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Brazil City Snapshot
NLP / Natural Language Processing
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About
Brazil is the fifth-largest country globally by area and the fifth most populous, with over 208 million people. The Federative Republic of Brazil is composed of 26 states, the Federal District, and 5,570 municipalities. This dataset is a compilation of publicly available information about Brazilian Municipalities. The data was retrieved from several websites, processed, and merged by city name, resulting in 79 distinct data fields for every city. The dataset aims to assist students in enhancing their analytical abilities and anyone interested in learning more about Brazil.
Columns
- CITY: Name of the City
- STATE: Name of the State
- CAPITAL: Indicates if the city is a Capital of State (1 if Capital)
- IBGE_RES_POP: Resident Population - 2010
- IBGE_RES_POP_BRAS: Resident Population Brazilian - 2010
- IBGE_RES_POP_ESTR: Resident Population Foreigners - 2010
- IBGE_DU: Domestic Units Total - 2010
- IBGE_DU_URBAN: Domestic Units Urban - 2010
- IBGE_DU_RURAL: Domestic Units Rural - 2010
- IBGE_POP: Resident Population Regular Urban Planning - 2010
- IBGE_1: Resident Population Regular Urban Planning - until 1 y.o - 2010
- IBGE_1-4: Resident Population Regular Urban Planning - from 1 to 4 y.o - 2010
- IBGE_5-9: Resident Population Regular Urban Planning - from 4 to 9 y.o - 2010
- IBGE_10-14: Resident Population Regular Urban Planning - from 10 to 14 y.o - 2010
- IBGE_15-59: Resident Population Regular Urban Planning - from 15 to 59 y.o - 2010
- IBGE_60+: Resident Population Regular Urban Planning - above 60 y.o - 2010
- IBGE_PLANTED_AREA: Planted Area (hectares) - 2017 (1 hectare = 10,000 square metres)
- IBGE_CROP_PRODUCTION_$: Crop Production - 2017 ($ 1,000 reais)
- IDHM Ranking: HDI Ranking - 2010
- IDHM: HDI Human Development Index - 2010
- IDHM_Renda: HDI GNI Index - 2010
- IDHM_Longevidade: HDI Life Expectancy index - 2010
- IDHM_Educacao: HDI Education index - 2010
- LONG: City Longitude - 2010
- LAT: City Latitude - 2010
- ALT: City Elevation (metres) - 2010 (1 metre)
- PAY_TV: PayTV users - 2019-03
- FIXED_PHONES: Fixed Phones (not cell phones) users - 2019-03
- AREA: City area (square kilometres) - 2018 (1 square kilometre = 1,000,000 square metres)
- REGIAO_TUR: Tourism Category Region - 2017
- CATEGORIA_TUR: Tourism Category - 2017
- ESTIMATED_POP: Estimated Population - 2018-07
- RURAL_URBAN: Rural or Urban Typology - 2016
- GVA_AGROPEC: Gross Added Value - Agropecuary - 2016 ($ 1,000 reais)
- GVA_INDUSTRY: Gross Added Value - Industry - 2016 ($ 1,000 reais)
- GVA_SERVICES: Gross Added Value - Services - 2016 ($ 1,000 reais)
- GVA_PUBLIC: Gross Added Value - Public Services - 2016 ($ 1,000 reais)
- GVA_TOTAL: Total Gross Added Value - 2016 ($ 1,000 reais)
- TAXES: Taxes - 2016 ($ 1,000 reais)
- GDP: Gross Domestic Product - 2016 ($ 1,000 reais)
- POP_GDP: Population - 2016
- GDP_CAPITA: Gross Domestic Product per capita - 2016
- GVA_MAIN: Activity with higher GVA contribution - 2016
- MUN_EXPENDIT: Municipal expenditures - in reais - 2016 ($ 1 real)
- COMP_TOT: Total number of companies - 2016
- COMP_A: Number of Companies: Agriculture, livestock, forestry, fishing and aquaculture - 2016
- COMP_B: Number of Companies: Extractive industries - 2016
- COMP_C: Number of Companies: Industries of transformation - 2016
- COMP_D: Number of Companies: Electricity and gas - 2016
- COMP_E: Number of Companies: Water, sewage, waste management and decontamination activities - 2016
- COMP_F: Number of Companies: Construction - 2016
- COMP_G: Number of Companies: Trade; repair of motor vehicles and motorcycles - 2016
- COMP_H: Number of Companies: Transport, storage and mail - 2016
- COMP_I: Number of Companies: Accommodation and food - 2016
- COMP_J: Number of Companies: Information and communication - 2016
- COMP_K: Number of Companies: Financial, insurance and related services activities - 2016
- COMP_L: Number of Companies: Real estate activities - 2016
- COMP_M: Number of Companies: Professional, scientific and technical activities - 2016
- COMP_N: Number of Companies: Administrative activities and complementary services - 2016
- COMP_O: Number of Companies: Public administration, defence and social security - 2016
- COMP_P: Number of Companies: Education - 2016
- COMP_Q: Number of Companies: Human health and social services - 2016
- COMP_R: Number of Companies: Arts, culture, sport and recreation - 2016
- COMP_S: Number of Companies: Other service activities - 2016
- COMP_T: Number of Companies: Domestic services - 2016
- COMP_U: Number of Companies: International and other extraterritorial institutions - 2016
- HOTELS: Total number of hotels - 2019-03
