. Sison; Mary Lenore Grefal; Rody G. Sy; Oliver C. Alix; Elmer Jasper B. Llanes; Paul Ferdinand M. Reganit; Allan Wilbert G. Gumatay; Felix Eduardo R. Punzalan; Felicidad V. Velandria; E. Shyong Tai; Hwee-Lin Wee (2023). A Community-Based Validation Study of the Short-Form 36 Version 2 Philippines (Tagalog) in Two Cities in the Philippines [Dataset]. http://doi.org/10.1371/journal.pone.0083794
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Nina T. Castillo-Carandang; Olivia T. Sison; Mary Lenore Grefal; Rody G. Sy; Oliver C. Alix; Elmer Jasper B. Llanes; Paul Ferdinand M. Reganit; Allan Wilbert G. Gumatay; Felix Eduardo R. Punzalan; Felicidad V. Velandria; E. Shyong Tai; Hwee-Lin Wee
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Philippines
    Description

    ObjectiveTo evaluate the validity and reliability of the Philippines (Tagalog) Short Form 36 Health Survey version 2 (SF-36v2®) standard questionnaire among Filipinos residing in two cities. Study Design and SettingThe official Philippines (Tagalog) SF-36v2 standard (4-week recall) version was pretested on 30 participants followed by formal and informal cognitive debriefing. To obtain the feedback on translation by bilingual respondents, each SF-36v2 question was stated first in English followed by Tagalog. No revisions to the original questionnaire were needed except that participants thought it was appropriate to incorporate "po" in the instructions to make it more polite. Face-to-face interviews of 562 participants aged 20-50 years living in two barangays (villages) in the highly urbanized city of Makati City (Metro Manila) and in urban and rural barangays in Tanauan City (province of Batangas) were subsequently conducted. Content validity, item level validity, reliability and factor structure of the SF-36v2 (Tagalog) were examined. ResultsContent validity of the SF-36v2 was assessed to be adequate for assessing health status among Filipinos. Item means of Philippines (Tagalog) SF-36v2 were similar with comparable scales in the US English, Singapore (English and Chinese) and Thai SF-36 version 1. Item-scale correlation exceeded 0.4 for all items except the bathing item in PF (correlation: 0.31). In exploratory factor analysis, the US two-component model was supported. However, in confirmatory factor analysis, the Japanese three-component model fit the Tagalog data better than the US two-component model. ConclusionsThe Philippines (Tagalog) SF-36v2 is a valid and reliable instrument for measuring health status among residents of Makati City (Metro Manila) and Tanauan City (Province of Batangas).

  11. Countries with the most Facebook users 2025

    • statista.com
    Updated Jun 19, 2025
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    Statista (2025). Countries with the most Facebook users 2025 [Dataset]. https://www.statista.com/statistics/268136/top-15-countries-based-on-number-of-facebook-users/
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    Dataset updated
    Jun 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2025
    Area covered
    Worldwide
    Description

    Which county has the most Facebook users? There are more than 383 million Facebook users in India alone, making it the leading country in terms of Facebook audience size. To put this into context, if India’s Facebook audience were a country, then it would be ranked third in terms of largest population worldwide. Apart from India, there are several other markets with more than 100 million Facebook users each: The United States, Indonesia, and Brazil with 196.9 million, 122.3 million, and 111.65 million Facebook users respectively. Facebook – the most used social media Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3.5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising. Facebook usage by device As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.

  12. i

    Census of Population and Housing 2010 - Philippines

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    Updated Oct 10, 2017
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    National Statistics Office (2017). Census of Population and Housing 2010 - Philippines [Dataset]. https://datacatalog.ihsn.org/catalog/7171
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    Dataset updated
    Oct 10, 2017
    Dataset authored and provided by
    National Statistics Office
    Time period covered
    2010
    Area covered
    Philippines
    Description

    Abstract

    Census of Population and Housing (CPH) refers to the entire process of collecting, compiling, evaluating, analyzing, publishing, and disseminating data about the population and the living quarters in a country. It entails the listing and recording of the characteristics of each individual and each living quarter as of a specified time and within a specified territory. In other words, the CPH offers a “snapshot” of the entire population on a specific date, that is, how many people reside within the national borders, who they are, and where they live during such specified date. Also, included are the characteristics of the housing units where they reside.

