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Transportation Services Index and Seasonally-Adjusted Transportation Data
data.bts.gov | Last Updated 2024-06-13T15:00:20.000ZAbout Transportation Services Index The Transportation Services Index (TSI), created by the U.S. Department of Transportation (DOT), Bureau of Transportation Statistics (BTS), measures the movement of freight and passengers. The index, which is seasonally adjusted, combines available data on freight traffic, as well as passenger travel, that have been weighted to yield a monthly measure of transportation services output. For charts and discussion on the relationship of the TSI to the economy, see our Transportation as an Economic Indicator: Transportation Services Index page (https://data.bts.gov/stories/s/TET-indicator-1/9czv-tjte) For release schedule see: https://www.bts.gov/newsroom/transportation-services-index-release-schedule About seasonally-adjusted data Statisticians use the process of seasonal-adjustment to uncover trends in data. Monthly data, for instance, are influenced by the number of days and the number of weekends in a month as well as by the timing of holidays and seasonal activity. These influences make it difficult to see underlying changes in the data. Statisticians use seasonal adjustment to control for these influences. Controlling of seasonal influences allows measurement of real monthly changes; short and long term patterns of growth or decline; and turning points. Data for one month can be compared to data for any other month in the series and the data series can be ranked to find high and low points. Any observed differences are “real” differences; that is, they are differences brought about by changes in the data and not brought about by a change in the number of days or weekends in the month, the occurrence or non-occurrence of a holiday, or seasonal activity.
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Great Lakes St. Lawrence Seaway Performance
data.bts.gov | Last Updated 2024-06-21T19:03:15.000ZThis dataset contains monthly performance statistics for the Great Lakes-St. Lawrence Seaway system.
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Sales Tax Collections by State
data.bts.gov | Last Updated 2024-07-02T13:02:23.000ZMonthly state sales tax collections is an experimental dataset published by the U.S. Census Bureau. It provides data for collections from sales taxes including motor fuel taxes. Data reported for a specific month generally represent sales taxes collected on sales made during the prior month. Tax collections primarily rely on unaudited data collected from existing state reports or state data sources available from and posted on the Internet. Secondarily, states report the data via the Quarterly Survey of State and Local Tax Revenue. Data are updated monthly, but due to differing reporting cycles data for some states may lag.
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Bikeshare (Docked and Dockless) and E-scooter Systems 2020 by Month and System Status
data.bts.gov | Last Updated 2024-02-23T20:58:57.000ZList of cities served by a bikeshare (docked or dockless) and/or e-scooter system by month in 2020. Some systems serve more than one city. The layer lists just the primary city served. Bikeshare includes systems that are open to the general public, IT-automated, and station based (contain hubs to which users can grab and return a bike) as well as dockless systems. The layer includes a count of the number of docking stations, the number of dockless bikeshare systems, and the number of e-scooter systems serving a city (if applicable) in each month and the status of the system - whether temporarily suspended or closed. Many systems temporarily suspended operations and/or closed permanently in response to COVID-19.
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Rail Freight Carloads (Seasonally Adjusted)
data.bts.gov | Last Updated 2024-06-13T15:00:20.000ZRelease Note BTS is withholding the scheduled release of the passenger and combined indexes for January. The passenger index is a statistical estimate of airline passenger travel and other components based on historical trends up to December 2019. As a result, the estimates have yet to fully account for the impact of the coronavirus. Air freight is also a statistical estimate. Since air freight makes up a smaller part of the freight index, the freight TSI is being released as scheduled. Description Statisticians use the process of seasonal-adjustment to uncover trends in data. Monthly data, for instance, are influenced by the number of days and the number of weekends in a month as well as by the timing of holidays and seasonal activity. These influences make it difficult to see underlying changes in the data. Statisticians use seasonal adjustment to control for these influences. Controlling of seasonal influences allows measurement of real monthly changes; short and long term patterns of growth or decline; and turning points. Data for one month can be compared to data for any other month in the series and the data series can be ranked to find high and low points. Any observed differences are “real” differences; that is, they are differences brought about by changes in the data and not brought about by a change in the number of days or weekends in the month, the occurrence or non-occurrence of a holiday, or seasonal activity.
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U.S. Air Carrier Passenger Travel (Not Seasonally Adjusted)
data.bts.gov | Last Updated 2024-06-13T15:00:20.000ZRelease Note BTS is withholding the scheduled release of the passenger and combined indexes for January. The passenger index is a statistical estimate of airline passenger travel and other components based on historical trends up to December 2019. As a result, the estimates have yet to fully account for the impact of the coronavirus. Air freight is also a statistical estimate. Since air freight makes up a smaller part of the freight index, the freight TSI is being released as scheduled. Description Statisticians use the process of seasonal-adjustment to uncover trends in data. Monthly data, for instance, are influenced by the number of days and the number of weekends in a month as well as by the timing of holidays and seasonal activity. These influences make it difficult to see underlying changes in the data. Statisticians use seasonal adjustment to control for these influences. Controlling of seasonal influences allows measurement of real monthly changes; short and long term patterns of growth or decline; and turning points. Data for one month can be compared to data for any other month in the series and the data series can be ranked to find high and low points. Any observed differences are “real” differences; that is, they are differences brought about by changes in the data and not brought about by a change in the number of days or weekends in the month, the occurrence or non-occurrence of a holiday, or seasonal activity.
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Rail Freight Carloads (Not Seasonally Adjusted)
data.bts.gov | Last Updated 2024-06-13T15:00:20.000ZRelease Note BTS is withholding the scheduled release of the passenger and combined indexes for January. The passenger index is a statistical estimate of airline passenger travel and other components based on historical trends up to December 2019. As a result, the estimates have yet to fully account for the impact of the coronavirus. Air freight is also a statistical estimate. Since air freight makes up a smaller part of the freight index, the freight TSI is being released as scheduled. Description Statisticians use the process of seasonal-adjustment to uncover trends in data. Monthly data, for instance, are influenced by the number of days and the number of weekends in a month as well as by the timing of holidays and seasonal activity. These influences make it difficult to see underlying changes in the data. Statisticians use seasonal adjustment to control for these influences. Controlling of seasonal influences allows measurement of real monthly changes; short and long term patterns of growth or decline; and turning points. Data for one month can be compared to data for any other month in the series and the data series can be ranked to find high and low points. Any observed differences are “real” differences; that is, they are differences brought about by changes in the data and not brought about by a change in the number of days or weekends in the month, the occurrence or non-occurrence of a holiday, or seasonal activity.
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Rail Passenger Travel (Not Seasonally Adjusted)
data.bts.gov | Last Updated 2024-06-13T15:00:20.000ZRelease Note BTS is withholding the scheduled release of the passenger and combined indexes for January. The passenger index is a statistical estimate of airline passenger travel and other components based on historical trends up to December 2019. As a result, the estimates have yet to fully account for the impact of the coronavirus. Air freight is also a statistical estimate. Since air freight makes up a smaller part of the freight index, the freight TSI is being released as scheduled. Description Statisticians use the process of seasonal-adjustment to uncover trends in data. Monthly data, for instance, are influenced by the number of days and the number of weekends in a month as well as by the timing of holidays and seasonal activity. These influences make it difficult to see underlying changes in the data. Statisticians use seasonal adjustment to control for these influences. Controlling of seasonal influences allows measurement of real monthly changes; short and long term patterns of growth or decline; and turning points. Data for one month can be compared to data for any other month in the series and the data series can be ranked to find high and low points. Any observed differences are “real” differences; that is, they are differences brought about by changes in the data and not brought about by a change in the number of days or weekends in the month, the occurrence or non-occurrence of a holiday, or seasonal activity.
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Truck Tonnage (Seasonally Adjusted Index)
data.bts.gov | Last Updated 2024-06-13T15:00:20.000ZRelease Note BTS is withholding the scheduled release of the passenger and combined indexes for January. The passenger index is a statistical estimate of airline passenger travel and other components based on historical trends up to December 2019. As a result, the estimates have yet to fully account for the impact of the coronavirus. Air freight is also a statistical estimate. Since air freight makes up a smaller part of the freight index, the freight TSI is being released as scheduled. Description Statisticians use the process of seasonal-adjustment to uncover trends in data. Monthly data, for instance, are influenced by the number of days and the number of weekends in a month as well as by the timing of holidays and seasonal activity. These influences make it difficult to see underlying changes in the data. Statisticians use seasonal adjustment to control for these influences. Controlling of seasonal influences allows measurement of real monthly changes; short and long term patterns of growth or decline; and turning points. Data for one month can be compared to data for any other month in the series and the data series can be ranked to find high and low points. Any observed differences are “real” differences; that is, they are differences brought about by changes in the data and not brought about by a change in the number of days or weekends in the month, the occurrence or non-occurrence of a holiday, or seasonal activity.
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U.S. Air Carrier Passenger Travel (Seasonally Adjusted)
data.bts.gov | Last Updated 2024-06-13T15:00:20.000ZRelease Note BTS is withholding the scheduled release of the passenger and combined indexes for January. The passenger index is a statistical estimate of airline passenger travel and other components based on historical trends up to December 2019. As a result, the estimates have yet to fully account for the impact of the coronavirus. Air freight is also a statistical estimate. Since air freight makes up a smaller part of the freight index, the freight TSI is being released as scheduled. Description Statisticians use the process of seasonal-adjustment to uncover trends in data. Monthly data, for instance, are influenced by the number of days and the number of weekends in a month as well as by the timing of holidays and seasonal activity. These influences make it difficult to see underlying changes in the data. Statisticians use seasonal adjustment to control for these influences. Controlling of seasonal influences allows measurement of real monthly changes; short and long term patterns of growth or decline; and turning points. Data for one month can be compared to data for any other month in the series and the data series can be ranked to find high and low points. Any observed differences are “real” differences; that is, they are differences brought about by changes in the data and not brought about by a change in the number of days or weekends in the month, the occurrence or non-occurrence of a holiday, or seasonal activity.