61 datasets found
  1. o

    Pakistan - Population of Major Cities - Datasets - Open Data Pakistan

    • opendata.com.pk
    Updated Jan 13, 2020
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    (2020). Pakistan - Population of Major Cities - Datasets - Open Data Pakistan [Dataset]. https://opendata.com.pk/dataset/pakistan-population-of-major-cities
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    Dataset updated
    Jan 13, 2020
    Area covered
    Pakistan
    Description

    This provincial level data provides population statistics for major cities of Pakistan.

  2. w

    Dataset of country, population and region of cities in Pakistan

    • workwithdata.com
    Updated Nov 7, 2024
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    Work With Data (2024). Dataset of country, population and region of cities in Pakistan [Dataset]. https://www.workwithdata.com/datasets/cities?col=city%2Ccountry%2Cpopulation%2Cregion&f=1&fcol0=country&fop0=%3D&fval0=Pakistan
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    Dataset updated
    Nov 7, 2024
    Dataset authored and provided by
    Work With Data
    License

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

    Area covered
    Pakistan
    Description

    This dataset is about cities in Pakistan. It has 349 rows. It features 4 columns: country, population, and region.

  3. Pakistan Cities

    • kaggle.com
    Updated Jan 26, 2021
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    Abid Ali Awan (2021). Pakistan Cities [Dataset]. https://www.kaggle.com/datasets/kingabzpro/pakistan-cities
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 26, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Abid Ali Awan
    License

    http://www.gnu.org/licenses/old-licenses/gpl-2.0.en.htmlhttp://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html

    Area covered
    Pakistan
    Description

    Context

    Simple Pakistani Cities Data, with latitude, longitude, population, Province. Below is a list of 146 prominent cities in Pakistan. Each row includes a city's latitude, longitude, province and other variables of interest. This is a subset of all 140,909 places in Pakistan (and only some of the fields) that you'll find in our World Cities Database.

    Source

    https://simplemaps.com/data/pk-cities

  4. Pakistan PK: Urban Population Growth

    • ceicdata.com
    Updated Jun 15, 2021
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    CEICdata.com (2021). Pakistan PK: Urban Population Growth [Dataset]. https://www.ceicdata.com/en/pakistan/population-and-urbanization-statistics/pk-urban-population-growth
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    Dataset updated
    Jun 15, 2021
    Dataset provided by
    CEIC Data
    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, 2006 - Dec 1, 2017
    Area covered
    Pakistan
    Variables measured
    Population
    Description

    Pakistan PK: Urban Population Growth data was reported at 2.526 % in 2017. This records a decrease from the previous number of 2.574 % for 2016. Pakistan PK: Urban Population Growth data is updated yearly, averaging 3.623 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 4.556 % in 1960 and a record low of 2.526 % in 2017. Pakistan PK: Urban Population Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Population and Urbanization Statistics. Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Weighted average;

  5. T

    Pakistan - Urban Population Growth (annual %)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 27, 2017
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    TRADING ECONOMICS (2017). Pakistan - Urban Population Growth (annual %) [Dataset]. https://tradingeconomics.com/pakistan/urban-population-growth-annual-percent-wb-data.html
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    May 27, 2017
    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 1, 1976 - Dec 31, 2025
    Area covered
    Pakistan
    Description

    Urban population growth (annual %) in Pakistan was reported at 2.3603 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Urban population growth (annual %) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

  6. Share of urban population in Pakistan 1960-2023

    • statista.com
    Updated Apr 25, 2014
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    Statista (2014). Share of urban population in Pakistan 1960-2023 [Dataset]. https://www.statista.com/statistics/455907/urbanization-in-pakistan/
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    Dataset updated
    Apr 25, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Pakistan
    Description

    The share of urban population in Pakistan amounted to 38.04 percent in 2023. In a steady upward trend, the share rose by 15.94 percentage points from 1960.

