If you have geographic information stored as a table, ArcGIS Pro can display it on a map and convert it to spatial data. In this tutorial, you'll create spatial data from a table containing the latitude-longitude coordinates of huts in a New Zealand national park. Huts in New Zealand are equivalent to cabins in the United States—they may or may not have sleeping bunks, kitchen facilities, electricity, and running water. The table of hut locations is stored as a comma-separated values (CSV) file. CSV files are a common, nonproprietary file type for tabular data.Estimated time: 45 minutesSoftware requirements: ArcGIS Pro

This dataset is about: (Table T2) Tie points used to create the revised composite depth section for ODP Site 198-1209. Please consult parent dataset @ https://doi.org/10.1594/PANGAEA.778035 for more information.

SwiftXponse Key Point Table

## Overview

SwiftXponse Key Point Table is a dataset for computer vision tasks - it contains Edges annotations for 465 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

DOI retrieved: 2012

Statewide Download (FGDB) (SHP)Users can also download smaller geographic areas of this feature service in ArcGIS Pro using the Copy Features geoprocessing tool. The address service contains statewide address points and related landmark name alias table and street name alias table.The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The existing New Jersey Statewide Address Point data last published in 2016 has been transformed in the NENA data model to create this new address point data.The initial address points were processed from statewide parcel records joined with the statewide Tax Assessor's (MOD-IV) database in 2015. Address points supplied by Monmouth County, Sussex County, Morris County and Montgomery Township in Somerset County were incorporated into the statewide address points using customized Extract, Transform and Load (ETL) procedures.The previous version of the address points was loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. Subsequent manual and bulk processing corrections and additions have been made, and are ongoing.***NOTE*** For users who incorporate NJOGIS services into web maps and/or web applications, please sign up for the NJ Geospatial Forum discussion listserv for early notification of service changes. Visit https://nj.gov/njgf/about/listserv/ for more information.

DOI retrieved: 2015

Geospatial Data Pack for Visualization 🗺️

Learn Geographic Mapping with Altair, Vega-Lite and Vega using Curated Datasets

Complete geographic and geophysical data collection for mapping and visualization. This consolidation includes 18 complementary datasets used by 31+ Vega, Vega-Lite, and Altair examples 📊. Perfect for learning geographic visualization techniques including projections, choropleths, point maps, vector fields, and interactive displays.

Source data lives on GitHub and can also be accessed via CDN. The vega-datasets project serves as a common repository for example datasets used across these visualization libraries and related projects.

Why Use This Dataset? 🤔

• Comprehensive Geospatial Types: Explore a variety of core geospatial data models:
  • Vector Data: Includes points (like airports.csv), lines (like londonTubeLines.json), and polygons (like us-10m.json).
  • Raster-like Data: Work with gridded datasets (like windvectors.csv, annual-precip.json).
• Diverse Formats: Gain experience with standard and efficient geospatial formats like GeoJSON (see Table 1, 2, 4), compressed TopoJSON (see Table 1), and plain CSV/TSV (see Table 2, 3, 4) for point data and attribute tables ready for joining.
• Multi-Scale Coverage: Practice visualization across different geographic scales, from global and national (Table 1, 4) down to the city level (Table 1).
• Rich Thematic Mapping: Includes multiple datasets (Table 3) specifically designed for joining attributes to geographic boundaries (like states or counties from Table 1) to create insightful choropleth maps.
• Ready-to-Use & Example-Driven: Cleaned datasets tightly integrated with 31+ official examples (see Appendix) from Altair, Vega-Lite, and Vega, allowing you to immediately practice techniques like projections, point maps, network maps, and interactive displays.
• Python Friendly: Works seamlessly with essential Python libraries like Altair (which can directly read TopoJSON/GeoJSON), Pandas, and GeoPandas, fitting perfectly into the Kaggle notebook environment.

