Primers used for quantitative real-time PCR, CHART-PCR and ChIP.

The Data Visualization Corpus

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1430847%2F29f7950c3b7daf11175aab404725542c%2FGettyImages-1187621904-600x360.jpg?generation=1601115151722854&alt=media" alt="">

Data Visualization

Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.

In the world of Big Data, data visualization tools and technologies are essential to analyze massive amounts of information and make data-driven decisions

The Data Visualizaion Copus

The Data Visualization corpus consists:

• 32 cheat sheets: This includes A-Z about the techniques and tricks that can be used for visualization, Python and R visualization cheat sheets, Types of charts, and their significance, Storytelling with data, etc..

• 32 Charts: The corpus also consists of a significant amount of data visualization charts information along with their python code, d3.js codes, and presentations relation to the respective charts explaining in a clear manner!

• Some recommended books for data visualization every data scientist's should read:

  1. Beautiful Visualization by Julie Steele and Noah Iliinsky
  2. Information Dashboard Design by Stephen Few
  3. Knowledge is beautiful by David McCandless (Short abstract)
  4. The Functional Art: An Introduction to Information Graphics and Visualization by Alberto Cairo
  5. The Visual Display of Quantitative Information by Edward R. Tufte
  6. storytelling with data: a data visualization guide for business professionals by cole Nussbaumer knaflic
  7. Research paper - Cheat Sheets for Data Visualization Techniques by Zezhong Wang, Lovisa Sundin, Dave Murray-Rust, Benjamin Bach

Suggestions:

In case, if you find any books, cheat sheets, or charts missing and if you would like to suggest some new documents please let me know in the discussion sections!

Resources:

• Charts: I personally recommend data viz catalogue, it's easy to understand with their explanation!
• Python codes: Plotly for python and Python graph gallery
• R codes for charts:Plotly for R
• d3 codes: Visualization codes using d3

Request to kaggle users:

• A kind request to kaggle users to create notebooks on different visualization charts as per their interest by choosing a dataset of their own as many beginners and other experts could find it useful!

• To create interactive EDA using animation with a combination of data visualization charts to give an idea about how to tackle data and extract the insights from the data

Suggestion and queries:

Feel free to use the discussion platform of this data set to ask questions or any queries related to the data visualization corpus and data visualization techniques

Kindly upvote the dataset if you find it useful or if you wish to appreciate the effort taken to gather this corpus! Thank you and have a great day!

Index Time Series for Alpha Architect U.S. Quantitative Momentum ETF. The frequency of the observation is daily. Moving average series are also typically included. Under normal circumstances,the fund will invest at least 80% of its net assets (plus any borrowings for investment purposes) in U.S.- listed companies that meet the Sub-Adviser"s definition of momentum ("Momentum Companies "). The Sub-Adviser employs a multi-step, quantitative, rules-based methodology to identify a portfolio of approximately 50 to 200 equity securities with the highest relative momentum.

The "Dataset_Graph.zip" file contains the graph models of the trees in the dataset. These graph models are saved in the "pickle" format, which is a binary format used for serializing Python objects. The graph models capture the structural information and relationships of the cylinders in each tree, representing the hierarchical organization of the branches.

Underlying quantitative data in support of the chart in Fig 4D in [1].

Dataset chart Quantitative Information Social Issues Racial Mental Emotional PhD Dr.David Render Solving Categorizing Identifying Social Issues Human Impact In Part National Case Studies Chicagoland Business & Los Angeles Economic Territories

Index Time Series for Alpha Architect U.S. Quantitative Value ETF. The frequency of the observation is daily. Moving average series are also typically included. The Sub-Adviser employs a multi-step, quantitative, rules-based methodology to identify a portfolio of approximately 50 to 200 undervalued U.S. equity securities with the potential for capital appreciation. A security is considered to be undervalued when it trades at a price below the price at which the Sub-Adviser believes it would trade if the market reflected all factors relating to the company"s worth.

Underlying quantitative data in support of the charts in Fig 6 in [1].