  7. Pakistan PK: Population in Largest City

    • ceicdata.com
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    CEICdata.com, Pakistan PK: Population in Largest City [Dataset]. https://www.ceicdata.com/en/pakistan/population-and-urbanization-statistics/pk-population-in-largest-city
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    Dataset provided by
    CEIC Data
    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, 2006 - Dec 1, 2017
    Area covered
    Pakistan
    Variables measured
    Population
    Description

    Pakistan PK: Population in Largest City data was reported at 15,020,931.000 Person in 2017. This records an increase from the previous number of 14,650,981.000 Person for 2016. Pakistan PK: Population in Largest City data is updated yearly, averaging 6,793,799.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 15,020,931.000 Person in 2017 and a record low of 1,853,325.000 Person in 1960. Pakistan PK: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

  8. H

    Pakistan - Population of Major Cities

    • data.humdata.org
    • data.wu.ac.at
    xls
    Updated Apr 25, 2025
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    OCHA Pakistan (2025). Pakistan - Population of Major Cities [Dataset]. https://data.humdata.org/dataset/f3895383-67ed-4a5d-beaa-b780d643c5df?force_layout=desktop
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    xls(1051136)Available download formats
    Dataset updated
    Apr 25, 2025
    Area covered
    Pakistan
    Description

    Major Cities Population

  9. Pakistan Cities Population Census Dataset

    • kaggle.com
    Updated Jan 24, 2021
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    Asim Zahid (2021). Pakistan Cities Population Census Dataset [Dataset]. https://www.kaggle.com/asimzahid/pakistan-cities-population-census-dataset
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 24, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Asim Zahid
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    Pakistan
    Description

    Dataset

    This dataset was created by Asim Zahid

    Released under CC0: Public Domain

    Contents

  10. Pakistan Census 2017 Data

    • kaggle.com
    Updated Feb 8, 2025
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    Qammar Shahzad (2025). Pakistan Census 2017 Data [Dataset]. http://doi.org/10.34740/kaggle/dsv/10695404
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 8, 2025
    Dataset provided by
    Kaggle
    Authors
    Qammar Shahzad
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    Pakistan
    Description

    This dataset provides detailed statistics from the 2017 census of Pakistan, covering demographic and geographic data for various administrative units across the country. The data includes population counts, sex ratios, population density, urban proportions, and household sizes, among other metrics. It allows for a comprehensive analysis of both rural and urban populations across different regions, including provinces like Punjab, Sindh, Khyber Pakhtunkhwa, Balochistan, and the federal territories.

    Key Features:

    Administrative Unit: The geographical or administrative division, such as Pakistan, rural, urban, and specific regions like provinces or territories. Area (Sq. Km.): The total area of the region in square kilometers. Population (2017): The population count based on the 2017 census. Population (1998): The population count based on the 1998 census, allowing for growth rate analysis. Sex Ratio: The ratio of males to females in the population. Population Density: Number of individuals per square kilometer. Urban Proportion: Percentage of the population living in urban areas. Average Household Size: The average number of individuals living in a household. Potential Use Cases:

    Population growth analysis over the years. Urban vs. rural population studies. Regional demographic trends and comparisons. Analysis of population density and its relation to area size. Understanding household size variations across different regions.

  11. f

    Accessibility: Travel Time-Cost to Major Cities (Pakistan - ~ 500m)

    • data.apps.fao.org
    • data.amerigeoss.org
    Updated Feb 19, 2025
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    (2025). Accessibility: Travel Time-Cost to Major Cities (Pakistan - ~ 500m) [Dataset]. https://data.apps.fao.org/map/catalog/srv/resources/datasets/0090dcf8-8300-4558-8288-d8e48720e773
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    Dataset updated
    Feb 19, 2025
    Area covered
    Pakistan
    Description

    Accessibility to major cities dataset is modelled as raster-based travel time/cost analysis, computed for the 26 largest cities (>250k habitants) in the country. The following cities are included: City - Population Chiniot 278,528 Nawabshah 279,338 Mingora 331,377 Okara 358,146 Kasur 358,296 Mardan 359,024 Wah Cantonment 379,534 Sahiwal 388,795 Gujrat 390,758 Dera Ghazi Khan 397,362 Rahimyar Khan 420,963 Sheikhūpura 473,269 Larkana 488,006 Sukkur 500,401 Sialkot 656,730 Sargodha 658,208 Bahawalpur 762,774 Quetta 999,385 Hyderabad 1,733,622 Multan 1,872,641 Peshawar 1,969,823 Gujranwala 2,028,421 Rawalpindi Islamabad 3,106,827 Faisalabad 3,210,158 Lahore 11,119,985 Karachi 14,884,402 This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (or optimal location).

