18 datasets found
  1. T

    Philippines Unemployment Rate

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Sep 10, 2025
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    TRADING ECONOMICS (2025). Philippines Unemployment Rate [Dataset]. https://tradingeconomics.com/philippines/unemployment-rate
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    json, excel, xml, csvAvailable download formats
    Dataset updated
    Sep 10, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Mar 31, 1986 - Jul 31, 2025
    Area covered
    Philippines
    Description

    Unemployment Rate in Philippines increased to 5.30 percent in July from 3.70 percent in June of 2025. This dataset provides - Philippines Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  2. T

    Philippines Employed Persons

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 15, 2025
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    TRADING ECONOMICS (2025). Philippines Employed Persons [Dataset]. https://tradingeconomics.com/philippines/employed-persons
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    json, xml, csv, excelAvailable download formats
    Dataset updated
    Jul 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Mar 31, 1986 - Jul 31, 2025
    Area covered
    Philippines
    Description

    The number of employed persons in Philippines decreased to 46046.45 Thousand in July of 2025 from 50474.72 Thousand in June of 2025. This dataset provides - Philippines Employed Persons - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  3. P

    Philippines Overseas Filipino Workers (OFWs)

    • ceicdata.com
    Updated Mar 15, 2018
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    CEICdata.com (2018). Philippines Overseas Filipino Workers (OFWs) [Dataset]. https://www.ceicdata.com/en/philippines/overseas-filipino-workers/overseas-filipino-workers-ofws
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    Dataset updated
    Mar 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, 2011 - Dec 1, 2022
    Area covered
    Philippines
    Description

    Philippines Overseas Filipino Workers (OFWs) data was reported at 2,156.616 Number th in 2023. This records an increase from the previous number of 1,963.403 Number th for 2022. Philippines Overseas Filipino Workers (OFWs) data is updated yearly, averaging 1,982.702 Number th from Dec 1999 (Median) to 2023, with 24 observations. The data reached an all-time high of 2,447.000 Number th in 2015 and a record low of 978.000 Number th in 2000. Philippines Overseas Filipino Workers (OFWs) data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G044: Overseas Filipino Workers.

  4. T

    Philippines Employment Rate

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 15, 2025
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    TRADING ECONOMICS (2025). Philippines Employment Rate [Dataset]. https://tradingeconomics.com/philippines/employment-rate
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    csv, excel, json, xmlAvailable download formats
    Dataset updated
    Jul 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Mar 31, 1991 - Jul 31, 2025
    Area covered
    Philippines
    Description

    Employment Rate in Philippines decreased to 94.70 percent in July from 96.30 percent in June of 2025. This dataset provides - Philippines Employment Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  5. w