    The 2010 CPH is designed to take an inventory of the total population and housing units in the Philippines and collect information about their characteristics. The census of population is the source of information on the size and distribution of the population, as well as their demographic, social, economic, and cultural characteristics. The census of housing, on the other hand, provides information on the stock of housing units and their structural characteristics and facilities which have bearing on the maintenance of privacy and health, and the development of normal family living conditions. These information are vital for making rational plans and programs for local and national development.

    Specifically, the 2010 CPH aims to: - obtain comprehensive data on the size, composition, and distribution of the population of the Philippines; - gather data on birth registration, literacy, school attendance, place of school, highest grade/year completed, residence 5 years ago, overseas worker, usual occupation, kind of business or industry, class of worker, place of work, fertility, religion, citizenship, ethnic group, disability, and functional difficulty, and determine their geographic distribution; - take stock of the housing units existing in the country and to get information about their geographic location, structural characteristics, and facilities, among others; - obtain information on the characteristics of the barangay, which will be used as basis for urban-rural classification; and - serve as sampling frame for use in household-based surveys.

    Data collected in this census were compiled, evaluated, analyzed, published, and disseminated for the use of government, business, industry, social scientists, other research and academic institutions, and the general public. Among the important uses of census data are the following:

    In government: - redistricting and apportionment of congressional seats; - allocation of resources and revenues; - creation of political and administrative units; - formulation of policies concerning population and housing; and - formulation of programs relative to the delivery of basic services for health, education, housing, and others

    In business and industry: - determination of sites for establishing businesses; - determination of consumer demands for various goods and services; and - determination of supply of labor for the production of goods and services

    In research and academic institutions: - conduct of researches on population and other disciplines; and - study of population growth and distribution as basis in preparing projections

    Geographic coverage

    National coverage Regions Provinces Cities and Municipalities Barangays

    Analysis unit

    household questionnaire: individuals (household members), households, housing units institutional questionnaire: individuals (institutional population), institutional living quarters barangay questionnaire: barangay

    Universe

    Census-taking in the Philippines follows a de-jure concept wherein a person is counted in the usual place of residence or the place where the person usually resides. Information on the count of the population and living quarters were collected with 12:01 a.m. of May 1, 2010 as the census reference time and date.

    The following individuals were enumerated:

    • Those who were present at the time of visit and whose usual place of residence is the housing unit where the household lives.

    • Those whose usual place of residence is the place where the household lives but are temporarily away at the time of the census.

    • Boarders/lodgers of the household or employees of household-operated businesses who do not usually return/go to their respective homes weekly.

    • Overseas workers and who have been away at the time of the census for not more than five years from the date of departure and are expected to be back within five years from the date of last departure.

    • Filipino "balikbayans" with usual place of residence in a foreign country but have resided or are expected to reside in the Philippines for at least a year from their arrival.

    • Citizens of foreign countries who have resided or are expected to reside in the Philippines for at least a year from their arrival, except members of diplomatic missions and non-Filipino members of international organizations.

    • Persons temporarily staying with the household who have no usual place of residence or who are not certain to be enumerated elsewhere.

    Kind of data

    Census/enumeration data [cen]

    Sampling procedure

    In the 2010 CPH, there are basically two types of questionnaires used for the enumeration of household members. These are CPH Form 2 or the Common Household Questionnaire and CPH Form 3 or the Sample Household Questionnaire. CPH Form 3 contains more questions than CPH Form 2.

    The 2010 CPH was carried out through a combination of complete enumeration and sampling. For this census, systematic cluster sampling was adopted. This sampling method is designed in such a way that efficient and accurate estimates will be obtained at the city/municipality level.