Table of Contents

• Why Use This Dataset?
• Dataset Inventory
• Usage Guide
• Appendix: Geospatial Examples by Technique
• Licenses
• Sources
• Learning Resources

Dataset Inventory 🗂️

This pack includes 18 datasets covering base maps, reference points, statistical data for choropleths, and geophysical data.

1. BASE MAP BOUNDARIES (Topological Data)

2. GEOGRAPHIC REFERENCE POINTS (Point Data) 📍

The US Geological Survey's Upper Midwest Environmental Sciences Center, in coordination with the US Fish and Wildlife Service's (USFWS) Branch of Migratory Bird Surveys, worked to develop, survey, and deploy an advanced aerial photography boresight in the town of Monroe, Louisiana. The intention of this boresight is to provide an extensive array of high-accuracy ground control points for the development of camera metrics on novel camera systems managed and deployed by the USFWS.

No description is available. Visit https://dataone.org/datasets/37f3714752bb28e3a0b9c14355e0a54b for complete metadata about this dataset.

Table Tennis Table

## Overview

Table Tennis Table is a dataset for computer vision tasks - it contains Key Points Of The Corner annotations for 250 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Several continental football/soccer championships are taking place at the moment such as the Euro 2024 and 2024 Copa América, so let’s have a project on soccer/football.

Tasks

1. Generate a league table with columns for Club, Played, Won, Drawn, Lost, GF, GA, GD, Points as you would see in a typical English Premier League Table
2. Create a bar chart of Total Points Earned (Points) sorted in descending order
3. Create a bar chart of Total Goals scored in favour (GF) sorted in descending order
4. Create a bar chart of Total Goals scored against (GA) sorted in descending order
5. Create a bar chart of Total Goals Difference (GD) sorted in descending order

The state of Tennessee is divided into 805 individual 7.5-minute topographic quadrangle maps. The Tennessee Department of Environment and Conservation (TDEC) maintains an archive of paper maps that were utilized for estimating groundwater well locations. Each well location was plotted by hand and marked with corresponding water well data. These hand-plotted locations represent the most accurate spatial information for each well but solely exist in paper format. To create a shapefile of the well location data for this data release, individual paper maps were scanned and georeferenced. From these georeferenced map images (GRI), the hand-plotted well locations were digitized, and a shapefile of point data was created. Attribute table data include quad name, drawing number, and hand-written identification data that was transcribed from the topographic maps. Latitude and longitude coordinates (decimal degrees) were populated and incorporated into the attribute table. The projection is USA Contiguous Albers Equal Area Conic USGS (meters). Detailed descriptions of the attributes can be found in the accompanying metadata files. Shapefile and metadata files can be located in child item for the quadrangle (sorted alphabetically).

Geotechnical reports are indexed within a database maintained by HPW-TEB Geotechnical Unit. Meta data associated to each geotechnical report are captured within this indexing table, including report reference number, title, author, highway and km start and end. The table has been modified to include columns that aid in georeferencing geotechnical reports. Added columns include route ID, Latitude, and Longitude. Transportation Engineering Branch is continually improving its geographical information systems with a major focus on creating linear referencing routes within ArcGIS. Georeferencing geotechnical reports will utilize the linear referencing routes in creating points and line shape files by referencing the highway number and km points or ranges as defined within the indexing table. Distributed from GeoYukon by the Government of Yukon . Discover more digital map data and interactive maps from Yukon's digital map data collection. For more information: geomatics.help@yukon.ca

Data in this Address_Points layer was loaded from the interim Building_Points_Joined layer, the result of a spatial join performed between Building_Points (centroids) and Parcels.The Building_Points layer was created on 11/ 08/2013 using the Feature to Point geoprocessing tool; input feature class was Building_Footprints_2010.Process outline:Create a copy of Building_Footprints_2010 in a local, file geodatabasePerform Feature to Point on copy of Building_Footprints_2010; result - Building_PointsPerform spatial join of Parcels to Building_Points; give each point the attribute values of the parcel within which it fallsAdd fields to Building_Points_Joined (FULLNAME, ADDRNUMSUF, ADDRCLASS) and calculate based on values in other attribute fieldsFULLNAME values are the result of a function which concacatenated, then trimmed, using STREET_DIR, STREET_NAM, STREET_TYP from the Parcels table.ADDRNUMSUF values are the result of a parsing operation in which '1/2' addresses were split from applicable HOUSE values. ADDRCLASS values resulted from a calculation based on the Parcels' BLDG_TYPE field.Data loaded to SiteAddressPoint feature class in a local gdb, sourced by Building_Points_Joined.SiteAddressPoint feature class copied to vector.GIS sdeSITEADDID calculated by GENERATE_ID value method using the DynamicValue table.On_Create rule established for SITEADDID when new features are created.Municipality calculated by INTERSECTING_FEATURE value method using the Dynamic Value table.CAPTUREMETH populated with value 'Other' to match the PointCollectionMethoddomain for that field.ZIP will require calculation when a reliable ZIP Codes layer has been secured. Questions? Contact Us

The US Geological Survey's Upper Midwest Environmental Sciences Center, in coordination with the US Fish and Wildlife Service's (USFWS) Branch of Migratory Bird Surveys, worked to develop, survey, and deploy an advanced aerial photography boresight in the town of Bangor, Maine. The intention of this boresight is to provide an extensive array of high-accuracy ground control points for the development of camera metrics on novel camera systems managed and deployed by the USFWS.

The Global Table Lamp market size was USD XX million in 2024. The Table Lamp market will show the strongest growth, with a compound annual growth rate (CAGR) of XX% from 2024 to 2031.

North America held the largest share of XX% in the year 2024 
Europe held a share of XX% in the year 2024 
Asia-Pacific held a significant share of XX% in the year 2024 
South America held a significant share of XX% in the year 2024
Middle East and Africa held a significant share of XX% in the year 2024 

Key drivers for Table Lamp Market

Rising demand for aesthetic and beautiful décor lamps is driving the market growth for table lamps 

People, nowadays, are prioritizing how their homes look and aesthetic and eye-catching furniture is increasingly being demand for this purpose. Table lamps, which are decorative or minimalistic, or smart-light featured, in recent years, have become a significant aspect of any décor as they enhance the ambience of the setting with the ideal bulb, shape, shade, and color.

For instance, Vintage filament bulb lamps bring old-world charm into living spaces. These trendy pieces emit a warm, inviting glow that enhances ambience. It is suggested that they should be placed on bedside tables or work desks for soft lighting, or it can also be grouped together on a console table to create a captivating center piece. For office spaces, trend of optical illusion lamps has been in demand, specifically those that causes Illusions of Light. It provides a mesmerizing aesthetic and plays with perspectives, making the observers question. They are a versatile decor piece, as it is also suitable for creating a focal point on bedside tables or office desks. Furthermore, a table lamp for dining tables or bedrooms with designs that reflect the occasion and set the mood for a romantic dinner also contributes to the growth of aesthetically pleasing table lamps. For example, a heart-shaped lamp or one with floral designs can be used for the theme of love and romance. A red, pink, or green bulb, such as The Beige and Gold Italian Mesh Decorative Ceramic & Stainless Steel Table Lamp With Green Shade for instance, can set a passionate and relaxed atmosphere.

According to the Ellementry Home & Gifting, lamps are one of the crucial elements that should be present in the bedroom because of several reasons supporting inclusion. Firstly, when the over-full room or if the ceiling doesn’t complement the height of the room, these lamps will do justice and offset the blunders in room decor. Although tube lights brighten the room, some portions or corners of the room do not get the required lighting, thus, a bulb-fitted lamp is perfect for those under-covered areas which makes them aesthetically beautiful corners. These beautiful lamps also enhance and bring the desired jovial mood all together. Thus, rising demand for aesthetic and beautiful décor lamps is driving the market growth for table lamps.