    Philippines - National Demographic Survey 1993 - Dataset - waterdata

    • wbwaterdata.org
    Updated Mar 16, 2020
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    (2020). Philippines - National Demographic Survey 1993 - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/philippines-national-demographic-survey-1993
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    Dataset updated
    Mar 16, 2020
    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 1993 National Demographic Survey (NDS) is a nationally representative sample survey of women age 15-49 designed to collect information on fertility; family planning; infant, child and maternal mortality; and maternal and child health. The survey was conducted between April and June 1993. The 1993 NDS was carried out by the National Statistics Office in collaboration with the Department of Health, the University of the Philippines Population Institute, and other agencies concerned with population, health and family planning issues. Funding for the 1993 NDS was provided by the U.S. Agency for International Development through the Demographic and Health Surveys Program. Close to 13,000 households throughout the country were visited during the survey and more than 15,000 women age 15-49 were interviewed. The results show that fertility in the Philippines continues its gradual decline. At current levels, Filipino women will give birth on average to 4.1 children during their reproductive years, 0.2 children less than that recorded in 1988. However, the total fertility rate in the Philippines remains high in comparison to the level achieved in the neighboring Southeast Asian countries. The primary objective of the 1993 NDS is to provide up-to-date inform ation on fertility and mortality levels; nuptiality; fertility preferences; awareness, approval, and use of family planning methods; breastfeeding practices; and maternal and child health. This information is intended to assist policymakers and administrators in evaluating and designing programs and strategies for improving health and family planning services in 'the country. MAIN RESULTS Fertility varies significantly by region and socioeconomic characteristics. Urban women have on average 1.3 children less than rural women, and uneducated women have one child more than women with college education. Women in Bicol have on average 3 more children than women living in Metropolitan Manila. Virtually all women know of a family planning method; the pill, female sterilization, IUD and condom are known to over 90 percent of women. Four in 10 married women are currently using contraception. The most popular method is female sterilization ( 12 percent), followed by the piU (9 percent), and natural family planning and withdrawal, both used by 7 percent of married women. Contraceptive use is highest in Northern Mindanao, Central Visayas and Southern Mindanao, in urban areas, and among women with higher than secondary education. The contraceptive prevalence rate in the Philippines is markedly lower than in the neighboring Southeast Asian countries; the percentage of married women who were using family planning in Thailand was 66 percent in 1987, and 50 percent in Indonesia in 199l. The majority of contraceptive users obtain their methods from a public service provider (70 percent). Government health facilities mainly provide permanent methods, while barangay health stations or health centers are the main sources for the pill, IUD and condom. Although Filipino women already marry at a relatively higher age, they continue to delay the age at which they first married. Half of Filipino women marry at age 21.6. Most women have their first sexual intercourse after marriage. Half of married women say that they want no more children, and 12 percent have been sterilized. An additional 19 percent want to wait at least two years before having another child. Almost two thirds of women in the Philippines express a preference for having 3 or less children. Results from the survey indicate that if all unwanted births were avoided, the total fertility rate would be 2.9 children, which is almost 30 percent less than the observed rate, More than one quarter of married women in the Philippines are not using any contraceptive method, but want to delay their next birth for two years or more (12 percent), or want to stop childbearing (14 percent). If the potential demand for family planning is satisfied, the contraceptive prevalence rate could increase to 69 percent. The demand for stopping childbearing is about twice the level for spacing (45 and 23 percent, respectively). Information on various aspects of maternal and child health-antenatal care, vaccination, breastfeeding and food supplementation, and illness was collected in the 1993 NDS on births in the five years preceding the survey. The findings show that 8 in 10 children under five were bom to mothers who received antenatal care from either midwives or nurses (45 percent) or doctors (38 percent). Delivery by a medical personnel is received by more than half of children born in the five years preceding the survey. However, the majority of deliveries occurred at home. Tetanus, a leading cause of infant deaths, can be prevented by immunization of the mother during pregnancy. In the Philippines, two thirds of bitlhs in the five years preceding the survey were to mothers who received a tetanus toxoid injection during pregnancy. Based on reports of mothers and information obtained from health cards, 90 percent of children aged 12-23 months have received shots of the BCG as well as the first doses of DPT and polio, and 81 percent have received immunization from measles. Immunization coverage declines with doses; the drop out rate is 3 to 5 percent for children receiving the full dose series of DPT and polio. Overall, 7 in 10 children age 12-23 months have received immunization against the six principal childhood diseases-polio, diphtheria, ~rtussis, tetanus, measles and tuberculosis. During the two weeks preceding the survey, 1 in 10 children under 5 had diarrhea. Four in ten of these children were not treated. Among those who were treated, 27 percent were given oral rehydration salts, 36 percent were given recommended home solution or increased fluids. Breasffeeding is less common in the Philippines than in many other developing countries. Overall, a total of 13 percent of children born in the 5 years preceding the survey were not breastfed at all. On the other hand, bottle feeding, a widely discouraged practice, is relatively common in the Philippines. Children are weaned at an early age; one in four children age 2-3 months were exclusively breastfed, and the mean duration of breastfeeding is less than 3 months. Infant and child mortality in the Philippines have declined significantly in the past two decades. For every 1,000 live births, 34 infants died before their first birthday. Childhood mortality varies significantly by mother's residence and education. The mortality of urban infants is about 40 percent lower than that of rural infants. The probability of dying among infants whose mother had no formal schooling is twice as high as infants whose mother have secondary or higher education. Children of mothers who are too young or too old when they give birth, have too many prior births, or give birth at short intervals have an elevated mortality risk. Mortality risk is highest for children born to mothers under age 19. The 1993 NDS also collected information necessary for the calculation of adult and maternal mortality using the sisterhood method. For both males and females, at all ages, male mortality is higher than that of females. Matemal mortality ratio for the 1980-1986 is estimated at 213 per 100,000 births, and for the 1987-1993 period 209 per 100,000 births. However, due to the small number of sibling deaths reported in the survey, age-specific rates should be used with caution. Information on health and family planning services available to the residents of the 1993 NDS barangay was collected from a group of respondents in each location. Distance and time to reach a family planning service provider has insignificant association with whether a woman uses contraception or the choice of contraception being used. On the other hand, being close to a hospital increases the likelihood that antenatal care and births are to respondents who receive ANC and are delivered by a medical personnel or delivered in a health facility.