  12. w

    Pakistan - Complete Country Profile & Statistics 2025

    • worldviewdata.com
    html
    Updated Jul 24, 2025
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    World View Data (2025). Pakistan - Complete Country Profile & Statistics 2025 [Dataset]. https://www.worldviewdata.com/countries/pakistan
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    htmlAvailable download formats
    Dataset updated
    Jul 24, 2025
    Dataset authored and provided by
    World View Data
    License

    https://worldviewdata.com/termshttps://worldviewdata.com/terms

    Time period covered
    2025
    Area covered
    Variables measured
    Area, Population, Literacy Rate, GDP per capita, Life Expectancy, Population Density, Human Development Index, GDP (Gross Domestic Product), Geographic Coordinates (Latitude, Longitude)
    Description

    Comprehensive socio-economic dataset for Pakistan including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

  13. Pakistan PK: Population in Largest City: as % of Urban Population

    • ceicdata.com
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    CEICdata.com, Pakistan PK: Population in Largest City: as % of Urban Population [Dataset]. https://www.ceicdata.com/en/pakistan/population-and-urbanization-statistics/pk-population-in-largest-city-as--of-urban-population
    Explore at:
    Dataset provided by
    CEIC Data
    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, 2006 - Dec 1, 2017
    Area covered
    Pakistan
    Variables measured
    Population
    Description

    Pakistan PK: Population in Largest City: as % of Urban Population data was reported at 20.922 % in 2017. This records a decrease from the previous number of 20.928 % for 2016. Pakistan PK: Population in Largest City: as % of Urban Population data is updated yearly, averaging 21.610 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 23.038 % in 1980 and a record low of 18.670 % in 1960. Pakistan PK: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

  14. w

    Dataset of male population and urban population of countries per year in...

    • workwithdata.com
    Updated Apr 9, 2025
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    Work With Data (2025). Dataset of male population and urban population of countries per year in Pakistan (Historical) [Dataset]. https://www.workwithdata.com/datasets/countries-yearly?col=country%2Cdate%2Cpopulation_male%2Curban_population&f=1&fcol0=country&fop0=%3D&fval0=Pakistan
    Explore at:
    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Work With Data
    License

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

    Area covered
    Pakistan
    Description

    This dataset is about countries per year in Pakistan. It has 64 rows. It features 4 columns: country, male population, and urban population.

  15. Pakistan PK: Urban Population

    • ceicdata.com
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    CEICdata.com, Pakistan PK: Urban Population [Dataset]. https://www.ceicdata.com/en/pakistan/population-and-urbanization-statistics/pk-urban-population
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    Dataset provided by
    CEIC Data
    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, 2006 - Dec 1, 2017
    Area covered
    Pakistan
    Variables measured
    Population
    Description

    Pakistan PK: Urban Population data was reported at 71,796,554.000 Person in 2017. This records an increase from the previous number of 70,005,347.000 Person for 2016. Pakistan PK: Urban Population data is updated yearly, averaging 31,121,090.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 71,796,554.000 Person in 2017 and a record low of 9,926,529.000 Person in 1960. Pakistan PK: Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Population and Urbanization Statistics. Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Sum;

  16. i

    Labour Force Survey 2010-2011 - Pakistan

    • catalog.ihsn.org
    Updated May 31, 2023
    + more versions
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    Federal Bureau of Statistcs (2023). Labour Force Survey 2010-2011 - Pakistan [Dataset]. https://catalog.ihsn.org/catalog/11327
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    Dataset updated
    May 31, 2023
    Dataset authored and provided by
    Federal Bureau of Statistcs
    Time period covered
    2010 - 2011
    Area covered
    Pakistan
    Description

