Consolidate Data

## Overview

Consolidate Data is a dataset for object detection tasks - it contains Ice Et Clear annotations for 815 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).

A complete list of live websites using the consolidate technology, compiled through global website indexing conducted by WebTechSurvey.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

The MERGE dataset is a collection of audio, lyrics, and bimodal datasets for conducting research on Music Emotion Recognition. A complete version is provided for each modality. The audio datasets provide 30-second excerpts for each sample, while full lyrics are provided in the relevant datasets. The amount of available samples in each dataset is the following:

• MERGE Audio Complete: 3554
• MERGE Audio Balanced: 3232
• MERGE Lyrics Complete: 2568
• MERGE Lyrics Balanced: 2400
• MERGE Bimodal Complete: 2216
• MERGE Bimodal Balanced: 2000

Additional Contents

Each dataset contains the following additional files:

• av_values: File containing the arousal and valence values for each sample sorted by their identifier;
• tvt_dataframes: Train, validate, and test splits for each dataset. Both a 70-15-15 and a 40-30-30 split are provided.

Metadata

A metadata spreadsheet is provided for each dataset with the following information for each sample, if available:

• Song (Audio and Lyrics datasets) - Song identifiers. Identifiers starting with MT were extracted from the AllMusic platform, while those starting with A or L were collected from private collections;
• Quadrant - Label corresponding to one of the four quadrants from Russell's Circumplex Model;
• AllMusic Id - For samples starting with A or L, the matching AllMusic identifier is also provided. This was used to complement the available information for the samples originally obtained from the platform;
• Artist - First performing artist or band;
• Title - Song title;
• Relevance - AllMusic metric representing the relevance of the song in relation to the query used;
• Duration - Song length in seconds;
• Moods - User-generated mood tags extracted from the AllMusic platform and available in Warriner's affective dictionary;
• MoodsAll - User-generated mood tags extracted from the AllMusic platform;
• Genres - User-generated genre tags extracted from the AllMusic platform;
• Themes - User-generated theme tags extracted from the AllMusic platform;
• Styles - User-generated style tags extracted from the AllMusic platform;
• AppearancesTrackIDs - All AllMusic identifiers related with a sample;
• Sample - Availability of the sample in the AllMusic platform;
• SampleURL - URL to the 30-second excerpt in AllMusic;
• ActualYear - Year of song release

Acknowledgements

This work is funded by FCT - Foundation for Science and Technology, I.P., within the scope of the projects: MERGE - DOI: 10.54499/PTDC/CCI-COM/3171/2021 financed with national funds (PIDDAC) via the Portuguese State Budget; and project CISUC - UID/CEC/00326/2020 with funds from the European Social Fund, through the Regional Operational Program Centro 2020.

Renato Panda was supported by Ci2 - FCT UIDP/05567/2020.

Merge Dataset

## Overview

Merge Dataset is a dataset for computer vision tasks - it contains Human Pose annotations for 4,025 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).

Dataset

This dataset was created by Kechu

Contents

Hap Seng Consolidate - Aktualne wartości, dane historyczne, prognozy, statystyki, wykresy i kalendarz ekonomiczny - Mar 2025.Data for Hap Seng Consolidate including historical, tables and charts were last updated by Trading Economics this last March in 2025.

Romania MFIs: Assets: Consolidate: Net data was reported at 571,446.117 RON mn in Sep 2018. This records an increase from the previous number of 566,937.025 RON mn for Aug 2018. Romania MFIs: Assets: Consolidate: Net data is updated monthly, averaging 472,778.465 RON mn from Jan 2007 (Median) to Sep 2018, with 141 observations. The data reached an all-time high of 571,446.117 RON mn in Sep 2018 and a record low of 198,304.442 RON mn in Jan 2007. Romania MFIs: Assets: Consolidate: Net data remains active status in CEIC and is reported by National Bank of Romania. The data is categorized under Global Database’s Romania – Table RO.KB016: Balance Sheet: Monetary Financial Institutions.

Romania MFIs: Assets: Consolidate: Net: Domestic: Shares & Others data was reported at 2,719.898 RON mn in Sep 2018. This records an increase from the previous number of 2,706.376 RON mn for Aug 2018. Romania MFIs: Assets: Consolidate: Net: Domestic: Shares & Others data is updated monthly, averaging 1,829.020 RON mn from Jan 2007 (Median) to Sep 2018, with 141 observations. The data reached an all-time high of 3,168.908 RON mn in Dec 2015 and a record low of 523.246 RON mn in Jan 2007. Romania MFIs: Assets: Consolidate: Net: Domestic: Shares & Others data remains active status in CEIC and is reported by National Bank of Romania. The data is categorized under Global Database’s Romania – Table RO.KB016: Balance Sheet: Monetary Financial Institutions.