  6. T

    Philippines Unemployed Persons

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Philippines Unemployed Persons [Dataset]. https://tradingeconomics.com/philippines/unemployed-persons
    Explore at:
    json, xml, csv, excelAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Mar 31, 1986 - Jul 31, 2025
    Area covered
    Philippines
    Description

    The number of unemployed persons in Philippines increased to 2593.41 Thousand in July of 2025 from 1949.02 Thousand in June of 2025. This dataset provides - Philippines Unemployed Persons - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  7. F

    Filipino General Conversation Speech Dataset for ASR

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    + more versions
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    FutureBee AI (2022). Filipino General Conversation Speech Dataset for ASR [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/general-conversation-filipino-philippines
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    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Area covered
    Philippines
    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    Welcome to the Filipino General Conversation Speech Dataset — a rich, linguistically diverse corpus purpose-built to accelerate the development of Filipino speech technologies. This dataset is designed to train and fine-tune ASR systems, spoken language understanding models, and generative voice AI tailored to real-world Filipino communication.

    Curated by FutureBeeAI, this 30 hours dataset offers unscripted, spontaneous two-speaker conversations across a wide array of real-life topics. It enables researchers, AI developers, and voice-first product teams to build robust, production-grade Filipino speech models that understand and respond to authentic Filipino accents and dialects.

    Speech Data

    The dataset comprises 30 hours of high-quality audio, featuring natural, free-flowing dialogue between native speakers of Filipino. These sessions range from informal daily talks to deeper, topic-specific discussions, ensuring variability and context richness for diverse use cases.

    Participant Diversity:
    Speakers: 60 verified native Filipino speakers from FutureBeeAI’s contributor community.
    Regions: Representing various provinces of Philippines to ensure dialectal diversity and demographic balance.
    Demographics: A balanced gender ratio (60% male, 40% female) with participant ages ranging from 18 to 70 years.
    Recording Details:
    Conversation Style: Unscripted, spontaneous peer-to-peer dialogues.
    Duration: Each conversation ranges from 15 to 60 minutes.
    Audio Format: Stereo WAV files, 16-bit depth, recorded at 16kHz sample rate.
    Environment: Quiet, echo-free settings with no background noise.

    Topic Diversity

    The dataset spans a wide variety of everyday and domain-relevant themes. This topic diversity ensures the resulting models are adaptable to broad speech contexts.

    Sample Topics Include:
    Family & Relationships
    Food & Recipes
    Education & Career
    Healthcare Discussions
    Social Issues
    Technology & Gadgets
    Travel & Local Culture
    Shopping & Marketplace Experiences, and many more.

    Transcription

    Each audio file is paired with a human-verified, verbatim transcription available in JSON format.

    Transcription Highlights:
    Speaker-segmented dialogues
    Time-coded utterances
    Non-speech elements (pauses, laughter, etc.)
    High transcription accuracy, achieved through double QA pass, average WER < 5%

    These transcriptions are production-ready, enabling seamless integration into ASR model pipelines or conversational AI workflows.

    Metadata

    The dataset comes with granular metadata for both speakers and recordings:

    Speaker Metadata: Age, gender, accent, dialect, state/province, and participant ID.
    Recording Metadata: Topic, duration, audio format, device type, and sample rate.

    Such metadata helps developers fine-tune model training and supports use-case-specific filtering or demographic analysis.

    Usage and Applications

    This dataset is a versatile resource for multiple Filipino speech and language AI applications:

    ASR Development: Train accurate speech-to-text systems for Filipino.
    Voice Assistants: Build smart assistants capable of understanding natural Filipino conversations.