    The sampling rate or the proportion of households to be selected as samples depends on the size of the city/municipality where the Enumeration Area (EA) is located. For the cities/municipalities with estimated number of households of 500 and below, 100 percent sampling rate was used. While for those cities/municipalities with estimated number of households of 501 and above, a sampling rate of 20 percent was implemented.

    In this sampling scheme, each city/municipality was treated as a domain. For city/municipality with 100 percent sampling rate, all households in all the EAs within this city/municipality were selected as samples. For those with a 20 percent sampling rate, systematic cluster sampling was adopted. That is, sample selection of one in five clusters with the first cluster selected at random. Thus in effect, the EAs belonging to the city/municipality with 20 percent sampling rate are divided into clusters of size 5. Random start is pre-determined for each EA.

    If the sampling rate applied to a city/municipality is 100 percent, it means that all households in that municipality were administered with CPH Form 3. If it is 20 percent, it means that 20 percent of all households used CPH Form 3 while 80 percent used CPH Form 2.

    The random start used by EA is a number from 1 to 5 which was used to select the cluster where the first sample households in an EA, and subsequently the other sample households, were included.

    Clusters are formed by grouping together households that have been assigned consecutive serial numbers as they were listed in the Listing Booklet. For a 20 percent sampling rate, clusters were formed by grouping together five households.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    CPH Form 1 - Listing Booklet This form is a booklet used to list the buildings, housing units, households, and the Institutional Living Quarters (ILQs) within an EA. This form also records other important information such as the name of household heads and name and type of institutions and their addresses, population totals, and counts of males and females.

    CPH Form 2 - Common Household Questionnaire This is the basic census questionnaire, which was used to interview and record information about the common or nonsample households. This questionnaire gathered information on the following demographic and socio-economic characteristics of the population: relationship to household head, sex, date of birth, age, birth registration, marital status, religion, ethnicity, citizenship, disability, functional difficulty, highest grade/year completed, residence 5 years ago, and overseas worker. It also contains questions on the type of building/house, construction materials of the roof and outer walls, state of repair of the building/house, year the building/house was built, floor area of the housing unit, and tenure status of the lot.

    CPH Form 3 - Sample Household Questionnaire This is the basic census questionnaire, which was used to interview and record information about the sample households. This questionnaire contains ALL questions asked in CPH Form 2 PLUS additional population questions: literacy, school attendance, place of school, usual occupation, kind of business or industry, class of worker, place of work, and some items on fertility. Moreover, there are additional questions on household characteristics: fuel for lighting and cooking, source of water supply for drinking and/or cooking and for laundry, and bathing, tenure status of the housing unit, acquisition of the housing unit, source of financing of the housing unit, monthly rental of the housing unit, tenure status of the lot, usual manner of garbage disposal, kind of toilet facility, and land ownership. It also asked questions on the language/dialect generally spoken at home, residence five years from now, and presence of household conveniences/devices, and access to internet.

    CPH Form 4 -

  13. i

    Family Income and Expenditure Survey 1994 - Philippines

    • catalog.ihsn.org
    Updated Mar 29, 2019
    + more versions
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    National Statistics Office (2019). Family Income and Expenditure Survey 1994 - Philippines [Dataset]. https://catalog.ihsn.org/catalog/3700
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    National Statistics Office
    Time period covered
    1994 - 1995
    Area covered
    Philippines
    Description

    Abstract

    The 1994 Family Income and Expenditure Survey (FIES) is a nationwide survey of households undertaken by the National Statistics Office (NSO). Similar surveys were conducted in 1956-1957, 1961, 1965, 1971, 1975, 1979, 1985 and 1988. Like the previous surveys, this undertaking aims to accomplish the following primary objectives:

    1. to gather data on family income and family living expenditures and related information affecting income and expenditure levels and patterns in the Philippines;

    2. to determine the sources of income and income distribution, levels of living and spending patterns, and the degree of inequality among families;

    3. to provide benchmark information to update weights for the estimation of consumer price index (CPI)

    Geographic coverage

    National coverage

    Analysis unit

    Household Consumption expenditure item Income by source

    Universe

    The 1994 FIES has as its target population, all households and members of households nationwide. Institutional population is not within the scope of the survey.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling design of the 1994 FIES adopts that of the Integrated Survey of Households (ISH), which uses a stratified two-stage cluster sampling design. It is prepared by the National Economic and Development Authority (NEDA) Technical Committee on Survey Design and first implemented in 1984. It is the same sampling design used in the ISH modules starting in 1986.