Index Time Series for Invesco Quantitative Strats Glbl Eq Lw Vol Lw Crbn UCITS ETF Acc EUR. The frequency of the observation is daily. Moving average series are also typically included. NA

“Variable-oriented quantitative empirical research: systemic framework and procedures” is extracted in this project as a structured knowledge graph, representing the core variables, hypothesized relationships, and analytical steps as nodes and edges, so that they can be easily used for automatic retrieval, modeling, and visual analysis.

The ability to observe and interpret images and clinical information is essential for veterinarians in clinical practice. The purpose of this study is to determine the utility of a novel teaching method in veterinary medicine, the incorporation of art interpretation using the Visual Thinking Strategies (VTS), on students’ observational and clinical interpretation skills when evaluating radiographs and patient charts. Students were asked to observe and interpret a set of radiographs and a patient chart, subsequently involved in art interpretation using VTS, and then asked to observe and interpret a different set of radiographs and a different patient chart. Qualitative and quantitative analysis was performed, including scoring of observations and interpretations by a radiologist and emergency and critical care resident. For radiographs, observation and interpretation scores increased significantly after VTS. There was no change in patient chart observation or interpretation scores after VTS. Broadly, VTS provided creative thinking and visual literacy exercises that students felt pushed students them to think more openly, notice subtleties, use evidential reasoning, identify thinking processes, and integrate details into a narrative. However, its impact on clinical reasoning, as assessed by chart observation and interpretation scores, was uncertain. Further studies are needed to determine the optimal way to incorporate art interpretation in the veterinary medical curriculum.

This dataset comprises a five-level, fine-grained, lossless knowledge graph (Version 2) constructed around full-text papers on advanced qualitative research and mixed-methods research methodologies. The source texts are complete, lengthy academic works covering the philosophical foundations of qualitative research, research design, specific methodological operations, and diverse case studies and mixed-methods practices. This dataset no longer preserves the original formatting and layout details. Instead, it systematically transforms the knowledge content into structured data organized as “whole-chapter-paragraph-sentence-keyword/heterogeneous node,” supporting methodological meta-research, instructional design, knowledge graph and GraphRAG modeling, as well as the development of intelligent retrieval and reasoning systems for academic texts. Version 2 significantly enhances paragraph-level representation, chart data preservation, and metadata annotation capabilities over its predecessor, balancing readability, computability, and methodological rigor.

Wikipedia is the largest and most read online free encyclopedia currently existing. As such, Wikipedia offers a large amount of data on all its own contents and interactions around them, as well as different types of open data sources. This makes Wikipedia a unique data source that can be analyzed with quantitative data science techniques. However, the enormous amount of data makes it difficult to have an overview, and sometimes many of the analytical possibilities that Wikipedia offers remain unknown. In order to reduce the complexity of identifying and collecting data on Wikipedia and expanding its analytical potential, after collecting different data from various sources and processing them, we have generated a dedicated Wikipedia Knowledge Graph aimed at facilitating the analysis, contextualization of the activity and relations of Wikipedia pages, in this case limited to its English edition. We share this Knowledge Graph dataset in an open way, aiming to be useful for a wide range of researchers, such as informetricians, sociologists or data scientists.

There are a total of 9 files, all of them in tsv format, and they have been built under a relational structure. The main one that acts as the core of the dataset is the page file, after it there are 4 files with different entities related to the Wikipedia pages (category, url, pub and page_property files) and 4 other files that act as "intermediate tables" making it possible to connect the pages both with the latter and between pages (page_category, page_url, page_pub and page_link files).

The document Dataset_summary includes a detailed description of the dataset.

Thanks to Nees Jan van Eck and the Centre for Science and Technology Studies (CWTS) for the valuable comments and suggestions.