  8. Mobile phone users Philippines 2021-2029

    • statista.com
    Updated Feb 28, 2025
    + more versions
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    Statista (2025). Mobile phone users Philippines 2021-2029 [Dataset]. https://www.statista.com/forecasts/558756/number-of-mobile-internet-user-in-the-philippines
    Explore at:
    Dataset updated
    Feb 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    The number of smartphone users in the Philippines was forecast to increase between 2024 and 2029 by in total 5.6 million users (+7.29 percent). This overall increase does not happen continuously, notably not in 2026, 2027, 2028 and 2029. The smartphone user base is estimated to amount to 82.33 million users in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

  9. Data from: Lost on the frontline, and lost in the data: COVID-19 deaths...

    • figshare.com
    zip
    Updated Jul 22, 2022
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    Loraine Escobedo (2022). Lost on the frontline, and lost in the data: COVID-19 deaths among Filipinx healthcare workers in the United States [Dataset]. http://doi.org/10.6084/m9.figshare.20353368.v1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jul 22, 2022
    Dataset provided by
    Figsharehttp://figshare.com/
    figshare
    Authors
    Loraine Escobedo
    License

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

    Area covered
    United States
    Description

    To estimate county of residence of Filipinx healthcare workers who died of COVID-19, we retrieved data from the Kanlungan website during the month of December 2020.22 In deciding who to include on the website, the AF3IRM team that established the Kanlungan website set two standards in data collection. First, the team found at least one source explicitly stating that the fallen healthcare worker was of Philippine ancestry; this was mostly media articles or obituaries sharing the life stories of the deceased. In a few cases, the confirmation came directly from the deceased healthcare worker's family member who submitted a tribute. Second, the team required a minimum of two sources to identify and announce fallen healthcare workers. We retrieved 86 US tributes from Kanlungan, but only 81 of them had information on county of residence. In total, 45 US counties with at least one reported tribute to a Filipinx healthcare worker who died of COVID-19 were identified for analysis and will hereafter be referred to as “Kanlungan counties.” Mortality data by county, race, and ethnicity came from the National Center for Health Statistics (NCHS).24 Updated weekly, this dataset is based on vital statistics data for use in conducting public health surveillance in near real time to provide provisional mortality estimates based on data received and processed by a specified cutoff date, before data are finalized and publicly released.25 We used the data released on December 30, 2020, which included provisional COVID-19 death counts from February 1, 2020 to December 26, 2020—during the height of the pandemic and prior to COVID-19 vaccines being available—for counties with at least 100 total COVID-19 deaths. During this time period, 501 counties (15.9% of the total 3,142 counties in all 50 states and Washington DC)26 met this criterion. Data on COVID-19 deaths were available for six major racial/ethnic groups: Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Native Hawaiian or Other Pacific Islander, Non-Hispanic American Indian or Alaska Native, Non-Hispanic Asian (hereafter referred to as Asian American), and Hispanic. People with more than one race, and those with unknown race were included in the “Other” category. NCHS suppressed county-level data by race and ethnicity if death counts are less than 10. In total, 133 US counties reported COVID-19 mortality data for Asian Americans. These data were used to calculate the percentage of all COVID-19 decedents in the county who were Asian American. We used data from the 2018 American Community Survey (ACS) five-year estimates, downloaded from the Integrated Public Use Microdata Series (IPUMS) to create county-level population demographic variables.27 IPUMS is publicly available, and the database integrates samples using ACS data from 2000 to the present using a high degree of precision.27 We applied survey weights to calculate the following variables at the county-level: median age among Asian Americans, average income to poverty ratio among Asian Americans, the percentage of the county population that is Filipinx, and the percentage of healthcare workers in the county who are Filipinx. Healthcare workers encompassed all healthcare practitioners, technical occupations, and healthcare service occupations, including nurse practitioners, physicians, surgeons, dentists, physical therapists, home health aides, personal care aides, and other medical technicians and healthcare support workers. County-level data were available for 107 out of the 133 counties (80.5%) that had NCHS data on the distribution of COVID-19 deaths among Asian Americans, and 96 counties (72.2%) with Asian American healthcare workforce data. The ACS 2018 five-year estimates were also the source of county-level percentage of the Asian American population (alone or in combination) who are Filipinx.8 In addition, the ACS provided county-level population counts26 to calculate population density (people per 1,000 people per square mile), estimated by dividing the total population by the county area, then dividing by 1,000 people. The county area was calculated in ArcGIS 10.7.1 using the county boundary shapefile and projected to Albers equal area conic (for counties in the US contiguous states), Hawai’i Albers Equal Area Conic (for Hawai’i counties), and Alaska Albers Equal Area Conic (for Alaska counties).20