    The urban and rural areas of each province are the principal domains of the survey. In addition, the urban and rural areas of cities with a population of 150,000 or more as of 1990 are also made domains of the survey with rural and urban dimensions. These include the four cities and five municipalities of Metro Manila (Manila, Quezon City, Pasay and Caloocan; Valenzuela, Parañaque, Pasig, Marikina and Makati), and other key cities such as Baguio, Angeles, Cabanatuan, Olongapo, Batangas, Lipa, Lucena, San Pablo, Bacolod, Iloilo, Cebu, Mandaue, Zamboanga, Butuan, Cagayan de Oro, Davao, General Santos, and Iligan and key municipalities such as San Fernando, Pampanga and Tarlac, Tarlac.

    Sampling Units and Sampling Frame The primary sampling units (PSUs) under the sample design are the barangays and the households within each sample barangay comprise the secondary sampling units (SSUs).

    The frame from which the sample barangays are drawn is obtained from the 1990 Census of Population and Housing (CPH). Hence, all the approximately 40,000 barangays covered in the 1990 CPH are part of the primary sampling frame.

    The sampling frame for the SSUs, that is, the households, is prepared by listing all households in each of the selected sample barangays. The listing operation is conducted regularly in the sample barangays to update the secondary sampling frame from where the sample households are selected.

    Sample Size and Sampling Fraction The size of the sample is envisioned to meet the demand for fairly adequate statistics at the domain level. Taking this need into account and considering cost constraints as well, the decision reached is for a national sample of about 26,000 households.

    In general, the sample design results in self-weighting samples within domains, with a uniform sampling fraction of 1:400 for urban and 1:600 for rural areas. However, special areas are assigned different sampling fractions so as to obtain "adequate" samples for each. Special areas refer to the urban and rural areas of a province or large city which are small relative to their counterparts.

    Selection of Samples For the purpose of selecting PSUs, the barangay in each domain are arranged by population size (as of the 1990 Census of Population) in descending order and then grouped into strata of approximately equal sizes. Four independent PSUs are drawn with probability proportional to size with complete replacement.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaire has five main parts consisting of the following: Part I. Identification and Other Information (Geographic Identification, Other Information and Particulars about the Family)

    Part II. Expenditures and Other Disbursements Section A. Food, Alcoholic Beverages and Tobacco Section B. Fuel, Light and Water, Transportation and Communication, Household Operations Section C. Personal Care and Effects, Clothing Footwear and Other Wear Section D. Education, Recreation, and Medical Care Section E. Furnishings and Equipment Section F. Taxes Section G. Housing, House Maintenance and Minor Repairs Section H. Miscellaneous Expenditures Section I. Other Disbursements

    Part III. Income Section A. Salaries and Wages from Employment Section B. Net Share of Crops, Fruits and Vegetables Produced and/or Livestock and Poultry Raised by Other Households Section C. Other Sources of Income Section D. Other Receipts Section F. Family Sustenance Activities

    Part IV. Entrepreneurial Activities Section A1. Crop Farming and Gardening Section A2. Livestock and Poultry Raising Section A3. Fishing Section A4. Forestry and Hunting Section A5. Wholesale and Retail Section A6. Manufacturing Section A7. Community, Social, Recreational and Personal Services Section A8. Transportation, Storage and Communication Services Section A9. Mining and Quarrying Section A10. Construction Section A11. Entrepreneurial Activities Not Elsewhere Classified

    Part V: Health - Care Section A. Health - care Expenditures Section B. Health Insurance

    Cleaning operations

    The 1994 FIES questionnaire contains about 800 data items and a guide for comparing income and expenditures and internal consistency.