Restraints for Table Lamp Market

Fluctuating raw material costs and supply chain disruptions hinder the market growth for table lamps 

The price volatility of the raw materials making the table lamps, significantly affects the table lamp production. The raw materials used in the production of table lamps are ceramic, steel, metal, aluminum, paper, plastic, and more. For instance, the ceramic sector heavily depends on gas supply for production, thus, it will face, a respective crisis as a result of fluctuating prices of gas. Gas is one of the main raw materials of the ceramic industry as about 12% of the total production cost of ceramic products goes to gas. In 2022, gas prices were increased by 40% more in two phases, thus, the latest 155% price hike in 2023 puts the users of ceramic in danger. As a result, it is difficult for the entrepreneurs of this sector to survive. Moreover, the freight charge increases caused by the Russia-Ukraine war negatively affect the supply chain and the production costs as well. Furthermore, in the production of glass, producing the glass itself needs a lot of energy and is therefore specifically affected by the high procurement prices. So, as a result, the lighting industry passes on this increasing price to consumers as glass is incorporated in the making of glass table lamps. On the other side, the distances between the manufacturers, lamp make...

Observations from the HERschel Inventory of the Agents of Galaxy Evolution (HERITAGE) have been used to identify dusty populations of sources in the Large and Small Magellanic Clouds (LMC and SMC).The study used the HERITAGE catalogs of point sources from both the Photodetector Array Camera and Spectrometer (PACS; 100 and 160 microns) and Spectral and Photometric Imaging Receiver (SPIRE; 250, 350, and 500 microns) cameras. These catalogs are matched to each other to create a Herschel band-merged catalog and then further matched to archival Spitzer IRAC and MIPS catalogs from the Spitzer Surveying the Agents of Galaxy Evolution (SAGE) and SAGE-SMC surveys to create single mid- to far-infrared (far-IR) point source catalogs that span the wavelength range from 3.6 to 500 microns. There are 35,322 unique sources in the LMC and 7503 in the SMC.The Band-Matched Classification Tables identify matches to literature catalogs of previously classified LMC and SMC objects.

No description is available. Visit https://dataone.org/datasets/1c8197da4e2832422bbb642560cc1ab7 for complete metadata about this dataset.

Table Rock Lake was constructed in 1958 on the White River in southwest Missouri and northwest Arkansas for flood control, hydroelectric power, public water supply, and recreation. The surface area of Table Rock Lake is about 42,400 acres and approximately 715 miles of shoreline are at the conservation pool level (915 feet above the North American Vertical Datum of 1988). Sedimentation in reservoirs can result in reduced water storage capacity and a reduction in usable aquatic habitat. Therefore, accurate and up-to-date estimates of reservoir water capacity are important for managing pool levels, power generation, water supply, recreation, and downstream aquatic habitat. Many of the lakes operated by the U.S. Army Corps of Engineers are periodically surveyed to monitor bathymetric changes that affect water capacity. During October and November 2020, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, completed one such survey of Table Rock Lake using multibeam echosounders. The echosounder data was combined with light detection and ranging (lidar) data to prepare a bathymetric map and a surface area and capacity table. Collection of bathymetric data in October and November 2020 at Table Rock Lake near Branson, Missouri, used marine-based mobile mapping units that operate with several components: a multibeam echosounder (MBES) unit, an inertial navigation system (INS), and a data acquisition computer. Bathymetric data were collected using the MBES units in longitudinal transects to provide complete coverage of the lake. The MBES systems were electronically or physically tilted in some areas to improve data collection along the shoreline, in coves, and in areas that are shallower than 2.5 meters deep (the practical limit of reasonable and safe data collection with the MBES). The bathymetric data collected during the 2020 survey (TableRockLake2020_bathy_pts.zip) were gridded on a 6.56-foot (2-meter) grid using the Combined Uncertainty and Bathymetry Estimator (CUBE) method and were the source of points to create the bathymetric surface of the lake. The gridded bathymetric point data were quality-assured with data from 42 selected resurvey areas (TableRockLake2020_QA_raw.zip) to test the accuracy of the gridded bathymetric point data. The two bathymetry datasets are provided as comma-delimited text files that have been compressed into zip archives. Attribute/column labels of each dataset are described in the "Entity and attribute" section of the metadata file.