  10. Average daily traffic volume Metro Manila Philippines 2018-2024

    • statista.com
    Updated Aug 8, 2025
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    Statista (2025). Average daily traffic volume Metro Manila Philippines 2018-2024 [Dataset]. https://www.statista.com/statistics/1276518/philippines-average-daily-traffic-metro-manila/
    Explore at:
    Dataset updated
    Aug 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    The streets and highways of Metro Manila in the Philippines saw an average of 3.82 million vehicles traveling each day in 2024. This was about 20,000 vehicles more than the year before. Metro Manila is notorious for its traffic congestion, and motorists in Manila City alone can lose about 100 hours annually when driving during rush hour. Which vehicles congest Metro Manila?  In 2024, motorcycles were the vehicles with the highest average daily traffic volume in Metro Manila. Aside from being affordable, motorcycles are the best option for navigating the traffic-congested streets of the region. Most Filipinos own a scooter, followed by mopeds. Next to motorcycles, cars, either private or rental, were also a major source of traffic in Metro Manila. Commuting in Metro Manila As the volume of vehicles traveling within Metro Manila continues to increase, commuters may have to spend hours each day getting to their destination. While public transportation options, such as commuter trains, jeepneys, and buses, are available, travelers may face difficulties in reaching their destination with less stress and travel time. According to a nationwide Statista survey in June 2024, most Filipinos spend 15 minutes to about an hour each day commuting to work, school, or university. However, factors such as proximity to the destination and whether the respondents live in rural or urban areas should be considered.

  11. T

    Philippines Daily Minimum Wages

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated Apr 4, 2019
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    TRADING ECONOMICS (2019). Philippines Daily Minimum Wages [Dataset]. https://tradingeconomics.com/philippines/minimum-wages
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    json, xml, csv, excelAvailable download formats
    Dataset updated
    Apr 4, 2019
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jul 1, 1989 - Jan 31, 2025
    Area covered
    Philippines
    Description

    Minimum Wages in Philippines remained unchanged at 645 PHP/day in 2025 from 645 PHP/day in 2024. This dataset provides - Philippines Minimum Wages- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  12. Number of mobile broadband connections in the Philippines 2014-2029

    • statista.com
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    Statista Research Department, Number of mobile broadband connections in the Philippines 2014-2029 [Dataset]. https://www.statista.com/topics/8230/smartphones-market-in-the-philippines/
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    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    Philippines
    Description

    The number of mobile broadband connections in the Philippines was forecast to continuously increase between 2024 and 2029 by in total 18.3 million connections (+20.46 percent). After the ninth consecutive increasing year, the number of connections is estimated to reach 107.69 million connections and therefore a new peak in 2029. Mobile broadband connections include cellular connections with a download speed of at least 256 kbit/s (without satellite or fixed-wireless connections). Cellular Internet-of-Things (IoT) or machine-to-machine (M2M) connections are excluded. The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of mobile broadband connections in countries like Vietnam and Laos.

  13. Number of HIV cases Philippines 2012-2024

    • statista.com
    Updated Aug 8, 2025
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    Statista (2025). Number of HIV cases Philippines 2012-2024 [Dataset]. https://www.statista.com/statistics/701857/philippines-estimated-number-of-people-living-with-hiv/
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    Dataset updated
    Aug 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    The Philippines reported about ****** HIV cases, an increase from the previous year. The number of reported HIV cases has gradually increased since 2012, aside from a significant dip in 2020. The state of HIV As the monthly average number of people newly diagnosed with HIV increases, the risk it poses threatens the lives of Filipinos. HIV is a sexually transmitted infection that attacks the body’s immune system, with more males being diagnosed than females. In 2022, the majority of people newly diagnosed with HIV were those between the age of 25 and 34 years, followed by those aged 15 and 24. There is still no cure for HIV and without treatment, it could lead to other severe illnesses such as tuberculosis and cancers such as lymphoma and Kaposi’s sarcoma. However, HIV is now a manageable chronic illness that can be treated with proper medication. What are the leading causes of death in the Philippines? Between January and September 2024, preliminary figures have shown that ischaemic heart disease was the leading cause of death in the Philippines. The prevalence of heart diseases in the nation has been closely attributed to the Filipino diet, which was described as having a high fat, high cholesterol, and high sodium content. In addition, acute respiratory infections and hypertension also registered the highest morbidity rate among leading diseases in the country in 2021.