Hap Seng Consolidate 주식 - 현재 값, 이력 데이터, 예측, 통계, 차트 및 경제 달력 - Mar 2025.Data for Hap Seng Consolidate | 주식 including historical, tables and charts were last updated by Trading Economics this last March in 2025.

Hap Seng Consolidate هزینه بهره بدهی - ارزش های فعلی، داده های تاریخی، پیش بینی، آمار، نمودار و تقویم اقتصادی - Mar 2025.Data for Hap Seng Consolidate | هزینه بهره بدهی including historical, tables and charts were last updated by Trading Economics this last March in 2025.

Credit report of Bnb Consolidate contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

Posted quarterly, using FDCCI Task Force data reported to OMB through the quarterly Integrated Data Collection (IDC) deadline. Federal Data Center Consolidation Initiative (FDCCI) Data Center Closures 2010-2015. Under the FDDCI, agencies have categorized their agency data center populations into two categories: core and non-core. The government is closing 40% of agency-identified, non-core data centers, while optimizing agency-identified core-data centers, according to a series of total cost of ownership metrics (see OMB M-13-09 and OMB M-14-08). This dataset reflects information only for agency-identified, non-core closures. All questions or inquiries should be directed to the specific agencies. The FY2010 through FY2015 dataset provides a list of planned or closed data centers by agency and by city/state location since the FDCCI started. Please note ?OTHER? is listed for data centers in cloud, co-located or managed service data centers, where square footage is unavailable. See related information about the FDCCI, including the definition of a data center and other FAQs at http://cio.gov/fdcci.

Dataset Card for YouTubeTranscriptData

  Dataset Details







  Dataset Description

This dataset contains transcripts of around 167K youtube videos that include coding lectures, podcasts, interviews, news videos, commentary and song lyrics. Also there are multiple files that have been generated using webscrapping.

Curated by: Shivendra Singh License: [none]

  Dataset Sources

Repository: SmallLanguageModel Demo [optional]: [More Information… See the full description on the dataset page: https://huggingface.co/datasets/shivendrra/consolidated-datasets.

Romania MFIs: Assets: Consolidate: Net: Foreign data was reported at 219,243.425 RON mn in Sep 2018. This records a decrease from the previous number of 219,251.095 RON mn for Aug 2018. Romania MFIs: Assets: Consolidate: Net: Foreign data is updated monthly, averaging 174,224.654 RON mn from Jan 2007 (Median) to Sep 2018, with 141 observations. The data reached an all-time high of 228,035.520 RON mn in Mar 2018 and a record low of 87,737.943 RON mn in Jul 2007. Romania MFIs: Assets: Consolidate: Net: Foreign data remains active status in CEIC and is reported by National Bank of Romania. The data is categorized under Global Database’s Romania – Table RO.KB016: Balance Sheet: Monetary Financial Institutions.

Romania MFIs: Liabilities: Consolidate: Net data was reported at 555,171.928 RON mn in Jun 2018. This records a decrease from the previous number of 562,704.353 RON mn for May 2018. Romania MFIs: Liabilities: Consolidate: Net data is updated monthly, averaging 472,277.608 RON mn from Jan 2007 (Median) to Jun 2018, with 138 observations. The data reached an all-time high of 562,704.353 RON mn in May 2018 and a record low of 198,304.441 RON mn in Jan 2007. Romania MFIs: Liabilities: Consolidate: Net data remains active status in CEIC and is reported by National Bank of Romania. The data is categorized under Global Database’s Romania – Table RO.KB017: Balance Sheet: Monetary Financial Institutions.

Romania MFIs: Assets: Consolidate: Net: Domestic: Credit: Government data was reported at 9,205.582 RON mn in Sep 2018. This records an increase from the previous number of 9,166.319 RON mn for Aug 2018. Romania MFIs: Assets: Consolidate: Net: Domestic: Credit: Government data is updated monthly, averaging 9,662.423 RON mn from Jan 2007 (Median) to Sep 2018, with 141 observations. The data reached an all-time high of 11,787.718 RON mn in Jun 2010 and a record low of 2,637.905 RON mn in Jan 2007. Romania MFIs: Assets: Consolidate: Net: Domestic: Credit: Government data remains active status in CEIC and is reported by National Bank of Romania. The data is categorized under Global Database’s Romania – Table RO.KB016: Balance Sheet: Monetary Financial Institutions.

Dataset Multiple Combine

## Overview

Dataset Multiple Combine is a dataset for object detection tasks - it contains Handwritten Digits MHok Handwritten Digits One GznX annotations for 1,833 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).

The Consolidated Lunar Atlas is a collection of the best photographic images of the moon, including low-oblique photography, full-moon photography, and tabular and positional plates.

This layer shows total population counts by sex, age, and race groups data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, Consolidated City, Census Designated Place, Incorporated Place boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P2, P3, P5, P12, P13, P17, PCT12 (Not all lines of these DHC tables are available in this feature layer.)Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, 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 and block group 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 unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.