    Abstract

    The major aim of the survey is to collect a set of comprehensive statistics on the various dimensions of country’s civilian labour force as a means to pave the way for skill development, planning, employment generation, assessing the role and importance of the informal sector and, sizing up the volume, characteristics and contours of employment. The broad objectives of the survey are as follows: - To collect data on the socio-demographic characteristics of the total population i.e. age, sex, marital status, level of education, current enrolment and migration etc; - To acquire current information on the dimensions of national labour force; i.e. number of persons employed, unemployed, and underemployed or out of labour market; - To gather descriptive facts on the engagement in major occupational trades and the nature of work undertaken by the institutions/organizations; - To profile statistics on employment status of the individuals, i.e. whether they are employers, own account workers, contributing family workers or paid employees (regular/casual); - To classify non-agricultural enterprises employing household member(s) as formal and informal; - To quantify the hours worked at main/subsidiary occupations; - To provide data on wages and mode of payment for paid employees; - To make an assessment of occupational health and safety of employed persons by causes, type of treatment, conditions that caused the accident/injury and time of recovery; and - To collect data on the characteristics of unemployed persons i.e. age, sex, level of education, previous experience if any, occupation, industry, employment status related to previous job, waiting time invested in the quest for work, their availability for work and expectations for future employment.

    Geographic coverage

    National coverage.

    The survey covers all urban and rural areas of the four provinces of Pakistan defined as such by1998 Population Census, excluding Federally Administered Tribal Areas (FATA) and military restricted areas. The population of excluded areas constitutes about 2% of the total population.

    All sample enumeration blocks in urban areas and mouzas/dehs/villages in rural areas were enumerated except three sample areas (PSUs), due to law & order and recent flood. However, the number of sample households enumerated (36420) is high (equivalent) 99.9% of the total sample size) to the estimated sample size (36464).

    Analysis unit

    • Individual aged 10 years and above
    • Household

    Universe

    The universe for Labour Force Survey consistsed of all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census excluding FATA and military restricted areas. The population of excluded areas constitutes about 2% of the total population. The following groups were also excluded non-settled population, persons living in institutions and foreigners.

    Kind of data

    Sample survey data [ssd]

    Frequency of data collection

    Quarterly.

    Sampling procedure

    Sample Design: A stratified two-stage sample design is adopted for the survey.

    Sampling Frame: Federal Bureau of Statistics (FBS) has developed its own sampling frame for urban areas. Each city/town is divided into enumeration blocks. Each enumeration block is comprised of 200 to 250 households on the average with well-defined boundaries and maps. The list of enumeration blocks as updated through Economic Census 2003 and the list of villages/mouzas/dehs of 1998 Population Census are taken as sampling frames. Enumeration blocks & villages are considered as Primary Sampling Units (PSUs) for urban and rural domains respectively.

    Stratification Plan - Urban Domain: Large cities Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad are considered as large cities. Each of these cities constitutes a separate stratum, further sub-stratified according to low, middle and high income groups based on the information collected in respect of each enumeration block at the time of demarcation/ updating of urban area sampling frame.

    • Remaining Urban Areas: In all the four provinces after excluding the population of large cities from the population of an administrative division, the remaining urban population is grouped together to form a stratum.

    • Rural Domain: Each administrative district in the Punjab, Sindh and Khyber Pakhtunkhwa (KP) is considered an independent stratum whereas in Balochistan, each administrative division constitutes a stratum.

    • Selection of primary sampling units (PSUs): Enumeration blocks in urban domain and mouzas/dehs/villages in rural are taken as Primary Sampling Units (PSUs). In the urban domain, sample PSUs from each ultimate stratum/sub-stratum are selected with probability proportional to size (PPS) method of sampling scheme. In urban domain, the number of households in an enumeration block as updated through Economic Census 2003 and village population of 1998 Census for rural domain is considered as measure of size.

    • Selection of secondary sampling units (SSUs): The listed households of sample PSUs are taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 12 from each urban sample PSU, 16 from rural sample PSU are selected with equal probability using systematic sampling technique with a random start.

