Every year, many people migrate to different countries from Pakistan, and a lot of them migrate to Pakistan as emigrants of refugees. Pakistan ranks 2nd, according to UNHCR, among the countries to host the most refugees. Thus this is a tribute to Pakistan and information to the world that Pakistan is quite different than you think!

About the Dataset: Pharmaceutical Products Pricing and Availability Data in Pakistan

This dataset contains information about pharmaceutical product pricing and availability in Pakistan. The data was collected from various sources and compiled into a structured format for analysis. The dataset consists of 1630 entries with 7 columns, including:

Name: The name of the pharmaceutical product. Company: The company manufacturing or distributing the product. Price_before: The product's price before any discount is applied. Discount: The discount offered on the product, if applicable. Price_After: The price of the product after applying any discount. Pack_Size: The size or quantity of the product's packaging. Availability: The availability status of the product.

The dataset provides insights into the pricing trends and availability of pharmaceutical products in Pakistan, which can be valuable for various stakeholders including consumers, healthcare professionals, and policymakers. It can be used for analysis, research, and decision-making in the pharmaceutical industry.

Data Overview: Entries: 1630 Missing Values: Some columns have missing values, such as 'Name', 'Company', 'Price_before', 'Discount', 'Price_After', 'Pack_Size', and 'Availability'. Data Types: The dataset consists of object types for textual data and one float type for numerical data.

Potential Uses: This dataset can be used for a variety of purposes, including:

• Analyzing pricing trends and patterns of different drugs in Pakistan.
• Studying the affordability and accessibility of essential medicines in Pakistan.
• Tracking the performance of different pharmaceutical companies in the Pakistani market.
• Identifying potential areas for improving access to affordable medicines in Pakistan.

Limitations: It is important to note that this dataset only includes data on the maximum retail prices of pharmaceutical products. The actual price consumers pay may vary depending on the pharmacy and other factors. Additionally, the dataset does not include information on the quality of the pharmaceutical products.

I hope this description is helpful!

Context: The 2019–20 coronavirus pandemic was confirmed to have reached Pakistan on 26 February 2020, when a student in Karachi tested positive upon returning from Iran. By 18 March, cases had been registered in all four provinces, the two autonomous territories, and the federal territory of Islamabad. The dataset is completely acquired from NIH Publications, Governmental resources and extra mile contacts. The dataset reflects at provincial level and details from all the aspects. Complete details can be visualized at hyperurl.co/pakcovid Content: The dataset contains chronological seven tabs and 80+ columns with data ranging from Suspected Cases Last Date Suspected Cases Last 24 Hrs Suspected Cases Cumulative Lab Tests Last 24 Hrs Lab Tests Cumulative Confirmed Cases Last Date Confirmed Cases Last 24 Hrs Confirmed Cases Cumulative Deaths Last Date Deaths Last 24 Hrs Deaths Cumulative Transmission Total Transmission Foreign - Iran Transmission Foreign - Iran % Transmission Foreign - Other Transmission Foreign - Other % Transmission Local - Tableegh Transmission Local % - Tableegh Transmission Local - Others Transmission Local % - Others Transmission Local Transmission Local % Total Hospitals Beds for COVID Total Admitted Admitted Stable Admitted Critical Admitted Ventilator Home Quarantine Recovered Death Quarantine Facilities Last 24 Hrs Arrival Last 24 Hrs (Location) Last 24 Hrs Departure Cumulative Quarantined Number of Tests Results Achieved Test Positive Cases Test Positive Cases % Confirmed HW - Active Doctors Confirmed HW - Active Nurses Confirmed HW - Active Others Confirmed HW - Active Total Confirmed HW - Active Isolation Confirmed HW - Active Hospital Confirmed HW - Active Hospital Stable Confirmed HW - Active Hospital Ventilator Confirmed HW - Active Recovered Confirmed HW - Active Deaths all at provincial level The first version has the data from first case of February 26 2020 to April 19, 2020. We intend to publish weekly updates Data Source: National Institute of Health website Daily publication Processed via Python Camelot Package. Visit https://github.com/MesumRaza for details on scripting. Acknowledgements: Users are allowed to use, copy, distribute and cite the dataset as follows: “Mesum Raza Hemani, Corona Virus Pakistan Dataset 2020, Kaggle Dataset Repository”

