The total population in Mexico was estimated at 129.7 million people in 2023, according to the latest census figures and projections from Trading Economics. This dataset provides - Mexico Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset tabulates the data for the Mexico, MO population pyramid, which represents the Mexico population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Mexico, MO, is 28.5.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Mexico, MO, is 26.8.
• Total dependency ratio for Mexico, MO is 55.3.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Mexico, MO is 3.7.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Mexico population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Mexico for the selected age group is shown in the following column.
• Population (Female): The female population in the Mexico for the selected age group is shown in the following column.
• Total Population: The total population of the Mexico for the selected age group is shown in the following column.

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/.

Recommended for further research

This dataset is a part of the main dataset for Mexico Population by Age. You can refer the same here

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

Context

The data obtained from the Mexico's General Direction of Epidemiology contains multiple information on the current pandemic situation. However, these data are saturated with features that may not be very useful in a predictive analysis.

Due to this I decided to clean and format the original data and generate a dataset that groups confirmed, dead, recovered and active cases by State, Municipality and Date.

This is very useful if you want to generate geographically specific models

Content

The data set contains the covid cases columns (positive, dead, recovered and active) that are counted by state and municipality.

I.e

Would you like to see the data cleaning notebook? You can check it in my Github

Classification criteria

• Recovered cases: If the patient is not dead and it has been more than 15 days then he is considered as recovered.
• Active cases: If the patien isn't recovered an isn't dead then is active

Time lapse

The first documented case is on 2020-01-13. The dataset will be updated every day adding new cases

Acknowledgements

For this project, the data are obtained from the official URL of the government of México whose author is “Dirección General de Epidemiología”:

Corona Virus Data: https://www.gob.mx/salud/documentos/datos-abiertos-152127

Data Dictionary: https://www.gob.mx/salud/documentos/datos-abiertos-152127

Differences in results

According to the official results obtained from: https://coronavirus.gob.mx/datos/

• The main difference between the official data and this dataset is in the recovered cases. This is because the Mexican government only considers outpatient cases when counting recovered cases. This dataset considers outpatient and inpatient cases when counting recovered people.

• The second difference is some rows that contained nonsense information(I think this was a data collection error by the institution), these were eliminated.

The number of unemployed persons in Mexico decreased to 1490226 in the first quarter of 2025 from 1567775 in the fourth quarter of 2024. This dataset provides - Mexico Unemployed Persons - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset tabulates the population of New Mexico by race. It includes the population of New Mexico across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of New Mexico across relevant racial categories.

Key observations

The percent distribution of New Mexico population by race (across all racial categories recognized by the U.S. Census Bureau): 53.62% are white, 2.11% are Black or African American, 9.52% are American Indian and Alaska Native, 1.71% are Asian, 0.10% are Native Hawaiian and other Pacific Islander, 12% are some other race and 20.94% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the New Mexico
• Population: The population of the racial category (excluding ethnicity) in the New Mexico is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of New Mexico total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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/.

Recommended for further research

This dataset is a part of the main dataset for New Mexico Population by Race & Ethnicity. You can refer the same here

This project provides a comprehensive dataset of over 125,000 missing and unaccounted-for people in Mexico from the 1960s to 2025. The dataset is sourced from the publicly available records on the RNPDO website and represents individuals who were actively missing as of the date of collection (May 1, 2025). To protect individual identities, personal identifiers, such as names, have been removed.Dataset Features:The data has been cleaned and translated to facilitate analysis by a global audience.Fields include:SexDate of birthDate of incidenceState and municipality of the incidentData spans over six decades, offering insights into trends and regional disparities.Additional Materials:Python Script: A Python script to generate customizable visualizations based on the dataset. Users can specify the state to generate tailored charts.Sample Chart: An example chart showcasing the evolution of missing persons per 100,000 inhabitants in Mexico between 2006 and 2025.Requirements File: A requirements.txt file listing the necessary Python libraries to run the script seamlessly.This dataset and accompanying tools aim to support researchers, policymakers, and journalists in analyzing and addressing the issue of missing persons in Mexico.

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.

The number of employed persons in Mexico decreased to 59001009 in the first quarter of 2025 from 59487546 in the fourth quarter of 2024. This dataset provides - Mexico Employed Persons - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2015, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.

Introduction

Welcome to the Mexican Spanish Call Center Speech Dataset for the Telecom domain designed to enhance the development of call center speech recognition models specifically for the Telecom industry. This dataset is meticulously curated to support advanced speech recognition, natural language processing, conversational AI, and generative voice AI algorithms.

Speech Data

This training dataset comprises 30 Hours of call center audio recordings covering various topics and scenarios related to the Telecom domain, designed to build robust and accurate customer service speech technology.

