Comprehensive market data and analytics for D/D/D WAVE HIGH KING CAESAR - SR - YU-GI-OH! - COTD-EN042- 1ST ED. - LP+ including pricing distribution, seller metrics, and market trends.

The Plant-based Ranch and Caesar Dressing market has been experiencing a significant transformation, reflective of the growing consumer shift towards healthier, sustainable food options. With an increasing number of people adopting plant-based diets, the demand for dairy-free and vegan dressings has surged in recent

Comprehensive market data and analytics for D/D/D WAVE HIGH KING CAESAR YU-GI-OH! OP24-EN009 SUPER RARE including pricing distribution, seller metrics, and market trends.

Caesars Entertainment Inc. Company Profile, Opportunities, Challenges and Risk (SWOT, PESTLE and Value Chain); Corporate and ESG Strategies; Competitive Intelligence; Financial KPI’s; Operational KPI’s; Recent Trends: “ Read More

Comprehensive market data and analytics for D/D/D WAVE HIGH KING CAESAR 1ST EDITION PLATINUM RARE RA04 YUGIOH CARD including pricing distribution, seller metrics, and market trends.

Abstract: The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). It aimed to comprehensively characterize the genomic and molecular landscape of various cancer types. This dataset includes curated survival data from the Pan-cancer Atlas paper titled "An Integrated TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR) to drive high quality survival outcome analytics". The paper highlights four types of carefully curated survival endpoints, and recommends the use of the endpoints of OS, PFI, DFI, and DSS for each TCGA cancer type. The dataset also includes phenotypic information about HNSC. The Sample IDs are unique identifiers, which can be paired with the gene expression dataset. Inspiration: This dataset was uploaded to UBRITE for GTKB project. Instruction: The survival and phenotype data were merged into one file. Empty columns were removed. Columns with the same value for every sample were also removed. Acknowledgments: Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8 Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11. https://doi.org/10.1016/j.cell.2018.02.052 The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120 (2013). https://doi.org/10.1038/ng.2764 U-BRITE last update: 07/13/2023 {"references": ["Goldman, M.J., Craft, B., Hastie, M. et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol (2020). https://doi.org/10.1038/s41587-020-0546-8", "Liu, Jianfang, Caesar-Johnson, Samantha J. et al. An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics. Cell, Volume 173, Issue 2, 400 - 416.e11.\u00a0https://doi.org/10.1016/j.cell.2018.02.052", "The Cancer Genome Atlas Research Network., Weinstein, J., Collisson, E. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113\u20131120 (2013). https://doi.org/10.1038/ng.2764"]} UBRITE location: /data/project/ubrite/gtkb/TCGA/Clinical

Comprehensive dataset of 4 Metal working shops in Cesar, Colombia as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

[207+ Pages Report] The global vegan dressing market size is expected to grow from USD 269.34 million in 2023 to USD 584.98 million by 2032, at a CAGR of 9.00% from 2024-2032

Comprehensive market data and analytics for D/D/D WAVE OBLIVION KING CAESAR RAGNAROK DOCS-EN044 SUPER RARE 1ST EDITIO YUGIOH including pricing distribution, seller metrics, and market trends.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Caesars Stock (CZR) Forecast: Mixed Signals

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Scores of the ACC, BA, precision, recall, F1-Score, MCC, AUC, and κ for rnCV on a random subsets of the CESAR dataset.

Comprehensive market data and analytics for D/D/D WAVE OBLIVION KING CAESAR RAGNAROK MP16-EN138 SUPER RARE 1ST EDITIO YUGIOH including pricing distribution, seller metrics, and market trends.

This file includes the raw CAESAR and absorption data measured in each P-T condition and the Python codes for diffraction and absorption data analysis.

Matlab codes for P-T calibration are also enclosed.