- BEDS: Total number of hotel beds - 2019-03
- Pr_Agencies: Total number of private bank agencies - 2019-02
- Pu_Agencies: Total number of public bank agencies - 2019-02
- Pr_Bank: Total number of private banks - 2019-02
- Pu_Bank: Total number of public banks - 2019-02
- Pr_Assets: Total amount of private bank assets - 2019-02 ($ 1 real)
- Pu_Assets: Total amount of public bank assets - 2019-02 ($ 1 real)
- Cars: Total number of cars - 2019-01
- Motorcycles: Total number of motorcycles, scooters, moped - 2019-01
- Wheeled_tractor: Total number of wheeled tractors - 2019-01
- UBER: Indicates if UBER is present (1 if UBER) - 2019-05
- MAC: Total number of McDonald's stores - 2018-11
- WALMART: Total number of Walmart Stores - 2018-12
- POST_OFFICES: Total number of post offices - 2019-05
Distribution
The dataset is provided in CSV format with a size of 2.36 MB. It is structured as tabular data, comprising 81 columns and 5,573 records, with each record representing a unique Brazilian municipality.
Usage
This dataset is ideal for a variety of applications and use cases, including:
- Educational purposes: Students can utilise this data to practise and enhance their analytical skills.
- Country insights: Anyone interested in gaining a deeper understanding of Brazil's urban and rural areas, demographics, and economic landscape.
- Socio-economic analysis: Examining the Human Development Index (HDI), Gross Domestic Product (GDP), and the distribution of companies across various sectors within Brazilian municipalities.
- Urban planning and development: Analysing population distribution, domestic units, and city area for planning initiatives.
- Market research: Identifying the presence of major businesses (e.g., McDonald's, Walmart, Uber) and analysing local market penetration of services like PayTV, fixed phones, and banking.
- Tourism studies: Investigating regional tourism categories, the number of hotels, and available hotel beds to inform tourism development strategies.
- Agricultural analysis: Studying planted areas and crop production figures at the municipal level.
Coverage
- Geographic Scope: The data covers 5,570 municipalities across the Federative Republic of Brazil, providing information on their respective states and whether they serve as state capitals.
- Time Range: Data spans multiple years, with core demographic and Human Development Index (HDI) information from 2010. Economic indicators, including Gross Added Value (GVA), Gross Domestic Product (GDP), taxes, and company statistics, are primarily from 2016. Agricultural data (planted area, crop production) and tourism categories are from 2017. Estimated population data is from July 2018, and city area is from 2018. Recent data points, such as PayTV and fixed phone users, hotel and bank statistics, vehicle counts, Uber presence, McDonald's and Walmart stores, and post office numbers, are predominantly from 2019.
- Demographic Scope: Includes resident population (total, Brazilian, foreign), total domestic units, and a breakdown of domestic units into urban and rural. Population is also segmented by several age groups: until 1 year old, 1-4 years old, 4-9 years old, 10-14 years old, 15-59 years old, and above 60 years old.
- Data Availability Notes: While the dataset contains information for 5,573 cities, some fields like 'STATE' have approximately 25% missing values. Furthermore, fields related to tourism categories ('REGIAO_TUR', 'CATEGORIA_TUR'), rural/urban typology ('RURAL_URBAN'), and the main GVA activity ('GVA_MAIN') show significant missing data in the provided summary statistics.
License
CC BY-SA 4.0
Who Can Use It
- Students: For data analysis, statistical training, and academic projects.
- Researchers: Conducting studies on Brazilian demographics, urbanisation trends, economic development, and social indicators.
- Data Analysts and Scientists: For building analytical models, performing statistical analysis, and generating insights into municipal characteristics.
- Economists: Analysing regional economic disparities, GDP contributions, and the business landscape.
- Urban Planners: Informing decisions related to infrastructure, population distribution, and public service provision.
- Businesses: Utilising for market entry strategies, location analysis for retail chains, and understanding local consumer bases.
- Tourism Professionals: For developing tourism strategies and understanding tourist infrastructure at a municipal level.
- Government Agencies: For policy formulation, regional development initiatives, and public administration studies.
Dataset Name Suggestions
- Brazilian Municipal Data
- Brazil City Indicators
- Brazilian Urban & Economic Profiles
- Brazil Municipalities Statistics
- Brazil City Snapshot
Attributes
Original Data Source: Brazil City Snapshot
QUALITY