The state of Mexico is the most populated region in Mexico, being home to around 13.44 percent of the country's total population. In 2022, approximately 17.32 million people lived in the state of Mexico, whereas 9.3 million resided in the country's capital, Mexico City. The state with the lowest number of inhabitants was Colima, with around 770,900 residents.

Chiapas was the state in Mexico with the highest average extreme poverty rate in 2022. It was estimated that almost three out of ten people in Chiapas lived in a situation of extreme poverty. In contrast, Baja California was the state with the lowest extreme poverty rate, with 0.8 percent, well below the national average, which stood at 7.1 percent. The share of population living in poverty in Mexico amounted to 36.3 percent in 2022.

In 2023, California had the highest Hispanic population in the United States, with over 15.76 million people claiming Hispanic heritage. Texas, Florida, New York, and Illinois rounded out the top five states for Hispanic residents in that year. History of Hispanic people Hispanic people are those whose heritage stems from a former Spanish colony. The Spanish Empire colonized most of Central and Latin America in the 15th century, which began when Christopher Columbus arrived in the Americas in 1492. The Spanish Empire expanded its territory throughout Central America and South America, but the colonization of the United States did not include the Northeastern part of the United States. Despite the number of Hispanic people living in the United States having increased, the median income of Hispanic households has fluctuated slightly since 1990. Hispanic population in the United States Hispanic people are the second-largest ethnic group in the United States, making Spanish the second most common language spoken in the country. In 2021, about one-fifth of Hispanic households in the United States made between 50,000 to 74,999 U.S. dollars. The unemployment rate of Hispanic Americans has fluctuated significantly since 1990, but has been on the decline since 2010, with the exception of 2020 and 2021, due to the impact of the coronavirus (COVID-19) pandemic.

Two out of every three persons in Chiapas lived under the poverty line in 2022, making it the federal entity with the largest share of poor population in Mexico. On average, about 36 percent of the Mexican population was living in poverty that year.

A dataset listing New Mexico cities by population for 2024.

All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

In 2022, around 48.59 percent of New Mexico's population was of Hispanic origin, compared to the national percentage of 19.45. California, Texas, and Arizona also registered shares over 30 percent. The distribution of the U.S. population by ethnicity can be accessed here.

This project provides a comprehensive dataset on intentional homicides in Mexico from 1990 to 2023, disaggregated by sex and state. It includes both raw data and tools for visualization, making it a valuable resource for researchers, policymakers, and analysts studying violence trends, gender disparities, and regional patterns.ContentsHomicide Data: Total number of male and female victims per state and year.Population Data: Corresponding male and female population estimates for each state and year.Homicide Rates: Per 100,000 inhabitants, calculated for both sexes.Choropleth Map Script: A Python script that generates homicide rate maps using a GeoJSON file.GeoJSON File: A spatial dataset defining Mexico's state boundaries, used for mapping.Sample Figure: A pre-generated homicide rate map for 2023 as an example.Requirements File: A requirements.txt file listing necessary dependencies for running the script.SourcesHomicide Data: INEGI - Vital Statistics MicrodataPopulation Data: Mexican Population Projections 2020-2070This dataset enables spatial analysis and data visualization, helping users explore homicide trends across Mexico in a structured and reproducible way.

This map shows a comparison between the number of economically active males who are 15 years or older to number of economically active females who are 15 years or older in Mexico by State and Municipality. Data is from Censo INEGI 2020. Each layer is configured with a pop-up for additional information. In addition, the Municipality layer is configured with a new Map Viewer chart. Censo INEGI 2020 información Ocupación Municipal /INEGI Census 2020 Employment Information by MunicipalityEsta capa muestra la información de la situación de ocupación de la población en México a nivel municipal. También hay atributos, que representan estas características como porcentaje del total de la población municipal, que se pueden mapear o utilizar en el análisis.La capa está simbolizada por el porcentaje de población femenina no económicamente activa, a nivel municipal. Para ver la lista completa de atributos disponibles en este servicio, vaya a la pestaña "Datos" y seleccione "Campos" en la parte superior derecha.Esta capa lista para usar se puede usar dentro de ArcGIS Pro, ArcGIS Online, sus aplicaciones configurables, paneles, Story Maps, aplicaciones personalizadas y aplicaciones móviles. Los datos también se pueden exportar para flujos de trabajo sin conexión. Por favor, cite al INEGI (Instituto Nacional de Estadística y geografía) cuando utilice estos datos.Información adicional sobre documentación y metodología del censo se puede encontrar en Censo Población y Vivienda 2020 (inegi.org.mx)_This layer shows employment status of the population in Mexico at a municipal level. There are also attributes, representing these characteristics as percentage of total municipal population, which can be mapped or used within analysis. The layer is symbolized by the percentage of female population who is not economically active, at the municipal level. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite INEGI (Instituto Nacional de Estadistica y Geografia) when using this data.Additional information regarding documentation and methodology regarding the census can be found at Censo Población y Vivienda 2020 (inegi.org.mx)