  14. e

    Filipino Nurses and Carers in the United Kingdom - Dataset - B2FIND

    • b2find.eudat.eu
    Updated Oct 30, 2023
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    (2023). Filipino Nurses and Carers in the United Kingdom - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/20c16048-90c4-5cd2-8d64-e53faedc3049
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    Dataset updated
    Oct 30, 2023
    Area covered
    United Kingdom, Philippines
    Description

    This project investigated various routes of entry to the UK of labour migrants coming from a single source country. Additionally, face-to-face interviews were conducted with recruiters, experts and healthcare professionals involved in training and administration in the Philippines. A total of 73 transcripts were compiled, 19 from care home assistants/nurses, 19 from domestic workers, 18 from hospital nurses, 13 from Philippine fieldwork (including student nurses), 2 from UK based recruitment agencies, 1 from a migrant organisation and 1 from a UK care home. Data and literature on health worker emigration patterns were gathered from local research bodies. The mission of the Centre is to provide a strategic, integrated approach to understanding contemporary and future migration dynamics across sending areas and receiving contexts in the UK and EU. In 2003, Filipinos made up the largest and most visible group of internationally recruited nurses in the UK. Of roughly 13,000 overseas nationals registered with the Nursing and Midwifery Council (NMC) that year, around 5,600, or almost half, came from the Philippines. They also figured prominently in private care homes and in the provision of care in private households. While there are various nationalities contributing to the care workforce, this project narrowed its focus on care workers from the Philippines due to it being a sector that is heavily segmented by ‘race,’ nationality, as well as immigration status. Focusing on one nationality also allowed us to investigate various routes of entry in the UK of labour migrants coming from a single source country. Additionally, fieldwork was carried out in the Philippines between November and December 2004 in order to asses the effect of nursing and care work recruitment from the sending country perspective. A series of interviews were conducted with recruiters, academics, experts and healthcare professionals involved in training and administration. Data and literature on health worker emigration patterns were gathered from local research bodies. The following findings were observed: (1) Many care workers arrived in the UK via other countries, highlighting the wide scope of multinational recruitment agencies. (2) Filipino care workers arriving via Singapore and the Middle East tended to enter via student visas, but employers assigned them more work than their immigration status allowed (they worked 35-40 hours compared to the regulated 20 hours) (3) Nurses working in care homes experienced more difficulty applying for registration, and were in some cases discouraged by employers. (4) Regulatory conditions differ significantly between public and private care providers. Recruitment to private nursing homes is particularly unregulated. 73 face-to-face interviews were conducted and transcribed from 19 care home assistants/nurses, 19 domestic workers, 18 hospital nurses, 13 Philippine fieldwork (including student nurses), 2 UK based recruitment agencies, a migrant organisation and a UK care home. No sampling method was used, it was totally universe. Data and literature on health worker emigration patterns were gather from local research bodies.

  15. T

    Philippines Coronavirus COVID-19 Deaths

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 4, 2020
    + more versions
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    TRADING ECONOMICS (2020). Philippines Coronavirus COVID-19 Deaths [Dataset]. https://tradingeconomics.com/philippines/coronavirus-deaths
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    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Mar 4, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 3, 2020 - May 17, 2023
    Area covered
    Philippines
    Description

    Philippines recorded 66453 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, Philippines reported 4115202 Coronavirus Cases. This dataset includes a chart with historical data for Philippines Coronavirus Deaths.

  16. F

    In-Car Speech Dataset: Filipino (Philippines)

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). In-Car Speech Dataset: Filipino (Philippines) [Dataset]. https://www.futurebeeai.com/dataset/monologue-speech-dataset/in-car-speech-dataset-filipino
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    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Area covered
    Philippines
    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    Welcome to the Filipino Language In-car Speech Dataset, a comprehensive collection of audio recordings designed to facilitate the development of speech recognition models specifically tailored for in-car environments. This dataset aims to support research and innovation in automotive speech technology, enabling seamless and robust voice interactions within vehicles for drivers and co-passengers.

    Speech Data

    This dataset comprises over 5,000 high-quality audio recordings collected from various in-car environments. These recordings include scripted wake words and command-type prompts.

