In 2024, approximately 11.9 million people lived in São Paulo, making it the largest municipality in Brazil and one of the most populous cities in the world. The homonymous state of São Paulo was also the most populous federal entity in the country. Brazil's cities Brazil is home to two large metropolises: São Paulo with close to 11.9 million inhabitants, and Rio de Janeiro with around 6.7 million inhabitants. It also contains a number of smaller but well-known cities, such as Brasília, Salvador, Belo Horizonte, and many others, which report between 2 and 3 million inhabitants each. As a result, the country's population is primarily urban, with nearly 88 percent of inhabitants living in cities. While smaller than some of the other cities, Brasília was chosen to be the capital because of its relatively central location. The city is also well-known for its modernist architecture and utopian city plan, which is quite controversial - criticized by many and praised by others. Sports venues capitals A number of Brazil’s medium-sized and large cities were chosen as venues for the 2014 World Cup, and the 2015 Summer Olympics also took place in Rio de Janeiro. Both of these events required large sums of money to support infrastructure and enhance mobility within a number of different cities across the country. Billions of dollars were spent on the 2014 World Cup, which went primarily to stadium construction and renovation but also to a number of different mobility projects. Other short-term spending on infrastructure for the World Cup and the Rio Olympic Games was estimated at 50 billion U.S. dollars. While these events have poured a lot of money into urban infrastructure, a number of social and economic problems within the country remain unsolved.

Context

This dataset has information about brazilian cities.

Content

• city: the name of the city
• lat: the latitude of each city
• lng: the longitude of each city
• country: the country of each city (all Brazil in this case)
• iso2: country code (BR)
• admin: state of each city
• capital: wheter the city is a capital or not
• population: amount of inhabitants of each city
• population_proper: area contained within city limits

brazilian cities. name, office head of government, Mayor, image, Area, date founded, Elevation, Country, administrative division, continent, latitude, waterbody, longitude, Website, population, Demonym

streets in Brazil. name, named after, image, city, administrative división, country, continent, Length, Width, place, latitude, longitude, date creation

In 2025, approximately 23 million people lived in the São Paulo metropolitan area, making it the biggest in Latin America and the Caribbean and the sixth most populated in the world. The homonymous state of São Paulo was also the most populous federal entity in the country. The second place for the region was Mexico City with 22.75 million inhabitants. Brazil's cities Brazil is home to two large metropolises, only counting the population within the city limits, São Paulo had approximately 11.45 million inhabitants, and Rio de Janeiro around 6.21 million inhabitants. It also contains a number of smaller, but well known cities such as Brasília, Salvador, Belo Horizonte and many others, which report between 2 and 3 million inhabitants each. As a result, the country's population is primarily urban, with nearly 88 percent of inhabitants living in cities. Mexico City Mexico City's metropolitan area ranks sevenths in the ranking of most populated cities in the world. Founded over the Aztec city of Tenochtitlan in 1521 after the Spanish conquest as the capital of the Viceroyalty of New Spain, the city still stands as one of the most important in Latin America. Nevertheless, the preeminent economic, political, and cultural position of Mexico City has not prevented the metropolis from suffering the problems affecting the rest of the country, namely, inequality and violence. Only in 2023, the city registered a crime incidence of 52,723 reported cases for every 100,000 inhabitants and around 24 percent of the population lived under the poverty line.

stations in Brazil. name, image, type, date Opened, city, administrative división, continent, date Closed, Country, latitude, longitude, number of platforms

brazilian libraries. name, image, Annual visitors, type, Circulation, date founded, city, administrative división, continent, Country, Inventory, latitude, longitude, Website

For many countries lat/lng are determined with an algorithm that searches the place names in the main geonames database using administrative divisions and numerical vicinity of the postal codes as factors in the disambiguation of place names. For postal codes and place name for which no corresponding toponym in the main geonames database could be found an average lat/lng of 'neighbouring' postal codes is calculated. Please let us know if you find any errors in the data set. ThanksFor Canada we have only the first letters of the full postal codes (for copyright reasons)For Ireland we have only the first letters of the full postal codes (for copyright reasons)For Malta we have only the first letters of the full postal codes (for copyright reasons)The Argentina data file contains 4-digit postal codes which were replaced with a new system in 1999.For Brazil only major postal codes are available (only the codes ending with -000 and the major code per municipality).For India the lat/lng accuracy is not yet comparable to other countries.Update frequency: 1 month

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

This dataset contains Airbnb listings of 23 small towns (less than 20k inhabitants mainly) from different regions in Brazil. It was collected in June 2019 through web-scrapping directly from the Airbnb site. The data includes the following information related to each listing: city, name of the accommodation, neighborhood or area, type of accommodation, guests capacity, number of bedrooms, host name, URL, price, number of reviews, date of first review and geographical coordinates.

museums in Brazil. name, Annual visitors, date founded, city, administrative división, continent, Country, latitude, longitude, Website

brazilian universities. name, type, date founded, city, administrative división, continent, Country, latitude, longitude, number of Students, Website, employees

This dataset contains messages published and replies received by government weather and climate authorities on the X (former Twitter) social media platforms. The data comprises government weather and climate authorities for the Brazilian cities of São Paulo, Rio de Janeiro, Belo Horizonte, Porto Alegre, and Belém. Government weather and climate authorities are city hall departments or sectors responsible for informing and keeping the population updated about weather events. Publications made by the authority and replies published by citizens to these publications are observed. This data supports the study on the interaction dynamics between the climate authority and citizens over time. Data Structure Two files are available publications.csv and replies.csv. Each line in the publications' file (publications.csv) refers to an authority publication/tweet. For each publication, it is stored the public authority's unique Twitter identifier (AUTHORITY_ID), the tweet unique identifier (TWEET_ID), the Unix timestamp that indicates when it was published (TIMESTAMP), and the text of the publication (TEXT). Each line in the replies file (replies.csv) is a reply from a citizen to an authority. For each reply, it is stored the authority's unique Twitter identifier (AUTHORITY_ID), the unique identifier of the authority's tweet being replied to (TWEET_ID), the replier masked unique Twitter identifier (AUTHOR_ID), and the reply Unix timestamp (TIMESTAMP) that indicates when it was published. All data were collected through the X's application programming interface (API) provided to scientific researchers. Publications and replies were posted by users (authorities and citizens) with public visibility. Data Content The dataset covers 1-year observation period, starting on July 17, 2021, and ending on June 16, 2022. It contains a total of 10,229 publications and 5,471 replies. The observed authorities are as follows:

City Authority name X handle AUTHORITY_ID São Paulo Centro de Gerenciamento de Emergências Climáticas da Prefeitura de SP @cge_sp 268407434 Rio de Janeiro Sistema de Alerta localizado no Centro de Operações do Rio (COR) @alertario 87487749 Belo Horizonte Defesa Civil de Belo Horizonte @defesacivilbh 837731966 Porto Alegre Defesa Civil Porto Alegre @defesacivilpoa 1037420896473022466 Belém Defesa Civil de Belém @defesacivilbel 1346501728632500225

As weather and climate authorities are government bodies, the whole content of their publications is of public interest according to Brazilian law. Thus, the text messages in their publications on social media are in the public domain and are stored in this dataset. As the data structure describes, text messages of citizens' replies are not stored. According to the terms of use of the X platform, citizen text messages cannot be publicly stored outside the X platform. Such text messages are public on that platform, and, for reproductivity, they can be recollected using the platform web page or API informing the TWEET_ID stored in this dataset.

São Paulo had the highest population of any city in Brazil and also boasted the most companies with a cryptocurrency ATM or in-store payment method in 2021. According to open-source information, the Brazilian city even had a relatively high amount of these firms, especially when compared against Rio de Janeiro - a city with roughly half the population of São Paulo but approximately ** percent the amount of businesses.

The Brazilian National Institute of Meteorology (INMET, from the Portuguese "Instituto Nacional de Meteorologia'') is the Brazilian government agency responsible for monitoring, analysing and forecasting weather and climate. It provides meteorological warnings to be used by the local-level municipal authorities.

Data Content

INMET periodically publishes data on its website and provides them via XML RSS Feed. This dataset was collected from the RSS feeds mentioning the Brazilian cities of Belém located in the state of Pará, Belo Horizonte in Minas Gerais state, Porto Alegre in Rio Grande do Sul state, Rio de Janeiro in Rio de Janeiro state and São Paulo in São Paulo state from July/2021 to July/2022.

Data Structure

The description of columns collected from INMET warnings and stored in the warnings file (inmet-meteorological-warnings-1658070001.csv) is presented below. The warnings issued by INMET follow the Common Alerting Protocol (CAP). CAP provides an open, non-proprietary digital message format for all types of alerts and notifications [Standard, OASIS (2010). Common Alerting Protocol Version 1.2. Jul, 1, pp. 1-47. http://docs.oasis-open.org/emergency/cap/v1.2/CAP-v1.2-os.html ].

Columns:

• CITY: Name of the city for which the warning was issued.
• STATE: The Brazilian acronym for the state in which the city is located, for example, MG for Minas Gerais.
• CITYCODE: Unique numeric code for the city for which the warning was issued.
• IDENTIFIER: Unique identifier to INMET warning.
• RESPONSETYPE: Reaction to the warning.
• URGENCY: Urgency for taking action. For example, “Prepare”.
• SEVERITY: Severity of the meteorological event. For example, “Future”
• CERTAINTY: How likely is the event to happen? For example, “Observed” - Determined to have occurred or to be ongoing; “Likely” - (p > ~50%); “Possible” - Possible but not likely (p <= ~50%).
• WARNING: Standardized type of warning. For example, "Aviso de Acumulado de Chuva", "Aviso de Tempestade", "Aviso de Declínio de Temperatura".
• TIMESTAMPDATEONSE: Unix timestamp of the minimum time at which the event is expected to start.
• TIMESTAMPDATEEXPIRES: Unix timestamp of the maximum at which the event is expected to occur or the warning expires.
• COLORRISK: Event colour in hexadecimal following the INMET nomenclature, with yellow meaning potential danger, orange indicating danger, and red indicating great danger.
• BASESOURCE: INMET RSS XML file from which the warning was extracted.

heritage sites in Brazil. name, image, heritage designation, Area, date completed, Country, continent, latitude, longitude, style, Website, city, administrative división

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.