The objective of GEO is to fulfil a vision of a world where decisions and actions are informed by coordinated, comprehensive and sustained Earth Observation (EO). This is being pursued mainly through the added value of co-ordinating existing institutions, organised communities, space agencies, in-situ monitoring agencies, scientific institutions, research centres, universities, modelling centres, technology developers and other groups that deal with one or more aspects of EO. To reach this overarching goal, GEO focuses on capacity development in three dimensions: infrastructure, individuals and institutions. In the field of agriculture, the general goal is to promote the utilization of Earth observations for advancing sustainable agriculture, aquaculture and fisheries. Key issues include early warning, risk assessment, food security, market efficiency and combating desertification. (Source: http://www.research-europe.com/index.php/2011/08/joao-soares-secretariat-expert-for-agriculture-group-on-earth-observations/)

Money Supply M2 in Pakistan increased to 41409456 PKR Million in October from 41372563 PKR Million in September of 2025. This dataset provides - Pakistan Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The total population in Pakistan was estimated at 251.3 million people in 2024, according to the latest census figures and projections from Trading Economics. This dataset provides - Pakistan Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Supreme Court of Pakistan Judgments DatasetThis dataset contains almost 1200 judgments made by the Supreme Court of Pakistan up to May 2025.This dataset includes the judgments made by

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.

Pakistan: Government spending, billion USD: The latest value from 2024 is 31.71 billion U.S. dollars, a decline from 34.83 billion U.S. dollars in 2023. In comparison, the world average is 78.89 billion U.S. dollars, based on data from 100 countries. Historically, the average for Pakistan from 1960 to 2024 is 11.54 billion U.S. dollars. The minimum value, 0.38 billion U.S. dollars, was reached in 1960 while the maximum of 39.33 billion U.S. dollars was recorded in 2022.

Graph and download economic data for World Uncertainty Index for Pakistan (WUIPAK) from Q1 1952 to Q3 2025 about Pakistan, uncertainty, World, and indexes.

Pakistan: Government accountability: The latest value from 2024 is 0.183 index points, a decline from 0.316 index points in 2023. In comparison, the world average is 0.532 index points, based on data from 170 countries. Historically, the average for Pakistan from 1960 to 2024 is 0.062 index points. The minimum value, -0.722 index points, was reached in 1979 while the maximum of 0.657 index points was recorded in 2013.

Weather Forecast Dataset for Major Cities in Pakistan

Dataset Overview

This dataset provides comprehensive weather forecast information for various major cities in Pakistan, recorded at three-hour intervals on June 15, 2024. The data covers a wide range of atmospheric and weather conditions and includes multiple meteorological parameters essential for understanding weather patterns across different regions in Pakistan. This dataset is valuable for data analysis, machine learning models, and meteorological research.

Data Fields

The dataset includes the following fields:

• pres: Atmospheric pressure (mb).
• clouds: Cloud cover percentage.
• vis: Visibility in miles.
• wind_spd: Wind speed (m/s).
• wind_cdir_full: Full cardinal direction of the wind.
• slp: Sea level pressure (mb).
• datetime: Date and time in local format.
• ts: Unix timestamp.
• snow: Snowfall amount (mm).
• timestamp_utc: Timestamp in UTC format.
• uv: UV index.
• timestamp_local: Timestamp in local format.
• wind_dir: Wind direction (degrees).
• pop: Probability of precipitation (%).
• ghi: Global horizontal irradiance (W/m²).
• clouds_hi: High cloud cover percentage.
• precip: Precipitation amount (mm).
• temp: Temperature (°F).
• app_temp: Apparent temperature or 'feels like' temperature (°F).
• snow_depth: Snow depth (mm).
• dni: Direct normal irradiance (W/m²).
• wind_gust_spd: Wind gust speed (m/s).
• dewpt: Dew point temperature (°F).
• dhi: Diffuse horizontal irradiance (W/m²).
• solar_rad: Solar radiation (W/m²).
• clouds_low: Low cloud cover percentage.
• clouds_mid: Mid-level cloud cover percentage.
• ozone: Ozone levels (Dobson units).
• wind_cdir: Cardinal direction of the wind.
• rh: Relative humidity (%).
• pod: Part of the day (d: day, n: night).
• description: Text description of the weather.
• code: Weather condition code.
• icon: Weather icon code.
• city: Name of the city.
• country: Name of the country.
• lon: Longitude of the city's location.
• lat: Latitude of the city's location.

