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It contains latitudes and longitudes ,population of major cities of India.
https://simplemaps.com/data/in-cities
I wanted to create interactive maps for one of my project so i created this dataset.
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Dataset Card for Dataset Name
Includes Images for different Indian Cities.
Dataset Details
Each city has 2500 images
Dataset Description
This dataset contains 2500 images per Cities of popular indian Cities, City included are Ahmendabad, Mumbai, Delhi, Koklakta and A state Kerala.
Curated by: Divax Shah and Team
Dataset Sources
Demo: here
arXiv : https://arxiv.org/abs/2403.10912
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The dataset contains air quality information for various cities across India. It includes parameters such as Air Quality Index (AQI), concentrations of particulate matter (PM2.5 and PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), as well as geographical coordinates and time stamps. This dataset enables analysis and comparison of air quality levels among different cities, aiding in understanding environmental health impacts and informing policy decisions.
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Population in the largest city (% of urban population) in India was reported at 6.3201 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
The dataset contains daily temperature for four major cities in India namely : Kolkata , Mumbai , Chennai , Delhi .
The dataset has been curated from : academic.udayton.edu The blanks or not available data has been marked : na
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Population in largest city in India was reported at 33807403 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.
Delhi was the largest city in terms of number of inhabitants in India in 2023.The capital city was estimated to house nearly 33 million people, with Mumbai ranking second that year. India's population estimate was 1.4 billion, ahead of China that same year.
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This horizontal bar chart displays male population (people) by capital city using the aggregation sum in India. The data is about countries per year.
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Context
The dataset tabulates the median household income in Indian Village. It can be utilized to understand the trend in median household income and to analyze the income distribution in Indian Village by household type, size, and across various income brackets.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of Indian Village median household income. You can refer the same here
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Graph and download economic data for Geographical Outreach: Number of Automated Teller Machines (ATMs) in 3 Largest Cities for India (INDFCACLNUM) from 2007 to 2015 about ATM, India, banks, and depository institutions.
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Analysis of âSwiggy Restaurants Dataset of Metro Citiesâ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/aniruddhapa/swiggy-restaurants-dataset-of-metro-cities on 28 January 2022.
--- Dataset description provided by original source is as follows ---
This dataset contains swiggy registered restaurants details of major metropoliton cities of India. I have considered only metropoliton cities with population 4.5 million. As per the Census of India 2011 definition of more than 4 million population, some of the major Metropolitan Cities in India are:
Mumbai (more than 18 Million) Delhi (more than 16 Million) Kolkata (more than 14 Million) Chennai (more than 8.6 million) Bangalore (around 8.5 million) Hyderabad (around 7.6 million) Ahmedabad (around 6.3 million) Pune (around 5.05 million) Surat (around 4.5 million)
I have scrapped the data using python. It may not have all the restaurants of a particular city because if during webscrapping any restaurant has not enabled swiggy as their delivery partner, that restaurant's details will not be scrapped. Though I have scrapped same cities multiple times, to include maximum restaurant details. The data is collected on 12th Jan 2022.
Thank you swiggy for the dataset.
Your data will be in front of the world's largest data science community. What questions do you want to see answered?
--- Original source retains full ownership of the source dataset ---
With over 17 million businesses, all held in-house, BoldData has the largest supply of Indian data. We can select your perfect target based on numerous interesting selections: from 3,000 industries to region, turnover, sector, contact person and the number of employees.
Other questions or are you looking for another city or country? Our data experts are specialized in supervising international campaigns. We have specific direct marketing knowledge per country and have highly accurate data of 300 million companies in 150+ countries. Contact us for free tailor-made advice and an independent quote.
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The global smart city market size was estimated at $500 billion in 2023 and is projected to reach $3 trillion by 2032, growing at a compound annual growth rate (CAGR) of 23%. This remarkable growth is driven by rapid urbanization, technological advancements, and increasing government initiatives aimed at sustainable development. The convergence of IoT, AI, and data analytics is playing a pivotal role in transforming urban landscapes into interconnected, efficient ecosystems.
One of the primary growth factors of the smart city market is the accelerated pace of urbanization. With more than half of the worldâs population now residing in urban areas, cities face increasing pressure to improve infrastructure and services. Smart city technologies offer solutions for efficient resource management, enhanced public safety, and improved quality of life. The need for effective urban planning and sustainable development is pushing governments to adopt smart city initiatives at an unprecedented rate.
Advancements in technology, particularly in IoT, AI, and big data, are significantly contributing to the smart city market's expansion. IoT sensors and devices facilitate real-time data collection, enabling cities to monitor and manage resources such as water, electricity, and waste more efficiently. AI and data analytics are used to interpret this data, providing actionable insights that help in optimizing urban operations, reducing costs, and enhancing citizen services. The integration of these technologies is creating a symbiotic relationship between the digital and physical worlds, driving the evolution of smart cities.
Government support and initiatives are also major catalysts for the growth of the smart city market. Various governments around the world are investing heavily in smart city projects to address urban challenges such as traffic congestion, pollution, and energy consumption. For instance, the European Union has earmarked substantial funding for smart city projects under its Horizon 2020 program. Similarly, countries like China and India have launched extensive smart city missions aimed at transforming urban areas into technologically advanced, sustainable habitats.
Regionally, North America and Europe are leading the smart city market, owing to their advanced technological infrastructure and significant government investments. However, Asia Pacific is expected to exhibit the highest growth rate during the forecast period. Rapid urbanization, coupled with increasing government initiatives in countries like China, India, and Japan, is driving the smart city market in this region. Latin America and the Middle East & Africa are also showing promising growth, supported by improving economic conditions and increasing focus on sustainable development.
The smart city market is segmented into three primary components: hardware, software, and services. Each of these components plays a crucial role in enabling and enhancing the various functionalities of a smart city. Hardware components include sensors, smart meters, and communication devices, among others. These devices are essential for collecting real-time data from various urban environments, which is then used to monitor and manage city operations.
Software solutions are integral to the smart city market as they provide the platforms and applications needed to analyze and interpret the data collected by hardware devices. These software solutions enable various functions such as traffic management, energy management, and public safety. They also offer predictive analytics capabilities, which help city administrators anticipate and mitigate potential issues before they escalate. The increasing complexity and volume of data generated by smart cities necessitate robust software solutions to manage and analyze this data effectively.
Services are another critical component of the smart city market. These include consulting services, system integration, and managed services, which are essential for the successful implementation and operation of smart city projects. Consulting services help cities identify their specific needs and design customized smart city solutions. System integration services ensure that various hardware and software components work seamlessly together, while managed services provide ongoing support and maintenance to ensure the smooth functioning of smart city systems.
The hardware segment is expected to account for a significant share of the smart city market, driv
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The datasets contains date- and state-wise historically compiled data on air quality (by pollution level) in rural and urban areas of India from the year 2015 , as measured by Central Pollution Board (CPCB) through its daily (24 hourly measurements, taken at 4 PM everyday) Air Quality Index (AQI) reports.
The CPCB measures air quality by continuous online monitoring of various pollutants such as Particulate Matter10 (PM10), Particulate Matter2.5 (PM2.5), Sulphur Dioxide (SO2), Nitrogen Oxide or Oxides of Nitrogen (NO2), Ozone (O3), Carbon Monoxide (CO), Ammonic (NH3) and Lead (Pb) and calculating their level of pollution in the ambient air. Based on the each pollutant load in the air and their associated health impacts, the CPCB calculates the overall Air Pollution in Air Quality Index (AQI) value and publishes the data. This AQI data is then used by CPCB to report the air quality status i.e good, satisfactory, moderate, poor, very poor and severe, etc. of a particular location and their related health impacts because of air pollution.
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This dataset and codebook correspond to the second round of survey data gathered in Delhi and Mumbai (India) in 2024, within the project FULFILL - Fundamental Decarbonisation Through Sufficiency By Lifestyle Changes.
As part of Work Package 3 (WP3) in the FULFILL project, we collected quantitative data from six countries: Denmark, France, Germany, Italy, Latvia, and India. The first round of the survey, consisted of recruiting a representative sample of approximately 2000 households in each country. In this second survey round, we recruit around 500 respondents from the initial survey round, ensuring representativity is maintained.
In order to consider sufficiency-oriented lifestyles not only in Europe but also in the Global South, we conducted a similar survey in India. More specifically, we adjusted the survey to fit the context (e.g., including cooling) and, due to the large size and diversity within India, we focused data collection on two Mega Cities (>10Mio inhabitants), namely Mumbai and Delhi. Due to the different cultural context and in exchange with Indian researchers and the supporting market research institute, we decided to change the methodology for data collection from an online survey to face-to-face interviews. The survey includes a quantitative assessment of the carbon footprint in various domains of life, such as housing, mobility, and diet. In addition to this, the survey also measures socio-economic factors such as age, gender, income, education, household size, life stage, and political orientation. Furthermore, the survey includes measures of quality of life, encompassing aspects such as health and well-being, environmental quality, financial security, and comfort.
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Analysis of âDaily Air Pollution Data - India & USAâ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/sumandey/daily-air-quality-dataset-india on 28 January 2022.
--- Dataset description provided by original source is as follows ---
Air Pollution is a major health concern of many. However, the COVID-19 pandemic might have some role to play in bringing some changes to the overall quality of air.
The dataset consists of pm2.5 measurements from Jan 2019 to May 2021 of the Major Cities of India & the United States. You also need to understand how pm2.5 classifies Air Quality.
Special thanks go to https://aqicn.org for making the data open-source and use it for research purposes.
This data could be used to answer several questions -
You are open to coming up with your own analysis as well.
--- Original source retains full ownership of the source dataset ---
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It is estimated that more than 8 billion people live on Earth and the population is likely to hit more than 9 billion by 2050. Approximately 55 percent of Earthâs human population currently live in areas classified as urban. That number is expected to grow by 2050 to 68 percent, according to the United Nations (UN).The largest cities in the world include TĆkyĆ, Japan; New Delhi, India; Shanghai, China; MĂ©xico City, Mexico; and SĂŁo Paulo, Brazil. Each of these cities classifies as a megacity, a city with more than 10 million people. The UN estimates the world will have 43 megacities by 2030.Most cities' populations are growing as people move in for greater economic, educational, and healthcare opportunities. But not all cities are expanding. Those cities whose populations are declining may be experiencing declining fertility rates (the number of births is lower than the number of deaths), shrinking economies, emigration, or have experienced a natural disaster that resulted in fatalities or forced people to leave the region.This Global Cities map layer contains data published in 2018 by the Population Division of the United Nations Department of Economic and Social Affairs (UN DESA). It shows urban agglomerations. The UN DESA defines an urban agglomeration as a continuous area where population is classified at urban levels (by the country in which the city resides) regardless of what local government systems manage the area. Since not all places record data the same way, some populations may be calculated using the city population as defined by its boundary and the metropolitan area. If a reliable estimate for the urban agglomeration was unable to be determined, the population of the city or metropolitan area is used.Data Citation: United Nations Department of Economic and Social Affairs. World Urbanization Prospects: The 2018 Revision. Statistical Papers - United Nations (ser. A), Population and Vital Statistics Report, 2019, https://doi.org/10.18356/b9e995fe-en.
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This horizontal bar chart displays urban population (people) by capital city using the aggregation sum in India. The data is about countries per year.
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India is in the state of the nationwide lockdown to combat the prevalent monotonically rising COVID-19 cases. We all know that every country is being affected by the outbreak of COVID-19. This dataset was created to understand study pollution in major places of India during this period (1 March - 20 April).
OpenAQ is the world's first open, real-time and historical air quality platform, aggregating government-measured and research-grade data - entirely open-source. OpenAQ API was used for the purpose of extracting the pollution data. It provides an API to extract concentration of pollutants (CO, NO2, SO2, O3, PM10 & PM2.5) in 119 places in India. We extracted the pollution data for the interval of (1 March - 20 April 2020) of major cities that are considered.
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Background: Particulate matter (PM) is one among the crucial air pollutants and has the potential to cause a wide range of health effects. Indian cities ranked top places in the World Health Organization list of most polluted cities by PM. Objectives: Present study aims to assess the trends, short- and long-term health effects of PM in major Indian cities. Methods: PM-induced hospital admissions and mortality are quantified using AirQ+ software. Results: Annual PM concentration in most of the cities is higher than the National Ambient Air Quality Standards of India. Trend analysis showed peak PM concentration during post-monsoon and winter seasons. The respiratory and cardiovascular hospital admissions in the male (female) population are estimated to be 31,307 (28,009) and 5460 (4882) cases, respectively. PM2.5 has accounted for a total of 1,27,014 deaths in 2017. Conclusion: Cities with high PM concentration and exposed population are more susceptible to mortality and hospital admissions.
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It contains latitudes and longitudes ,population of major cities of India.
https://simplemaps.com/data/in-cities
I wanted to create interactive maps for one of my project so i created this dataset.