KidsÂ’ Table Market Outlook

According to our latest research, the global kidsÂ’ table market size reached USD 2.18 billion in 2024, demonstrating a robust growth trajectory. The market is expected to register a CAGR of 6.2% from 2025 to 2033, with the total market value anticipated to reach USD 3.76 billion by 2033. This growth is primarily driven by increasing parental focus on child development and comfort, coupled with the rising demand for multifunctional and ergonomically designed children's furniture.

One of the key growth factors propelling the kidsÂ’ table market is the heightened awareness among parents and caregivers regarding the importance of creating dedicated learning and play spaces for children. With early childhood development recognized as a critical phase, parents are investing in furniture that not only supports educational activities but also ensures safety and comfort. The market has seen a surge in demand for tables designed specifically for childrenÂ’s ergonomics, promoting correct posture and reducing the risk of musculoskeletal disorders. Additionally, the growing prevalence of nuclear families and urbanization has led to a rise in compact, space-saving furniture solutions, further boosting the adoption of kidsÂ’ tables in modern households.

Another significant driver is the increasing adoption of kidsÂ’ tables within educational and childcare settings, such as schools and daycare centers. As educational institutions place greater emphasis on interactive and collaborative learning environments, there is a rising need for furniture that can accommodate group activities and foster social interaction among children. This trend is particularly notable in developed regions, where investments in early childhood infrastructure are substantial. Furthermore, the integration of flexible, adjustable, and modular table designs is gaining traction, enabling institutions to adapt furniture layouts to diverse teaching methods and classroom sizes. This shift is expected to continue fueling demand for innovative kidsÂ’ tables throughout the forecast period.

The proliferation of e-commerce platforms and specialty furniture retailers has also played a pivotal role in expanding the kidsÂ’ table market. Online channels provide consumers with access to a wide array of designs, materials, and price points, making it easier for parents and organizations to find products that suit their specific needs. The convenience of home delivery and the availability of detailed product information online have further accelerated market growth. Additionally, manufacturers are leveraging digital marketing strategies and influencer partnerships to reach tech-savvy parents, amplifying brand visibility and driving sales. The convergence of these factors is expected to sustain the upward momentum of the kidsÂ’ table market in the coming years.

In addition to the growing demand for ergonomic and multifunctional furniture, the market is also witnessing a rising interest in specialized products like the Changing Table. This particular piece of furniture has become an essential item for parents, offering a dedicated space for diaper changes and other infant care activities. The Changing Table is designed to provide convenience and safety, often featuring storage compartments for easy access to baby essentials. Its popularity is driven by the increasing focus on creating organized and functional nursery spaces, as well as the trend towards compact living solutions that maximize utility in smaller homes. As families continue to prioritize both practicality and aesthetics in their children's furniture, the Changing Table is expected to see sustained demand across various regions.

Regionally, Asia Pacific is emerging as a dominant force in the kidsÂ’ table market, fueled by rapid urbanization, rising disposable incomes, and a growing focus on child-centric products. Countries such as China and India are witnessing a boom in the middle-class population, which is translating into increased spending on children's furniture. North America and Europe continue to be significant markets, characterized by high consumer awareness and a strong presence of leading brands. Meanwhile, the Middle East & Africa and Latin America are gradually catching up, driven by improving economic conditions and expanding retail infrastructure. This diverse regional la