Deep-water benthic ostracodes from the Pliocene-Pleistocene interval of ODP Leg 107, Hole 654A (Tyrrhenian Sea) were studied. From a total of 106 samples, 40 species considered autochthonous were identified. Detailed investigations have established the biostratigraphic distribution of the most frequent ostracode taxa. The extinction levels of Agrenocythere pliocenica (a psychrospheric ostracode) in Hole 654A and in some Italian land sections lead to the conclusion that the removal of psychrospheric conditions took place in the Mediterranean Sea during or after the time interval corresponding to the Small Gephyrocapsa Zone (upper part of early Pleistocene), and not at the beginning of the Quaternary, as previously stated. Based on a reduced matrix of quantitative data of 63 samples and 20 variables of ostracodes, four varimax assemblages were extracted by a Q-mode factor analysis. Six factors and eight varimax assemblages were recognized from the Q-mode factor analysis of the quantitative data of 162 samples and 47 variables of the benthic foraminifers. The stratigraphic distributions of the varimax assemblages of the two faunistic groups were plotted against the calcareous plankton biostratigraphic scheme and compared in order to trace the relationship between the benthic foraminifers and ostracodes varimax assemblages. General results show that the two populations, belonging to quite different taxa, display almost coeval changes along the Pliocene-Pleistocene sequence of Hole 654A, essentially induced by paleoenvironmental modifications. Mainly on the base of the benthic foraminifer assemblages (which are quantitatively better represented than the ostracode assemblages), it is possible to identify such modifications as variations in sedimentation depth and in bottom oxygen content.

Network of 43 papers and 72 citation links related to "A Qualitative and Quantitative Analysis of Real Time Traffic Information Providers".

Index Time Series for Invesco Markets II PLC - Invesco Quantitative Strategies ESG Global Equity Multi-Factor UCITS ETF. The frequency of the observation is daily. Moving average series are also typically included. NA

We propose a novel approach to predict saturation vapor pressures using group contribution-assisted graph convolutional neural networks (GC2NN), which use both, molecular descriptors like molar mass and functional group counts, as well as molecular graphs containing atom and bond features, as representations of molecular structure. Molecular graphs allow the ML model to better infer molecular connectivity and spatial relations compared to methods using other, non-structural embeddings. We achieve best results with an adaptive-depth GC2NN, where the number of evaluated graph layers depends on molecular size. We apply the model to compounds relevant for the formation of SOA, achieving strong agreement between predicted and experimentally-determined vapor pressure. In this study, we present two models: a general model with broader scope, achieving a mean absolute error (MAE) of 0.69 log-units (R2 = 0.86), and a specialized model focused on atmospheric compounds (MAE = 0.37 log-units, R2 = 0.94).

This dataset provides a five-level, fine-grained, and structurally normalized knowledge-graph representation of a qualitative methods text corpus (Research with Qualitative Data), treated purely as text data rather than as a bibliographic object. Each record corresponds to a node at one of five hierarchical levels—macro-section (level 1), meso-section (level 2), paragraph (level 3), sentence (level 4), and keyword/media snippet (level 5)—with explicit parent–child links (e.g., sentence → paragraph, paragraph → meso-section), forming a well-closed, acyclic tree structure. For all machine-readable content in the source PDF, the dataset decomposes the corpus into independent nodes while preserving page locators and section titles, so that any fragment of text can be traced back to its exact position in the original file. Keyword nodes are automatically extracted from sentences to enhance search, thematic mapping, and downstream modeling without altering or compressing the underlying text. For tables and images, the dataset stores captions, surrounding textual context, and row-level data_points where applicable, enabling full reconstruction of tabular and visual information at the text level. Under the assumption that “all machine-readable text in the PDF is the reference universe,” the collection achieves a practically lossless representation of the qualitative methods corpus and has been independently checked for level completeness, parent–child consistency, and content integrity, supporting its designation as a five-level, completely lossless text-based knowledge-graph dataset suitable for advanced qualitative methodology research, knowledge-graph engineering, and large-language-model retrieval and reasoning experiments.

Network of 46 papers and 98 citation links related to "Diagnostic performance of the specific uptake size index for semi-quantitative analysis of I-123-FP-CIT SPECT: harmonized multi-center research setting versus typical clinical single-camera setting".