Topic Diversity

This dataset offers a diverse range of conversation topics, call types, and outcomes, including both inbound and outbound calls with positive, neutral, and negative outcomes.

This extensive coverage ensures the dataset includes realistic call center scenarios, which is essential for developing effective customer support speech recognition models.

Transcription

To facilitate your workflow, the dataset includes manual verbatim transcriptions of each call center audio file in JSON format. These transcriptions feature:

These ready-to-use transcriptions accelerate the development of the Telecom domain call center conversational AI and ASR models for the Mexican Spanish language.

Metadata

The dataset provides comprehensive metadata for each conversation and participant:

Hospital Beds in Mexico remained unchanged at 1 per 1000 people in 2022 from 1 per 1000 people in 2021. This dataset includes a chart with historical data for Mexico Hospital Beds.

Unemployment Rate in Mexico increased to 2.50 percent in April from 2.20 percent in March of 2025. This dataset provides the latest reported value for - Mexico Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Cities can be tremendously efficient. It is easier to provide water and sanitation to people living closer together, while access to health, education, and other social and cultural services is also much more readily available. However, as cities grow, the cost of meeting basic needs increases, as does the strain on the environment and natural resources. Data on urbanization, traffic and congestion, and air pollution are from the United Nations Population Division, World Health Organization, International Road Federation, World Resources Institute, and other sources.

Introduction

Welcome to the Mexican Spanish Call Center Speech Dataset for the Retail domain designed to enhance the development of call center speech recognition models specifically for the Retail industry. This dataset is meticulously curated to support advanced speech recognition, natural language processing, conversational AI, and generative voice AI algorithms.

Speech Data

This training dataset comprises 30 hours of call center audio recordings covering various topics and scenarios related to the Retail domain, designed to build robust and accurate customer service speech technology.

Topic Diversity

This dataset offers a diverse range of conversation topics, call types, and outcomes, including both inbound and outbound calls with positive, neutral, and negative outcomes.

This extensive coverage ensures the dataset includes realistic call center scenarios, which is essential for developing effective customer support speech recognition models.

Transcription

To facilitate your workflow, the dataset includes manual verbatim transcriptions of each call center audio file in JSON format. These transcriptions feature:

These ready-to-use transcriptions accelerate the development of the Retail domain call center conversational AI and ASR models for the Mexican Spanish language.

Metadata

The dataset provides comprehensive metadata for each conversation and participant:

This metadata is a powerful tool for understanding and characterizing the data, enabling informed decision-making in the development of Mexican

I discovered and uploaded an intriguing dataset to Kaggle, showcasing official data from the Mexican government regarding the number of divorces in Xalapa, Mexico. This dataset encompasses approximately 4,900 divorce records.

What sets this dataset apart is its inclusion of each partner's birth date, a rarity in public datasets. This feature offers a unique opportunity to explore the zodiac signs of the partners and potentially discern any correlations between astrological signs and marital compatibility.

While astrology traditionally involves celestial objects like planets and stars, its purported influence is presumed to transcend nationalities and geographical locations.

Wages in Mexico increased to 621.89 MXN/Day in April from 619.29 MXN/Day in March of 2025. This dataset provides - Mexico Average Daily Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of United States by race. It includes the distribution of the Non-Hispanic population of United States across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of United States across relevant racial categories.

Key observations

Of the Non-Hispanic population in United States, the largest racial group is White alone with a population of 193.34 million (71.80% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the United States
• Population: The population of the racial category (for Non-Hispanic) in the United States is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of United States total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

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/.

Recommended for further research

This dataset is a part of the main dataset for United States Population by Race & Ethnicity. You can refer the same here

Hospitals in Mexico decreased to 38.50 per one million people in 2023 from 38.57 per one million people in 2022. This dataset includes a chart with historical data for Mexico Hospitals.

Introduction

Welcome to the Mexican Spanish Call Center Speech Dataset for the Travel domain designed to enhance the development of call center speech recognition models specifically for the Travel industry. This dataset is meticulously curated to support advanced speech recognition, natural language processing, conversational AI, and generative voice AI algorithms.

Speech Data:

This training dataset comprises 30 Hours of call center audio recordings covering various topics and scenarios related to the Travel domain, designed to build robust and accurate customer service speech technology.

Topic Diversity

This dataset offers a diverse range of conversation topics, call types, and outcomes, including both inbound and outbound calls with positive, neutral, and negative outcomes.

This extensive coverage ensures the dataset includes realistic call center scenarios, which is essential for developing effective customer support speech recognition models.

Transcription

To facilitate your workflow, the dataset includes manual verbatim transcriptions of each call center audio file in JSON format. These transcriptions feature:

These ready-to-use transcriptions accelerate the development of the Travel domain call center conversational AI and ASR models for the Mexican Spanish language.

Metadata

The dataset provides comprehensive metadata for each conversation and participant: