Exports in Mexico decreased to 44446.20 USD Million in January from 51687 USD Million in December of 2024. This dataset provides the latest reported value for - Mexico Exports - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The USDMXN increased 0.2404 or 1.20% to 20.3451 on Thursday March 27 from 20.1047 in the previous trading session. Mexican Peso - values, historical data, forecasts and news - updated on March of 2025.

American Labor Who's Who dataset, version 2.2.0

A dataset derived from the digitized text of Solon de Leon, et al., The American Labor Who's Who (New York: Hanford Press, 1925). This release includes separate files the U.S. and "Other Countries" sections of the directory.

The American Labor Who's Who (ALWW), published in 1925, is a directory of activists in the fields of trade unionism, immigrant rights, civil liberties, progressive and radical politics. The directory includes roughly 1,300 entries for U.S. activists and 300 additional non-US activists. Each entry is a telegraphic biography. Some provide only name, professional title and address at the time of publication, but many sketch rich life histories. Nearly all provide details on birth date and place, family background, education, migration, and work histories, as well as key organizations, events publications, home and work addresses.

The ALWW dataset is derived from the text hosted on the HathiTrust digital library: https://catalog.hathitrust.org/Record/000591300. Faculty, staff, and students at UCLA corrected the plain text from the scanned document and parsed the text into comma-separated fields. This release includes separate files for US entries and "Other Countries" entries. About 30 individuals are listed in the US section with the notation "see other countries," mainly Canadians and Mexicans. This subset is also in a separate file in this release.

For more information about this and related projects see: http://socialjusticehistory.org/projects/networkedlabor/.

Contributors Tobias Higbie, Principal Investigator, UCLA History Department Craig Messner, UCLA Center for Digital Humanities Nick de Carlo, UCLA Center for Digital Humanities Zoe Borovsky, UCLA Library

Contents of Release The US and Other Country datasets were developed separately as reflected in their different version numbers. The US entries are more developed and clean. Consider the Other Country files as beta releases. The files listed below are the most up-to-date available. Previous versions are also available via GitHub.

alww-us-2-2-0.csv (all US entries)

alww-othercountries-o.3.2.csv (all other country entries)

alww-othercountries-0.3.2-subset-crossrefd.csv (other country entries cross-referenced in the US entry section)

Field Layouts

The field layouts for the US and Other Country files are slightly different in this release.

US Entries The fields for the US file (alww-us-2-2-0.csv) include: NAME [first and last], NAME-ALWW [name as it appears in the original text], TITLES [named offices or occupations in 1925], ORGS [compiled list of organizations belonged to at any time], BIRTHDATES [m/d/y where present], BIRTHCOUNTRY [derived from Birthplace], BIRTHPLACE [as listed], FATHER [father's occupation, in a few cases includes mother], CAREER (UNABBREVIATED) [education and experience, usually chronological, most common abbreviations expanded to full words], CAREER (ABBREVIATED) [same as previous with original abbreviations], HOME ADDRESS [where present], WORK ADDRESS [where present], PUBLICATIONS [incomplete], INDEX CATEGORY 1 [categories derived from the ALWW index, many have more than one category], INDEX CATEGORY 2, INDEX CATEGORY 3, INDEX CATEGORY 4, INDEX CATEGORY 5, INDEX CATEGORY 6, INDEX CATEGORY 7, INDEX CATEGORY 8, ORIGINAL [unparsed entry text carried over from earlier versions].

Other Countries The other country files (alww-othercountries-o.3.2.csv and alww-othercountries-0.3.2-subset-crossrefd.csv) include these fields: Name [last, first], Titles [named offices or occupations in 1925], Organizations [compiled list of organizations belonged to at any time], Birthdate [as listed], Birthplace [as listed], Father [father's occupation], Other [same as Career above], HomeAddress [as listed], WorkAddress [as listed], Publications [derived from entries].

Related datasets American Labor Press Directory (1925); American Labor Press Directory (1940); Who's Who in Labor (1947).

The Bureau of Transportation Statistics (BTS) Border Crossing Data provide summary statistics for inbound crossings at the U.S.-Canada and the U.S.-Mexico border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Border crossing data are collected at ports of entry by U.S. Customs and Border Protection (CBP). The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States. CBP does not collect comparable data on outbound crossings. Users seeking data on outbound counts may therefore want to review data from individual bridge operators, border state governments, or the Mexican and Canadian governments.

This layer shows Hispanic or Latino origin by specific origin. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of the population with Hispanic or Latino origins. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2016-2020ACS Table(s): B03001 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: March 17, 2022The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis 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. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Projected Deaths by Single Year of Age, Sex, Race, and Hispanic Origin for the United States: 2016-2060 // Source: U.S. Census Bureau, Population Division // There are four projection scenarios: 1. Main series, 2. High Immigration series, 3. Low Immigration series, and 4. Zero Immigration series. // Note: Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. // For detailed information about the methods used to create the population projections, see https://www2.census.gov/programs-surveys/popproj/technical-documentation/methodology/methodstatement17.pdf. // Population projections are estimates of the population for future dates. They are typically based on an estimated population consistent with the most recent decennial census and are produced using the cohort-component method. Projections illustrate possible courses of population change based on assumptions about future births, deaths, net international migration, and domestic migration. The Population Estimates and Projections Program provides additional information on its website: https://www.census.gov/programs-surveys/popproj.html.

Long term historical dataset of the daily U.S. Dollar - Mexican Peso (USDMXN) exchange rate back to 1994.

This layer shows the population broken down by race and Hispanic origin. Data is from US Census American Community Survey (ACS) 5-year estimates.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2018-2022ACS Table(s): B03002 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data table was downloaded and joined with Zip Code boundaries in the City of Tempe.Date of Census update: December 15, 2023National Figures: data.census.gov

This data set contains lidar point data (UTM, Zone 11) from a strip of Southern California coastline (including water, beach, cliffs, and top of cliffs) from Long Beach to the US/Mexico border. The data set was created by combining data collected using an Optech Inc. Airborne Laser Terrain Mapper (ALTM) 1225 in combination with geodetic quality Global Positioning System (GPS) airborne and ground-based receivers. The Bureau of Economic Geology, the University of Texas at Austin owns and operates an ALTM 1225 system (serial number 99d118). The system was installed in a twin engine Partenavia P-68 Observer (tail number N6602L) owned and operated by Aspen Helicopter, Inc. The lidar data set described by this document was collected on 18 and 19 October 2005; Julian Days 29105 and 29205 (see Lineage, Source_Information, Source_Contribution for pass information). 99d118 instrument settings for these flights were; laser pulse rate: 25kHz, scanner rate: 26Hz, scan angle: +/- 20deg, beam divergence: narrow, altitude: 300-600m AGL, and ground speed: 95-120kts. Four GPS base stations, Seal Beach and San Onofre on 29105 and Point Loma and Scripps Pier on 29205 (see Lineage, Source_Information, Source_Contribution for coordinates), operated during the survey. Data represented is all points including terrain, vegetation, and structures. This data also contains returns from the water surface. No processing has been done to remove returns from terrain, vegetation, structures or water surfaces.

This page displays a table with Mexico Imports By Category in U.S. dollars, according to the United Nations COMTRADE database on international trade.