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.

Content

It contains latitudes and longitudes ,population of major cities of India.

Acknowledgements

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

Inspiration

I wanted to create interactive maps for one of my project so i created this dataset.

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

Google

Demo: here

arXiv : https://arxiv.org/abs/2403.10912

Delhi was the largest city in terms of number of inhabitants in India in 2025. The capital city was estimated to house nearly 35 million people, with Mumbai ranking second that year. India's population estimate was 1.4 billion, ahead of China that same year.

Unleash the potential of location-based analysis with this dataset of Indian cities. With over 4000 entries meticulously curated with city names, states, and precise latitude and longitude coordinates, uncover valuable insights into population distribution, urban development, and more.

Dataset for Indian cities, including images, unsplash, Airbnb, and Wikipedia content about each location, along with geospatial data such as latitude, longitude and Google Maps URL

The purpose of the dataset is to enable devs accross the world and mainly in india to build apps and websites The data is scraped locally using honojs and cleaned using LLM

Image Cover

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1842206%2Fcc0eb2fff946bf6e89ce8a5a1fcf2b57%2Fnewdelhi2.png?generation=1730130146299892&alt=media" alt="">

Context

Hourly and Daily Weather Dataset of Top 50 Most populous Indian cities. Weather data from https://open-meteo.com/ from January 01, 2020 to October 27, 2024.

Field documentation go here

• https://open-meteo.com/en/docs/historical-weather-api#start_date=2020-01-01&end_date=2024-10-27
• Datetime is in GMT

Visually verify coordinates

• Replace the placeholders with the latitude and longitude values of the cities https://www.latlong.net/c/?lat=(latitude)&long=(longitude)
• Another way to visualize the coordinates https://www.ncei.noaa.gov/maps/radar/

Citations and Acknowledgements

• Zippenfenig, P. (2023). Open-Meteo.com Weather API [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.7970649
• Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N. (2023). ERA5 hourly data on single levels from 1940 to present [Data set]. ECMWF. https://doi.org/10.24381/cds.adbb2d47
• Muñoz Sabater, J. (2019). ERA5-Land hourly data from 2001 to present [Data set]. ECMWF. https://doi.org/10.24381/CDS.E2161BAC
• Schimanke S., Ridal M., Le Moigne P., Berggren L., Undén P., Randriamampianina R., Andrea U., Bazile E., Bertelsen A., Brousseau P., Dahlgren P., Edvinsson L., El Said A., Glinton M., Hopsch S., Isaksson L., Mladek R., Olsson E., Verrelle A., Wang Z.Q. (2021). CERRA sub-daily regional reanalysis data for Europe on single levels from 1984 to present [Data set]. ECMWF. https://doi.org/10.24381/CDS.622A565A

India's Largest Cities Weather Data Weather Datasets

• 🇮🇳 India's Largest Cities Weather Data 1990-1999
• 🇮🇳 India's Largest Cities Weather Data 2000-2009
• 🇮🇳 India's Largest Cities Weather Data 2010-2019
• 🇮🇳 India's Largest Cities Weather Data 2020-YTD

Note

Image generated with Bing Image Generator

Title: Population Data of Indian Cities (2011 and 2001)

Description: This dataset contains population information for various cities in India, categorized by rank, city name, and population figures for the years 2011 and 2001. Additionally, it includes the corresponding state or union territory to which each city belongs. The dataset provides insights into population changes over a decade in different cities across India.

Columns:

Rank: This column represents the rank of each city based on its population in the year 2011. Cities are typically ranked in descending order of population, with the most populous city having the rank 1.

City: This column contains the names of the cities for which population data is recorded.

Population (2011): This column displays the population count of each city as of the year 2011. The population figures are likely to be recorded in thousands or millions

Population (2001): This column provides the population count of each city as of the year 2001. Comparing this data with the 2011 population figures allows for an analysis of population growth or decline over the decade.

State or Union Territory: This column indicates the administrative division to which each city belongs. In India, cities are typically grouped into states or union territories, and this column helps identify the geographical context of each city.

In 2021, Delhi had the highest metro coverage among major metropolitan cities in India with ** operational kilometers per *********** people. At the same time, Mumbai had the lowest coverage with only *** operational kilometers per *********** people. Poor public transportation in many Indian cities was responsible for traffic congestion and air pollution.

Actual value and historical data chart for India Population In Largest City

This dataset was taken from data.gov.in(Open Government Data Portal(INDIA)) which is a single-point of access to Datasets/Apps in open format published by Ministries/Departments. This categorical and detailed dataset provides information about number of vehicles of different categories in major Indian cities as of 31.03.2016

dataset taken from https://data.gov.in/resource/category-wise-detailed-total-registered-motor-vehicles-million-plus-cities-india-3132016

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.

About this dataset

Context

This list ranks the 23 cities in the Atlantic County, NJ by American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Native American Population: This column displays the rank of cities in the Atlantic County, NJ by their American Indian and Alaska Native (AIAN) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Native American Population: The Native American population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Native American. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Atlantic County Native American Population: This tells us how much of the entire Atlantic County, NJ Native American population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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.