Firstly Holtfrerich presents the Rostov Concept of the leading sector, before he sketches the development of mining in the Ruhr area by means of theoretical approaches concerning theories on production, price, and investment. In doing so, the author attempts to quantify the connections between the development of coal mining in the Ruhr district and other important sectors by means of an input-output scheme. Thereafter he examines how far the development of mining in the Ruhr area in the 19th century in its major phase of growth complies with the Rostov criteria for the leading sector. Finally Holtfrerich verifies the assumption that mining in the Ruhr district has been a leading sector of the German industrialisation.

Chart register Chart 01: Coal mining in the OBAB Dortmund, the Saar area, and the Kingdom of Prussia (1816-1913) Chart 02: Annual average price of coal in the OBAB Dortmund, nominal and real development (1816-1813) Chart 03: Number of operating coal mines in the OBAB Dortmund, and average production of each mine (1816-1892) Chart 04: Proportion of the five and ten greatest mines as to the total coal production of the mines in the OBAB Dortmund; in percent (1852-1890) Chart 05: Contributions of coal mines in the OBAB Dortmund in 1,000 marks (1850-1895) Chart 06: Tax burden for coal mining in the Lower Rhine region and in Westphalia (1880-1903) Chart 07: Burden of the coal mines in the OBAB Dortmund; coal mine contributions (“Bergwerksabgaben”) and taxes in percent of coal sales value (1816-1913) Chart 08: Annually licenced basic capital of the “Montan-Aktiengesellschaften” (coal, iron and steel corporations) founded in the Ruhr (1840-1870) Chart 10: Average number of workers per year (including mine officials) in the field of coal mining in the OBAB Dortmund (1816-1913) Chart 11: Average annual net payroll and annual net basic wages of the miners in the OBAB Dortmund (1850-1913) Chart 12: Wages in coal mining within the OBAB Dortmund (1850-1903) Chart 13: Working hours in coal mining within the OBAB Dortmund (1852-1892) Chart 14: Labour productivity in coal mining in the OBAB Dortmund (1816-1913) Chart 15: Development of capital investment: disposable steam machines (combined engine power in HP) of coal mines within the OBAB Dortmund (1851-1892) Chart 16: Development of investment: annual increase of steam machine power (in HP) (1852-1892) Chart 18: Development of capital productivity and capital intensity (1851-1892) Chart 19: Data on net value added and capital income in the field of coal mining in the OBAB Dortmund (1850-1903) Chart 20: Capital income/dividends and profits per produced ton of coal for coal mining in the Ruhr area (1850-1892) Chart 21: Proportion of the total coal produced in the Lower Rhine/Westphalian bassin, which was coked by the colliery itself, or – from 1882 on – formed into briquettes(1861-1892) Chart 22: Percentage of propulsion power in HP applied in coal mining within the OBAB Dortmund (1875-1895) Chart 23: Own consumption of coal of mines within the OBAB Dortmund (1852-1892) Chart 24: Development of the profit indicator for coal mining in the Ruhr district (1851-1892) Chart 25: Expansion of the German railway system (1835-1892) Chart 26: Figures on the development of Prussian railways (1844-1882) Chart 27: Development of average revenues for the transport of coal on various railways (1861-1877) Chart 28: Development of the proportion of means of transport with regard to the transport of coal from the Ruhr area (1851-1889) Chart 29: Division of domestic sales of the “Rheinisch-Westfälisches Kohlensyndikat” (Coal Syndicate of the Rhineland and Westphalia) per consumption groups in percent (1902-1906) Chart 30: Wroughtiron production and steel production from coal in the OBAB Dortmund and in the OBAB Bonn (part on the right bank of the Rhine) (1852-1882) Chart 31: Crude iron production in the Ruhr area, OBAB Dortmund (1837-1900) Chart 32: Price development for crude iron, bar iron and cast steel in the Ruhr district (1850-1892) Chart 33: Bar iron production in the OBAB Dortmund and in the OBAB Bonn by means of the charcoal hearth process and the “Puddelverfahren”, a method to produce steel from crude iron (1835-1870) Chart 34: The importance of the economic sectors according to their respective employment figures (1852-1875).