countries capital city Mexico City. name, long name, population (source), population, constitutional form, drives on, head of state authority, Main continent, number of airports, Airports - with paved runways, Airports - with unpaved runways, Area, Birth rate, calling code, Children under the age of 5 years underweight, Current Account Balance, Death rate, Debt - external, Economic aid donor, Electricity consumption, Electricity consumption per capita, Electricity exports, Electricity imports, Electricity production, Exports, GDP - per capita (PPP), GDP (purchasing power parity), GDP real growth rate, Gross national income, Human Development Index, Health expenditures, Heliports, HIV AIDS adult prevalence rate, HIV AIDS deaths, HIV AIDS people living with HIV AIDS, Hospital bed density, capital city, Currency, Imports, Industrial production growth rate, Infant mortality rate, Inflation rate consumer prices, Internet hosts, internet tld, Internet users, Investment (gross fixed), iso 3166 code, ISO CODE, Labor force, Life expectancy at birth, Literacy, Manpower available for military service, Manpower fit for military service, Manpower reaching militarily age annually, is democracy, Market value of publicly traded shares, Maternal mortality rate, Merchant marine, Military expenditures percent of GDP, Natural gas consumption, Natural gas consumption per capita, Natural gas exports, Natural gas imports, Natural gas production, Natural gas proved reserves, Net migration rate, Obesity adult prevalence rate, Oil consumption, Oil consumption per capita, Oil exports, Oil imports, Oil production, Oil proved reserves, Physicians density, Population below poverty line, Population census, Population density, Population estimate, Population growth rate, Public debt, Railways, Reserves of foreign exchange and gold, Roadways, Stock of direct foreign investment abroad, Stock of direct foreign investment at home, Telephones main lines in use, Telephones main lines in use per capita, Telephones mobile cellular, Telephones mobile cellular per capita, Total fertility rate, Unemployment rate, Unemployment, youth ages 15-24, Waterways, valley, helicopter, canyon, artillery, crater, religion, continent, border, Plateau, marsh, Demonym

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

The survey covers Mexico.

Analysis unit

• Household
• Individual

Universe

The WVS for Mexico covers national population aged 18 years and over for both sexes.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Mexico 2005 survey used a multi-stage sampling procedure. Interviewers selected an adult using a random selection method. However, we also employed control quotas according to sex and age this practice was more common in rural areas, where the male population is more difficult to find at home during interviewing hours. Interviewers made sure that respondents were at least 18 years old, that they lived in the selected household. Interviews were all conducted in-home.

Remarks about sampling: The first stage was the selection of polling points based on the list of electoral sections defined by the Federal Elections Institute. The sections were previously stratified as urban (70 percent), and rural and mixed (30 percent). Each section is relatively homogeneous in size, with about 1,092 registered voters in 63,810 sections that cover all the countrys adult population. Respondents included, of course, also adults nonregistered as voters. We selected 130 electoral sections in a systematically random fashion in each stratum, based on the list arranged proportionally to size of population. In the second stage we selected the household with a systematic random selection, based on a standard strategy of walking around the housing districts selected in the sample. In the third stage, interviewers selected an adult respondent in each household. We used control quotas based on sex and age in districts where random selection of interviewers was disproportionately leaning towards a specific group. Each polling point represents 12 interviews, and quota control established that 6 were male respondents and 6 women respondents, to ensure an appropriate distribution, especially in areas where some specific group is difficult to reach during the hours of interviewing (i.e. rural towns and communities). The Mexican countryside presents problems, for example, to reach male populations during the day in their households. In terms of age, the following quotas were employed where needed: 4 out of 12 were 18 to 29 years old; 5 out of 12 were 30 to 49 years old, and 3 out of 12 were 50 years old or older. We substituted four of the originally selected addresses; three in rural areas and one in an urban area. In the rural cases, the interviewers were not able to get to them because of the absence of roads and transportation. In the urban case, the polling point was substituted because the neighborhood represented serious safety problems at the time of the survey. All the polling points were substituted with addresses with the same socioeconomic level, in the same region, state and electoral district. Substitution of households and respondents were also employed, in the cases where either one of them was registered as a no contact or a refusal and remained under those categories after call backs or returns. Interviewers kept record of non response items (no contact, refusals, suspension) at every time.