    • Sample Size and Its Allocation: A sample of 36,464 households is considered appropriate to provide reliable estimates of key labour force characteristics at National/Provincial level. The entire sample of households (SSUs) is drawn from 2580 Primary Sampling Units (PSUs) out of which 1204 are urban and 1376 are rural. The overall sample has been distributed evenly over four quarters independently. As urban population is more heterogeneous therefore, a higher proportion of sample size is allocated to urban domain. To produce reliable estimates, a higher proportion of sample is assigned to Khyber Pk and Balochistan in consideration to their smallness. After fixing the sample size at provincial level, further distribution of sample PSUs to different strata in rural and urban domains in each province is made proportionately.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Structured questionnaire.

    Cleaning operations

    Editing and coding is done at headquarter by the subject matter section. Computer edit checks are applied to get even with errors identified at the stage of data entry. The relevant numerical techniques are used to eliminate erroneous data resulting from mistakes made during coding. The survey records are further edited and rectified through a series of computer processing stages.

    Response rate

    99.9%

    Data appraisal

    Notwithstanding complete observance of the requisite codes to ensure reliability of data, co-efficient of variations, computed in the backdrop of 5% margin of error exercised for determining sample size, are also given below to affirm the reliability of estimates.

  17. i

    Time Use Survey 2007 - Pakistan

    • dev.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Apr 25, 2019
    + more versions
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    Federal Bureau of Statistics (2019). Time Use Survey 2007 - Pakistan [Dataset]. https://dev.ihsn.org/nada/catalog/study/PAK_2007_TUS_v01_M
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    Dataset updated
    Apr 25, 2019
    Dataset authored and provided by
    Federal Bureau of Statistics
    Time period covered
    2007
    Area covered
    Pakistan
    Description

    Abstract

    A primary objective of the national Time Use Survey in Pakistan is to account for the 24 hours time in term of the full spectrum of activities carried out during the duration. The objectives of the survey are specified as under:- - To profile the quantum and distribution of paid/unpaid work as a means to infer policy/programme implications from the perspective of gender equity. - To collect and analyze the time use pattern of the individuals in order to help draw inferences for employment and welfare programmes. - To collect and analyze the comprehensive information about the time spent by people on marketed and non-marketed economic activities covered under the 1993-SNA, non-marketed non-SNA activities within the General Production Boundary and personal care and related activities that cannot be delegated to others. - To use the data in generating more reliable estimates on work force.

    Geographic coverage

    The survey covers all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census excluding Federally Administered Tribal Areas (FATA) and certain administrative areas of NWFP. The population of geographic areas excluded from the survey constitutes about 2 percent of the total population as enumerated in 1998 Population Census. The population excluded is located in difficult terrain and its enumeration through personal interview is not possible within the given constraints of time, access and cost.

    Analysis unit

    Households Individuals

    Universe

    The universe consists of all urban and rural areas of the four provinces of Pakistan, defined as such by Population Census 1998, excluding FATA & Military Restricted Areas. The population of excluded area constitutes about 3% of the total population and is located in different terrain.

    Sampling procedure

    Sampling Frame Federal Bureau of Statistics has developed its own sampling frame for all urban areas of the country. Each city/town has been divided into a number of enumeration blocks. Each enumeration block consists of 200-250 households on the average with well-defined boundaries and maps. The sampling frame i.e. lists of enumeration blocks as up-dated through Economic Census 2003-04 and the lists of villages/mouzas/dehs published by Population Census Organization as a result of 1998 Population Census have been taken as sampling frame. Enumeration blocks and villages are considered as primary sampling unites (PSUs) for urban and rural domain respectively.