    Participant Diversity:

    - Speakers: 50+ native Filipino speakers from the FutureBeeAI Community.

    - Regions: Ensures a balanced representation of Philippines1 accents, dialects, and demographics.

    - Participant Profile: Participants range from 18 to 70 years old, representing both males and females in a 60:40 ratio, respectively.

    Recording Nature: Scripted wake word and command type of audio recordings.

    - Duration: Average duration of 5 to 20 seconds per audio recording.

    - Formats: WAV format with mono channels, a bit depth of 16 bits. The dataset contains different data at 16kHz and 48kHz.

    Dataset Diversity

    Apart from participant diversity, the dataset is diverse in terms of different wake words, voice commands, and recording environments.

    Different Automobile Related Wake Words: Hey Mercedes, Hey BMW, Hey Porsche, Hey Volvo, Hey Audi, Hi Genesis, Hey Mini, Hey Toyota, Ok Ford, Hey Hyundai, Ok Honda, Hello Kia, Hey Dodge.

    Different Cars: Data collection was carried out in different types and models of cars.

    Different Types of Voice Commands:

    - Navigational Voice Commands

    - Mobile Control Voice Commands

    - Car Control Voice Commands

    - Multimedia & Entertainment Commands

    - General, Question Answer, Search Commands

    Recording Time: Participants recorded the given prompts at various times to make the dataset more diverse.

    - Morning

    - Afternoon

    - Evening

    Recording Environment: Various recording environments were captured to acquire more realistic data and to make the dataset inclusive of various types of noises. Some of the environment variables are as follows:

    - Noise Level: Silent, Low Noise, Moderate Noise, High Noise

    - Parking Location: Indoor, Outdoor

    - Car Windows: Open, Closed

    - Car AC: On, Off

    - Car Engine: On, Off

    - Car Movement: Stationary, Moving

    Metadata

    The dataset provides comprehensive metadata for each audio recording and participant:

    Participant Metadata: Unique identifier, age, gender, country, state, district, accent, and dialect.

    Other Metadata: Recording transcript, recording environment, device details, sample rate, bit depth, file format, recording time.

    This metadata is a powerful tool for understanding and characterizing the data, enabling informed decision-making in the development of Filipino voice assistant speech recognition models.

    Usage and Applications

    This In-car Speech Dataset is a valuable resource for various applications in the field of in-car voice recognition and AI-driven voice technology. This dataset can be leveraged to enhance the performance and functionality of voice-activated systems across different domains.

    Speech Recognition Model Training: Provides high-quality audio data for training models to accurately recognize and respond to in-car voice commands.

    Safety and Emergency Response: Supports the development of systems that recognize and respond to emergency commands and safety alerts.

    Driver Assistance: Facilitates the creation of advanced driver-assistance systems (ADAS) that leverage voice commands for hands-free operation.

    Secure and Ethical Collection

    Our proprietary data collection platform, “Yugo,” was used throughout the process of this dataset creation.

    Throughout the data collection process, the data remained within our secure platform and did not leave our environment, ensuring data security and confidentiality.

    The data collection process adhered to strict ethical guidelines, ensuring the privacy and consent of all participants.

    It does not include any personally identifiable information about any participant, which makes the dataset safe to use.

    Updates and Customization

    Understanding the importance of diverse environments for robust voice assistant models, our in-car voice dataset is regularly updated with new audio data captured in various real-world conditions.

    Customization & Custom Collection Options:

    - Environmental Conditions: Custom collection in specific environmental conditions upon request.

    - Sample Rates: Customizable from 8kHz to 48kHz.

    - Diverse Pace: Custom collection can be done at a diverse pace upon request.

    - Device Specific: Recording can be done with the specific mobile brand or operating system.

    License

    This Filipino In-car audio dataset is created by FutureBeeAI and is available for commercial use.

  17. F

    Filipino TTS Speech Dataset for Speech Synthesis

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
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    FutureBee AI (2022). Filipino TTS Speech Dataset for Speech Synthesis [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/tts-monolgue-filipino-philippines
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    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Dataset funded by
    FutureBeeAI
    Description

    The Filipino TTS Monologue Speech Dataset is a professionally curated resource built to train realistic, expressive, and production-grade text-to-speech (TTS) systems. It contains studio-recorded long-form speech by trained native Filipino voice artists, each contributing 1 to 2 hours of clean, uninterrupted monologue audio.