The sample size for Mexico is N=1560 and includes the national population aged 18 years and over for both sexes.

Mode of data collection

Face-to-face [f2f]

Research instrument

English and Spanish Questionnaires. The Mexico 2005 questionnaire includes these additional questions:

• Main television news broadcast R watches: v229a (placed between v229 Rs information sources and v230 how often R uses a personal computer).
• Voting intentions for President: v233b to v233c (placed between v233 party R would never vote for and v234 party R voted for federal deputy in 2003). In this question, interviewers used a secret-ballot method with the names of the candidates and the party logos.
• Party identification: v233a (placed between v222 party R would never vote for and v223 party R voted for federal deputy in 2003)
• Items on Mexicos economic relationships: v234a to v234d (placed between v234 party R voted for federal deputy in 2003 and v235 gender.
• Items on the relationship between Mexico and United States: v234a to v234d (placed between v234 party R voted for federal deputy in 2003 and v235 gender) -Items on underground economy: v247a to v247c (placed between v247 Does R supervise people in his job and v248 Is R the chief wage earner) v248 Is R the chief wage earner)

Response rate

Total number of starting names/addresses (electoral sections) 130 No contact at selected address (households) 1759 No contact with selected person 1084 Refusal at selected address 667 Personal refusal by selected respondent 824 Full productive interview 1560 Break Off 52 No elegible respondent 357 Quota filled 999

Remarks about non-response: Electoral sections are a reliable sampling unit in Mexico. Between 95 and 97 percent of all adult population is reachable using the electoral sections as sampling frame. The sample distribution in Mexico does not appear to have any known limitations. Non response rate is 70%, including no contacts and refusals.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

This map shows the population 15 and older who are illiterate in Mexico by State and Municipality. Data is from Censo INEGI 2020. Each layer is configured with a pop-up for additional information. In addition, the Municipality layer is configured with a new Map Viewer chart. Censo INEGI 2020 Información Educación Municipal /INEGI Census 2020 Education Information by MunicipalityEsta capa muestra la situación educativa en México a nivel municipal desglosada por nivel de educación, edad y género. También hay atributos, que representan estas características como porcentaje de la población total del municipio, que pueden mapearse o usarse dentro del análisis.La capa está simbolizada por el porcentaje de personas mayores a 15 años sin escolaridad, de la población total en el municipio. Para ver la lista completa de atributos disponibles en este servicio, vaya a la pestaña "Datos" y seleccione "Campos" en la parte superior derecha.Esta capa lista para usar se puede usar dentro de ArcGIS Pro, ArcGIS Online, sus aplicaciones configurables, paneles, Story Maps, aplicaciones personalizadas y aplicaciones móviles. Los datos también se pueden exportar para flujos de trabajo sin conexión. Por favor, cite al INEGI (Instituto Nacional de Estadística y geografía) cuando utilice estos datos.Información adicional sobre documentación y metodología del censo se puede encontrar en Censo Población y Vivienda 2020 (inegi.org.mx)._This layer shows the educational situation in Mexico at the municipal level broken down by level of education, age, and gender. There are also attributes, representing these characteristics as a percentage of the municipality’s total population, that can be mapped or used within the analysis.The layer is symbolized by the percentage of people older than 15 years without schooling, of the total population in the municipality. To see the full list of attributes available in this service, go to the "Data" tab and select "Fields" at the top right.This ready to use layer can be used within ArcGIS Pro, ArcGIS Online, their configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite INEGI (National Institute of Statistics and Geography) when using these data.Additional information on documentation and methodology of the census can be found at Censo Población y Vivienda 2020 (inegi.org.mx).

As of 2023, around 37.99 million people of Mexican descent were living in the United States - the largest of any Hispanic group. Puerto Ricans, Salvadorans, Cubans, and Dominicans rounded out the top five Hispanic groups living in the U.S. in that year.

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes:
- macroregion (admin-1 including region)
- region (admin-2 including state, province, department, governorate)
- macrocounty (admin-3 including arrondissement)
- county (admin-4 including prefecture, sub-prefecture, regency, canton, commune)
- localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb)

The dataset also contains human settlement points and polygons for:
- localities (city, town, and village)
- neighbourhoods (borough, macrohood, neighbourhood, microhood)

The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names.

Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

A dataset listing New Mexico counties by population for 2024.