    Stratification a) Urban Domain i) Large Sized Cities Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawapur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad are considered as large sized cities. Each of these cities constitutes a separate stratum which is further sub-stratified according to low, middle, high income groups based on the information collected in respect of each enumeration block at the time of demarcation/up-dating of urban area sampling frame. ii) Remaining urban areas After excluding the population of large sized cities from the population of respective administrative division, the remaining urban population of administrative division of four provinces is grouped together to form a stratum called other urban. Thus ex-division in remaining urban areas in the four provinces constitutes a stratum. b) Rural Domain In rural domain, each administrative district in the Punjab, Sindh and NWF Provinces is considered as independent and explicit stratum whereas, in Balochistan, each administrative division constitutes a stratum.

    Sample size and its Allocation Keeping in view the resources available, a sample size of 19600 sample households has been considered appropriate to provide estimates of key characteristics at the desired level. The entire sample of households (SSUs) has been drawn from 1388 Primary Sampling Units (PSUs) out of which 652 are urban and 736 are rural. In order to control seasonal variation etc. sample has been distributed evenly over four quarters. This has facilitated to capture the variation due to any seasonal activity as urban population is more heterogeneous therefore, a higher proportion of sample size has been allocated to urban domain. Similarly NWFP and Balochistan being the smaller province, have been assigned higher proportion of sample in order to get reliable estimates. After fixing the sample size at provincial level, further distribution of sample PSUs to different strata in rural and urban domains in each province has been made proportionately.

    Sample Design A three-stage stratified sample design has been adopted for the survey. Sample Selection Procedure a) Selection of Primary Sampling Unites (PSUs) Enumeration blocks in urban domain and mouzas/dehs/villages in rural domain are taken as primary sampling unites (PSUs). In the urban domain, sample PSUs from each ultimate stratum/sub-stratum is selected with probability proportional to size (PPS) method of sampling scheme. In urban domain, the number of households in enumeration block as up-dated through Economic Census 2003-04 and population of 1998 Census for each village/mouza/deh are considered as measure of size. b) Section of Secondary Sampling Units (SSUs) Households within sample PSUs are taken as secondary sampling unites (SSUs). A specified number of households i.e. 12 from each urban sample PSU and 16 from each rural sample PSU are selected with equal probability using systematic sampling technique with a random start. Different households are selected in each quarter. c) Selection of Third Stage Sampling Units i.e. Individuals/Persons (TSUs) From the sample households, individuals/persons aged 10+ years within each sample households (SSUs) have been taken as third stage sampling units (TSUs). Two individuals aged 10 years and above among the eligible individuals/persons from each sample household have been interviewed using a selection grid.The grid and selection steps are detailed on p13 of the survey report available under external resources.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaire has been framed in the light of contemporary precedents and practices in vogue in the developing countries. The recommendations of Gender Responsive Budgeting Initiatives (GRBI) expert who visited Pakistan in June 2006 have been taken into account. Further, the advice of local experts hailing both from data producing and using agencies has also been considered. Survey Questionnaire and Manual of Instructions, for the Supervisors & Enumerators, was finalized jointly by Federal Bureau of Statistics and GRBI Project staff. The questionnaire was also pre-tested and reviewed accordingly. The questionnaire adopted for the survey is given at Annexure-A. All the households selected in the sample stand interviewed. Diary part of the questionnaire is filled-in from two respondents selected from each of the enumerated households. The questionnaire consists of the following six parts. Section-1: Identification of the area, respondents, detail of field visits and staff entrusted with supervision, editing and coding. Section-2: Detailed information about the socio-economic and demographic particulars of the selected households and individuals. Some of the important household characteristics i.e. ownership status and type of the household, earthquake damage, household items, sources of energy, drinking water, transport, health & education facilities, sources of income, monthly income, age and sex composition of the population. Section-3: Demographic detail such as age, sex, marital status, educational level, having children, employment status, source of income etc. of the selected respondent of that household Section-4: Comprised of diary to record the activities performed by the first selected respondent through the 24 hours period between 4.00 a.m. of the day preceding the day of interview and 3.00 a.m. on the day of the interview. Section-5 and 6 pertain to the second selected respondent of the selected household. The diary which is the core instrument of the time use study is divided into forty eight half-hour slots. An open ended question about the activities performed during the thirty minutes was asked from the respondent. Provision for minimum of recording three activities through half hour slot was made. In case of reporting more than one activity, the respondent was probed whether these activities were carried out simultaneously or one after the other. Similarly, the two locations of performing the activities were also investigated in the diary part of the questionnaire. The activities recorded in the diary are then coded by the field enumerator according to the activity classification given at Annex-B.