These data are digital elevation models which describe landscape topography. The data were created to support analysis of landscape change following the 7th February 2021 avalanche-debris flow in Chamoli District, Uttarakhand, India. The data were used as standalone datasets to support this analysis, but also supported numerical modelling using CAESAR-Lisflood (see data collection). The DEMs were created from CNES/Airbus Pléiades-HR stereo satellite imagery captured in along-track mode. They are a geospatial dataset created in raster (.tif) format. They are most commonly imported into GIS software, where they can be analysed or support other forms of geospatial analysis. Full details about this dataset can be found at https://doi.org/10.5285/5a1eaef4-9211-4227-a017-d20b08be5784

These data are digital elevation models (DEMs) of difference (DoD). They are a geospatial dataset created in raster (.tif) format and quantify vertical (z) topographic change between two dates. The data were created to support analysis of landscape change following the 7th February 2021 avalanche-debris flow in Chamoli District, Uttarakhand, India. The data also supported numerical modelling using CAESAR-Lisflood (see related data https://catalogue.ceh.ac.uk/documents/7023cb77-c797-475e-872c-6f1e2b63dcc1). They are most commonly imported into GIS software, where they can be analysed or support other forms of geospatial analysis.

Experimental data. Processed composition data (material and chemical) of samples of:

(a) ferrous (FE) scrap corresponding to outputs and inputs of WP3 steel scrap upgrading trials; and

(b) non-ferrous (NF) metallic fractions recovered from the rejects of the said steel scrap upgrading trials.

The file contains the characterisation results of 10 FE scrap samples, of 2 Cu-rich samples and of 4 Al-rich samples (ref. AZTERLAN samples inventory datasets for D3.1, D3.2 and D5.2). The data have been used for:

(a) evaluating technical feasibility and cleaning efficiency of the primary and multi-step cleaning treatments (WP3). Such data pertain to Task 3.3 (WP3, CAESAR project GA 101058520 – Deliverable D3.1 & D3.2);

(b) evaluating quality and usability as secondary raw materials (in steelmaking and in other metal sector applications) of sorted NF metallic fractions recovered from cleaning rejects. Such data and the research pertain to Task 5.3 (WP5, CAESAR project GA 101058520 – Deliverable D5.2)

Format of data: excel file (.xlsx)

Origin:

• Compiled raw data of mass measurements of the hand sorted material categories, of the scrap and additions charged in the melting furnace and of the liquid metal output per melting trial.
• Compiled raw data from measurements of chemical composition by spectroscopic methods on casted testing specimens from scrap fractions melting trials, processed for secondary outputs in excel spreadsheets

Methodologies for collection or generation:

• AZTERLAN ad hoc method for material characterisation of the FE scrap samples: visual inspection and handsorting into categories, using an Excel-based template for recording measurements and calculating results
• AZTERLAN method for chemical characterisation of metal scrap after melting, by determination by Spark OES & LECO elemental analysis of the chemical composition of casted specimens of the tapped metal.

The description of the methods is included in the dataset file (datasheet « Experimental Methods info » of the Excel book)

[Rapport de plus de 207 pages] La taille du marché mondial des vinaigrettes végétaliennes devrait passer de 269.34 millions USD en 2023 à 584.98 millions USD d'ici 2032, à un TCAC de 9.00 % de 2024 à 2032

PT Bank Negara Indonesia (Persero) Tbk Stock Historical Price (BBNI.JK)

from January 2019 until present

▶ Context 📝

The dataset is taken from Yahoo Finance website. It is about the historical stock price of PT Bank Negara Indonesia (Persero) Tbk.

▶ Acknowledgements 🙏

I'd like to clarify that I'm only making data about the historical stock price of PT Bank Negara Indonesia (Persero) Tbk. available to Kaggle community.

▶ Inspiration 💭

• Forecasting stock price after January 2019
• Implementing machine learning models.
• Perform data analysis/data visualization of historical stock prices.

▶ Log 📰

• 4 January 2024: Initialization and fully automated update using Kaggle schedule run.

📷 Image by logo.yedepe.com.

Scores of the MCC for rnCV missing either the hyperparameter tuning, the feature selection or both on a random subsets of the CESAR dataset.