This map shows the population who don't have health insurance in Mexico by State and Municipality. Data is from Censo INEGI 2020. Each layer is configured with a pop-up for additional information. In addition, the Municipality layer is configured with a new Map Viewer chart. Censo INEGI 2020 Información Salud Municipal /INEGI Census 2020 Health Information by MunicipalityEsta capa muestra la información del acceso a los servicios de salud de la población en México a nivel municipal. También hay atributos, que representan estas características como porcentaje del total de la población municipal, que se pueden mapear o utilizar en el análisis.La capa está simbolizada por el porcentaje de población sin derecho a servicios de salud, a nivel municipal. Para ver la lista completa de atributos disponibles en este servicio, vaya a la pestaña "Datos" y seleccione "Campos" en la parte superior derecha.Esta capa lista para usar se puede usar dentro de ArcGIS Pro, ArcGIS Online, sus aplicaciones configurables, paneles, Story Maps, aplicaciones personalizadas y aplicaciones móviles. Los datos también se pueden exportar para flujos de trabajo sin conexión. Por favor, cite al INEGI (Instituto Nacional de Estadística y Geografia) cuando utilice estos datos.Información adicional sobre documentación y metodología del censo se puede encontrar en Censo Población y Vivienda 2020 (inegi.org.mx)_This layer shows access to health services of the population in Mexico at a municipal level. There are also attributes, representing these characteristics as percentage of total municipal population, which can be mapped or used within analysis. The layer is symbolized by the percentage of people with no access to health services, at the municipal level. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite INEGI (Instituto Nacional de Estadistica y Geografia) when using this data.Additional information regarding documentation and methodology regarding the census can be found at Censo Población y Vivienda 2020 (inegi.org.mx)

In 2020, Mexico had a catholic population of ********** people, by far the most followed religion in the country. Mexico State concentrated more than **** million, close to the double of the second state in the list, Jalisco. The capital Mexico City figured in the third place, with **** million Catholics.

Censo INEGI 2010 Informacion Ocupación Estatal /INEGI Census 2010 Employment Information by State Esta capa muestra la información de la situación de ocupación de la población en México a nivel estatal. También hay atributos, que representan estas características como porcentaje del total de la población estatal, que se pueden mapear o utilizar en el análisis. La capa está simbolizada por el porcentaje de población femenina no económicamente activa, a nivel estatal. Para ver la lista completa de atributos disponibles en este servicio, vaya a la pestaña "Datos" y seleccione "Campos" en la parte superior derecha. Esta capa lista para usar se puede usar dentro de ArcGIS Pro, ArcGIS Online, sus aplicaciones configurables, paneles, Story Maps, aplicaciones personalizadas y aplicaciones móviles. Los datos también se pueden exportar para flujos de trabajo sin conexión. Por favor, cite al INEGI (Instituto Nacional de Estadística y Geografia) cuando utilice estos datos. Información adicional sobre documentación y metodología del censo se puede encontrar en https://www.inegi.org.mx/programas/ccpv/2010/_This layer shows employment status of the population in Mexico at a state level. There are also attributes, representing these characteristics as percentage of total state population, which can be mapped or used within analysis. The layer is symbolized by the percentage of female population who is not economically active, at the state level. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite INEGI (Instituto Nacional de Estadistica y Geografia) when using this data. Additional information regarding documentation and methodology regarding the census can be found at https://www.inegi.org.mx/programas/ccpv/2010/

This dataset contains one of the main outputs of a study of internal migration among researchers in Mexico inferred from the affiliation addresses of Scopus publications from 1996-2018. Scopus data is owned and maintained by Elsevier.This dataset is provided under a CC BY-NC-SA Creative Commons v 4.0 license (Attribution-NonCommercial-ShareAlike). This means that other individuals may remix, tweak, and build upon these data non-commercially, as long as they provide citations to this data repository (10.6084/m9.figshare.12619016) and the reference articles listed below, and license the new creations under the identical terms. For more details about the study, please refer toMiranda-González, Andrea, Samin Aref, Tom Theile, and Emilio Zagheni. "Scholarly migration within Mexico: Analyzing internal migration among researchers using Scopus longitudinal bibliometric data." EPJ Data Science (2020). https://doi.org/10.1140/epjds/s13688-020-00252-9The dataset is provided in a comma-separated values file (.csv file) and each row represents one movement of one researcher-active scholar from a state (source) to another state (target) in Mexico in a specific year (move_year). The data can be used to produce internal migration flows for the states or possibly other migration estimates. It can also be used as an edge-list for creating a network model of migration events between states (states being the nodes of the network and each movement being represented as a directed edge from source to target).A zip file of annual networks (directed and weighted) in gml format is also provided.