Usage

This dataset is ideal for:

• Weather prediction models.
• Time-series analysis.
• Understanding climatic conditions across different cities.
• Environmental research.
• Educational purposes in meteorology and data science.

Data Source

The data is sourced from the Weatherbit API, a reliable provider of accurate and up-to-date weather information. The dataset represents a snapshot of weather conditions for major cities in Pakistan, offering granular data for detailed analysis.

Monthly and long-term Pakistan Current Account data: historical series and analyst forecasts curated by FocusEconomics.

Konsumsi Publik:% dari PDB Pakistan dilaporkan sebesar 9.5 % pada 2025. Rekor ini naik dibanding sebelumnya yaitu 8.9 % untuk 2024. Data Konsumsi Publik:% dari PDB Pakistan diperbarui tahunan, dengan rata-rata 12.8 % dari 1960 sampai 2025, dengan 66 observasi. Data ini mencapai angka tertinggi sebesar 16.8 % pada 1989 dan rekor terendah sebesar 8.7 % pada 2001. Data Konsumsi Publik:% dari PDB Pakistan tetap berstatus aktif di CEIC dan dilaporkan oleh CEIC Data. Data dikategorikan dalam Global Economic Monitor World Trend Plus – Table: Government Consumption: % of Nominal GDP: Annual.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata. DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted. REGION: Africa SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743. FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available. Pakistan data available from WorldPop here.

Tingkat Pengangguran Pakistan dilaporkan sebesar 6.90 % pada 2025. Rekor ini naik dibanding sebelumnya yaitu 6.30 % untuk 2021. Data Tingkat Pengangguran Pakistan diperbarui tahunan, dengan rata-rata 5.89 % dari 1980 sampai 2025, dengan 40 observasi. Data ini mencapai angka tertinggi sebesar 8.27 % pada 2003 dan rekor terendah sebesar 3.04 % pada 1986. Data Tingkat Pengangguran Pakistan tetap berstatus aktif di CEIC dan dilaporkan oleh Pakistan Bureau of Statistics. Data dikategorikan dalam Pakistan Global Database – Table PK.G: Labour Force Survey: Population, Labour Force, Employment and Unemployment.

Key information about Pakistan Number of Subscriber Fixed Line

• Pakistan Number of Subscriber Fixed Line was reported at 2,573,430.000 Unit in Dec 2023
• This records a decrease from the previous number of 2,580,350.000 Unit for Dec 2022
• Pakistan Number of Subscriber Fixed Line data is updated yearly, averaging 1,116,113.000 Unit from Dec 1960 to 2023, with 64 observations
• The data reached an all-time high of 6,370,860.000 Unit in 2013 and a record low of 66,776.000 Unit in 1964
• Pakistan Number of Subscriber Fixed Line data remains active status in CEIC and is reported by World Bank
• The data is categorized under World Trend Plus’s Association: Telecommunication Sector – Table PK.World Bank.WDI: Telecommunication

Fixed telephone subscriptions refers to the sum of active number of analogue fixed telephone lines, voice-over-IP (VoIP) subscriptions, fixed wireless local loop (WLL) subscriptions, ISDN voice-channel equivalents and fixed public payphones.;World Telecommunication/ICT Indicators Database, International Telecommunication Union (ITU);Sum;

Access Pakistan trade data with updated export-import records. Discover major products, top buyers and suppliers, HS codes, and real-time shipment data.

Pakistan Stock Symbols & Company Metadata

This dataset contains stock symbols and basic company metadata for all listed companies in Pakistan.It is updated weekly if new changes are there.

  📊 Dataset Contents

The dataset is provided as a CSV file with the following columns:

Column Description

name Full company name

ticker Stock ticker symbol (e.g., AAPL, MSFT)

market The exchange/market where the stock is listed

sector The primary business sector of the… See the full description on the dataset page: https://huggingface.co/datasets/ThunderDrag/Pakistan-Stock-Symbols-and-Metadata.