    Upon submission of the data diskettes containing first and second visit data, a summary file was extracted from the entire file through a computer program.

    The questionnaires were further subjected to a rigorous manual and machine edit checks for completeness, arithmetic accuracy, range validity and internal consistency. Items failing any of the edit checks were either corrected automatically by the computer on the basis of pre-determined specifications or, when needed, examined in a clerical error-reconciliation operation.

    The electronic data-processing (EDP) system developed by the NSO Data Processing Staff and used in the 1985 and 1988 FIES was generally adopted in processing the 1991 FIES with few modifications. There are thirteen (13) major steps in the machine processing of the 1991 FIES and these are as follows: 1. Data entry and verification 2. Structural editing (minor edit) 3. Edit list verification/correction 4. Update 5. Completeness check 6. Completeness check list verification/correction 7. Identification verification 8. Extraction of summary file for preliminary results 9. Matching of visit records (big edit) 10. Internal consistency checks (big edit) 11. Reject lists verification/correction 12. Update 13. Expansion 14. Tabulation 15. Generation of CPI weight tables 16. Variance analysis

    Steps 1 to 8 were performed right after each visit while the remaining steps were carried out upon completion of the data collection for the first and second visits. Steps 1 to 7 were implemented at the regional offices. In addition, except for NCR, Region 3, 6, 7 and the province of Basilan, Sulu, Tawi-tawi and Zamboanga City which were handled by the Central Office. Steps 10 and 11 were likewise undertaken in the regional offices. The first passes of reject listings were sent to the regional offices for verification and correction/updates are sent back to the Central Office for data file updating. Meanwhile, steps 8, 9 and all the concluding steps were handles by the Central Office.

    For data entry, IMPS (Integrated Microcomputer Processing System) was used.

    Response rate

    The response rate is the ratio of the total responding households to the total number of eligible households. Eligible households include households who were completely interviewed, refused to be interviewed or were temporarily away or not at home or on vacation during the survey period.

    Sampling error estimates

    As in all surveys, two types of non-response were encountered in the 1994 FIES: interview non-response and item non-response. Interview non-response refers to a sample household that could not be interviewed. Since the survey requires that the sample households be interviewed in both visits, households that transferred to another dwelling unit, temporarily away, on vacation, not at home, household unit demolished, destroyed by fire/typhoon and refusal to be interviewed in the second visit contributed to the number of interview non-response cases.

    Item non-response, or the failure to obtain responses to particular survey items, resulted from factors such as respondents being unaware of the answer to a particular question, unwilling to provide the requested information or ENs' omission of questions during the interview. Deterministic imputation was done to address item nonresponse. This imputation is a process in which proper entry for a particular missing item was deduced from other items of the questionnaire where the non-response item was observed. Notes and remarks indicated in the questionnaire were likewise used as basis for imputation.

  14. Smart City Index ranking APAC 2024

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Smart City Index ranking APAC 2024 [Dataset]. https://www.statista.com/statistics/1482724/apac-smart-city-index-ranking/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Asia-Pacific
    Description

    In 2024, Canberra, the capital city of Australia, ranked ***** in the global Smart City Index while topping the list among the reported Asia-Pacific cities. Contrastingly, Manila, the capital city of the Philippines, ranked ***** in the Smart City Index globally.

  15. Richest provinces Philippines 2023, by asset value

    • statista.com
    Updated Aug 8, 2025
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    Statista (2025). Richest provinces Philippines 2023, by asset value [Dataset]. https://www.statista.com/statistics/1019019/wealthiest-provinces-philippines-by-asset-value/
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    Dataset updated
    Aug 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Philippines
    Description

    The province of Cebu topped the ranking of the wealthiest provinces in the Philippines, with assets amounting to approximately 310 billion Philippine pesos in 2023. Following by a large margin were the provinces of Rizal and Camarines Sur.