Inspiration

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/.

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.

The demand for commercial real estate space in top seven cities in India stood at ** million square feet as of 2023. It was the same as previous year.

About this dataset

Context

This list ranks the 473 cities in the California by Indian population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Indian Population: This column displays the rank of city in the California by their Indian population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Indian Population: The Indian population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Indian. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total California Indian Population: This tells us how much of the entire California Indian population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

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.

Inspiration

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/.

As of 2024, Mumbai had a gross domestic product of *** billion U.S. dollars, the highest among other major cities in India. It was followed by Delhi with a GDP of around *** billion U.S. dollars. India’s megacities also boast the highest GDP among other cities in the country. What drives the GDP of India’s megacities? Mumbai is the financial capital of the country, and its GDP growth is primarily fueled by the financial services sector, port-based trade, and the Hindi film industry or Bollywood. Delhi in addition to being the political hub hosts a significant services sector. The satellite cities of Noida and Gurugram amplify the city's economic status. The southern cities of Bengaluru and Chennai have emerged as IT and manufacturing hubs respectively. Hyderabad is a significant player in the pharma and IT industries. Lastly, the western city of Ahmedabad, in addition to its strategic location and ports, is powered by the textile, chemicals, and machinery sectors. Does GDP equal to quality of life? Cities propelling economic growth and generating a major share of GDP is a global phenomenon, as in the case of Tokyo, Shanghai, New York, and others. However, the GDP, which measures the market value of all final goods and services produced in a region, does not always translate to a rise in quality of life. Five of India’s megacities featured in the Global Livability Index, with low ranks among global peers. The Index was based on indicators such as healthcare, political stability, environment and culture, infrastructure, and others.

Passenger Trips to Major Cities (India Air Travel)

Investigating Passenger Numbers to and from Indian Cities

By Telangana Open Data [source]

About this dataset

This dataset provides comprehensive insights into the air traveling activity in the year 2017 for Hyderabad, India. It displays a list of domestic air travelers to and from this city to all other cities in India. You can access valuable specifics like the number of passengers recorded on each journey until October 2017. This useful collection of data from data.telangana.gov.in provides an essential glimpse into trends and patterns amongst Hyderabad's domestic air traffic, helping city planners and business make more informed decisions!

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How to use the dataset

How to Use 2017 Hyderabad Domestic Air Traffic Data

This dataset provides information about the number of air travelers that arrived in or left from Hyderabad, India in 2017. The data covers all major cities in India until October, giving users a chance to analyze and compare domestic air traffic between cities. This guide will provide an overview on how to use this data set effectively.

Exploring the Dataset

The dataset contains two columns: ‘level_0’ which is the index of the dataframe and ‘M passengers’ which is the number of passengers listed for each airport. It is important to remember that the numbers correspond to they year 2017 only and not current passenger rates. Exploring this data will allow users understand trends in travel patterns across different cities throughout India over a period of time.

Analyzing Trends with Maps

Using mapping technologies such as CartoDB will allow users build dynamic visualizations and gain a better understanding on temporal changes that occur within Indian domestic air travel since start of 2017 up until October 2017. Comparing these maps with socio-economic metrics will also allow deeper analysis on population demographics across India’s top flight routes; useful information when creating marketing plans or proposals related aviation expansion projects etc...

### Additional Analysis Tools Besides mapping tools such as CartoDB; other tools like R can be used to run various statistical models related estimating future traffic volumes based on present passenger patterns, creating correlation networks between selected cities compared side by side against socio-economic trends etc.. Finally SPSS can be used run qualitative analysis those interested in analyzing more subjective avaiation industry related studies such as airliners customer services ratings by destinations city or feedback surveys pre post domestic flights taken throughout certain regions within India etc.

Research Ideas

• Constructing a detailed visualization of the air transportation patterns from Hyderabad to all other cities in India, offering an increased understanding of both high traffic and low traffic destinations.
• Understanding passenger demand for different travel providers such as AirAsia, Indigo etc in the city and predicting possible growth trends for them.
• Refining marketing strategies for flight-based travel services by establishing their target market within the Hyerabad area and subsequently utilizing data-driven tactics to increase sales

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: 2017 Hyderabad Domestic Air Traffic.csv | Column name | Description | |:--------------|:------------------------------------------| | level_0 | Unique identifier for each row. (Integer) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Telangana Open Data.

The official records on crime and response by the police are hugely insufficient in gauging the scale of the problem due to widespread under-reporting, among other deficiencies. Safety Trends and Reporting of Crime (SATARC), IDFC Institute’s flagship survey, is an attempt to marshal evidence, in a systematic way, about the extent and nature of crime, satisfaction with police, and perceptions of safety. The SATARC survey aims to bridge this gap in public data on safety and crime.

About this dataset

Context

This list ranks the 5 cities in the Indian River County, FL by American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Native American Population: This column displays the rank of cities in the Indian River County, FL by their American Indian and Alaska Native (AIAN) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Native American Population: The Native American population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Native American. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Indian River County Native American Population: This tells us how much of the entire Indian River County, FL Native American population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

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.

Inspiration

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/.