    Cleaning operations

    Soon after data collection, the field supervisors manually clean, edit and check the filled in questionnaire and refer back to field where necessary. This does not take much time since most of the manual editing is done in the field. Further editing is done by the subject matter section at the Headquarter. Also during data entry, further editing of error identified by applying computer edit checks is done. In edit checks, data ranges in numerical values are used to eliminate erroneous data as a result of mistakes made during coding. Thus, the survey records are edited and corrected through a series of computer processing stages.

  18. Pakistan PK: Urban Population: % of Total Population

    • ceicdata.com
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    CEICdata.com, Pakistan PK: Urban Population: % of Total Population [Dataset]. https://www.ceicdata.com/en/pakistan/population-and-urbanization-statistics/pk-urban-population--of-total-population
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    Dataset provided by
    CEIC Data
    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, 2006 - Dec 1, 2017
    Area covered
    Pakistan
    Variables measured
    Population
    Description

    Pakistan PK: Urban Population: % of Total Population data was reported at 39.700 % in 2017. This records an increase from the previous number of 39.224 % for 2016. Pakistan PK: Urban Population: % of Total Population data is updated yearly, averaging 30.203 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 39.700 % in 2017 and a record low of 22.104 % in 1960. Pakistan PK: Urban Population: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank: Population and Urbanization Statistics. Urban population refers to people living in urban areas as defined by national statistical offices. The data are collected and smoothed by United Nations Population Division.; ; United Nations Population Division. World Urbanization Prospects: 2014 Revision.; Weighted average;

  19. Pakistan - Demographic, Health, Education and Transport indicators

    • cloud.csiss.gmu.edu
    • data.amerigeoss.org
    • +1more
    csv
    Updated Jun 18, 2019
    + more versions
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    UN Humanitarian Data Exchange (2019). Pakistan - Demographic, Health, Education and Transport indicators [Dataset]. https://cloud.csiss.gmu.edu/uddi/ko_KR/dataset/unhabitat-pk-indicators
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    csv(67236)Available download formats
    Dataset updated
    Jun 18, 2019
    Dataset provided by
    United Nationshttp://un.org/
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    Pakistan
    Description

    The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.

  20. Pakistan Population: Urban

    • ceicdata.com
    Updated Jun 15, 2021
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    CEICdata.com (2021). Pakistan Population: Urban [Dataset]. https://www.ceicdata.com/en/pakistan/population/population-urban
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    Dataset updated
    Jun 15, 2021
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Jun 1, 2006 - Jun 1, 2017
    Area covered
    Pakistan
    Variables measured
    Population
    Description

    Pakistan Population: Urban data was reported at 75.580 Person mn in 2017. This records a decrease from the previous number of 77.930 Person mn for 2016. Pakistan Population: Urban data is updated yearly, averaging 50.450 Person mn from Jun 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 77.930 Person mn in 2016 and a record low of 28.290 Person mn in 1994. Pakistan Population: Urban data remains active status in CEIC and is reported by Ministry of Planning, Development & Reforms. The data is categorized under Global Database’s Pakistan – Table PK.G001: Population. The survey covers all of the four provinces of Pakistan defined as such 1998 Population Census, including Federally Administered Tribal Areas (FATA) and military restricted areas. The population of FATA and military restricted areas constitutes about 2% of the total population. Population statistics for 1981 and1998 are from Censuses. Population Censuses were conducted in March 1981 and 1998.

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(2020). Pakistan - Population of Major Cities - Datasets - Open Data Pakistan [Dataset]. https://opendata.com.pk/dataset/pakistan-population-of-major-cities

Pakistan - Population of Major Cities - Datasets - Open Data Pakistan

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Dataset updated
Jan 13, 2020
Area covered
Pakistan
Description

This provincial level data provides population statistics for major cities of Pakistan.

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