  16. Employment rate NCR Philippines 2024, by city and municipality

    • statista.com
    Updated Aug 8, 2025
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    Statista (2025). Employment rate NCR Philippines 2024, by city and municipality [Dataset]. https://www.statista.com/statistics/1424591/philippines-employment-rate-metro-manila-by-city/
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    Dataset updated
    Aug 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Philippines
    Description

    In 2024, the City of Pasig had the highest employment rate in the whole Metro Manila at **** percent. In comparison, the city of Manila had an employment rate of **** percent.

  17. Countries with the most YouTube users 2025

    • statista.com
    Updated Feb 17, 2025
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    Statista (2025). Countries with the most YouTube users 2025 [Dataset]. https://www.statista.com/statistics/280685/number-of-monthly-unique-youtube-users/
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    Dataset updated
    Feb 17, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2025
    Area covered
    YouTube, Worldwide
    Description

    As of February 2025, India was the country with the largest YouTube audience by far, with approximately 491 million users engaging with the popular social video platform. The United States followed, with around 253 million YouTube viewers. Brazil came in third, with 144 million users watching content on YouTube. The United Kingdom saw around 54.8 million internet users engaging with the platform in the examined period. What country has the highest percentage of YouTube users? In July 2024, the United Arab Emirates was the country with the highest YouTube penetration worldwide, as around 94 percent of the country's digital population engaged with the service. In 2024, YouTube counted around 100 million paid subscribers for its YouTube Music and YouTube Premium services. YouTube mobile markets In 2024, YouTube was among the most popular social media platforms worldwide. In terms of revenues, the YouTube app generated approximately 28 million U.S. dollars in revenues in the United States in January 2024, as well as 19 million U.S. dollars in Japan.

  18. Unemployment rate NCR Philippines 2024, by city and municipality

    • statista.com
    Updated Aug 8, 2025
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    Statista (2025). Unemployment rate NCR Philippines 2024, by city and municipality [Dataset]. https://www.statista.com/statistics/1424552/philippines-unemployment-rate-metro-manila-by-city/
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    Dataset updated
    Aug 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    Philippines
    Description

    In 2024, the Municipality of Pateros had the highest unemployment rate in the whole of Metro Manila in the Philippines at *** percent. In comparison, the city of Manila had an unemployment rate of *** percent.

  19. Priciest subdivision in Metro Manila, Philippines 2024, by max price range

    • statista.com
    Updated Aug 8, 2025
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    Statista (2025). Priciest subdivision in Metro Manila, Philippines 2024, by max price range [Dataset]. https://www.statista.com/statistics/1013708/major-high-end-residential-areas-philippines/
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    Dataset updated
    Aug 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    As of February 2024, Forbes Park in Makati City was the most expensive subdivision in Metro Manila in the Philippines. The maximum price range of this gated village amounted to *** billion Philippine pesos for a house and lot property. Meanwhile, properties in the Sikatuna Village in Quezon City had a maximum price of ** million Philippine pesos.

  20. Most vote-rich provinces Philippines 2022

    • statista.com
    Updated Jun 25, 2025
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    Statista (2025). Most vote-rich provinces Philippines 2022 [Dataset]. https://www.statista.com/statistics/1308074/philippines-most-vote-rich-provinces/
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    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Philippines
    Description

    For the 2022 national elections, the most vote-rich province in the Philippines was Cebu, with around **** million registered voters. This was followed by Cavite and Pangasinan with *** million and *** million registered voters, respectively.

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Statista (2025). Wealthiest cities Philippines 2023, by asset value [Dataset]. https://www.statista.com/statistics/1019020/wealthiest-cities-philippines-asset-value/
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Wealthiest cities Philippines 2023, by asset value

Explore at:
Dataset updated
Aug 8, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
Philippines
Description

In 2023, Quezon was the wealthiest city in the Philippines, with approximately 449 billion Philippine pesos worth of assets. Following by a large margin was Makati City. In that year, the province of Cebu was the wealthiest province in the country.

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