    Unlike typical prompt-based datasets with short, isolated phrases, this collection features long-form, topic-driven monologues that mirror natural human narration. It includes content types that are directly useful for real-world applications, like audiobook-style storytelling, educational lectures, health advisories, product explainers, digital how-tos, formal announcements, and more.

    All recordings are captured in professional studios using high-end equipment and under the guidance of experienced voice directors.

    Recording & Audio Quality

    Audio Format: WAV, 48 kHz, available in 16-bit, 24-bit, and 32-bit depth
    SNR: Minimum 30 dB
    Channel: Mono
    Recording Duration: 20-30 minutes
    Recording Environment: Studio-controlled, acoustically treated rooms
    Per Speaker Volume: 1–2 hours of speech per artist
    Quality Control: Each file is reviewed and cleaned for common acoustic issues, including: reverberation, lip smacks, mouth clicks, thumping, hissing, plosives, sibilance, background noise, static interference, clipping, and other artifacts.

    Only clean, production-grade audio makes it into the final dataset.

    Voice Artist Selection

    All voice artists are native Filipino speakers with professional training or prior experience in narration. We ensure a diverse pool in terms of age, gender, and region to bring a balanced and rich vocal dataset.

    Artist Profile:
    Gender: Male and Female
    Age Range: 20–60 years
    Regions: Native Filipino-speaking states from Philippines
    Selection Process: All artists are screened, onboarded, and sample-approved using FutureBeeAI’s proprietary Yugo platform.

    Script Quality & Coverage

    Scripts are not generic or repetitive. Scripts are professionally authored by domain experts to reflect real-world use cases. They avoid redundancy and include modern vocabulary, emotional range, and phonetically rich sentence structures.

    Word Count per Script: 3,000–5,000 words per 30-minute session
    Content Types:
    Storytelling
    Script and book reading
    Informational explainers
    Government service instructions
    E-commerce tutorials
    Motivational content
    Health & wellness guides
    Education & career advice
    Linguistic Design: Balanced punctuation, emotional range, modern syntax, and vocabulary diversity

    Transcripts & Alignment

    While the script is used during the recording, we also provide post-recording updates to ensure the transcript reflects the final spoken audio. Minor edits are made to adjust for skipped or rephrased words.

    Segmentation: Time-stamped at the sentence level, aligned to actual spoken delivery
    Format: Available in plain text and JSON
    Post-processing:
    Corrected for

  18. P

    Philippines Employment: Industry: Construction

    • ceicdata.com
    Updated Aug 11, 2020
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    CEICdata.com (2020). Philippines Employment: Industry: Construction [Dataset]. https://www.ceicdata.com/en/philippines/labour-force-survey-employment-by-industry-occupation-and-class/employment-industry-construction
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    Dataset updated
    Aug 11, 2020
    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
    Feb 1, 2024 - Jan 1, 2025
    Area covered
    Philippines
    Variables measured
    Employment
    Description

    Philippines Employment: Industry: Construction data was reported at 5,031.000 Person th in Feb 2025. This records an increase from the previous number of 4,597.000 Person th for Jan 2025. Philippines Employment: Industry: Construction data is updated monthly, averaging 4,518.500 Person th from Jan 2021 (Median) to Feb 2025, with 50 observations. The data reached an all-time high of 5,769.000 Person th in Jun 2024 and a record low of 4,018.000 Person th in Jan 2023. Philippines Employment: Industry: Construction data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G025: Labour Force Survey: Employment: by Industry, Occupation and Class.

  19. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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TRADING ECONOMICS (2025). Philippines Unemployment Rate [Dataset]. https://tradingeconomics.com/philippines/unemployment-rate

Philippines Unemployment Rate

Philippines Unemployment Rate - Historical Dataset (1986-03-31/2025-07-31)

Explore at:
4 scholarly articles cite this dataset (View in Google Scholar)
json, excel, xml, csvAvailable download formats
Dataset updated
Sep 10, 2025
Dataset authored and provided by
TRADING ECONOMICS
License

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

Time period covered
Mar 31, 1986 - Jul 31, 2025
Area covered
Philippines
Description

Unemployment Rate in Philippines increased to 5.30 percent in July from 3.70 percent in June of 2025. This dataset provides - Philippines Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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