Figures in scientific publications are critically important because they often show the data supporting key findings. Our systematic review of research articles published in top physiology journals (n = 703) suggests that, as scientists, we urgently need to change our practices for presenting continuous data in small sample size studies. Papers rarely included scatterplots, box plots, and histograms that allow readers to critically evaluate continuous data. Most papers presented continuous data in bar and line graphs. This is problematic, as many different data distributions can lead to the same bar or line graph. The full data may suggest different conclusions from the summary statistics. We recommend training investigators in data presentation, encouraging a more complete presentation of data, and changing journal editorial policies. Investigators can quickly make univariate scatterplots for small sample size studies using our Excel templates.

(G) Expression pattern of genes associated with group I and II loci (from Fig. 2E) within differentially expressed gene sets. Significance calculated by prop.test R, (***) P<0.001. (H) Venn diagram shows overlap between SOX3 binding in NPCs and GPCs. Bar graph shows expression pattern of genes continuously bound by SOX3 NPCs and GPCs. (I) Venn diagram shows overlap between SOX3 and SOX9 binding in GPCs. Bar graph shows expression pattern of genes co-bound by SOX3 and SOX9 in GPCs. (J) ChIP-seq peak graphics around the astrocyte gene Fgfbp3. ChIP-seq peaks are derived from three different experiments; SOX3 ChIPs in NPCs, SOX3 ChIPs in GPCs, SOX9 ChIPs in GPCs. Both ChIP-seq reads and called peak regions (underlying black lines) are shown for all data sets. Bar graphs shows the distribution of differentially expressed genes that are bound by all three factors. P-values (phyper, R) were calculated from the total number of protein coding genes in mm10 assembly (23´389). List of tagged entities: multiple components, Fgfbp3 (ncbigene:72514), Sox3 (uniprot:P53784), Sox9 (uniprot:Q04887), , ChIP assay (obi:OBI_0001954),ChIP-seq assay (obi:OBI_0000716),gene expression assay (bao:BAO_0002785)

This bar chart displays revenues ($) by industry using the aggregation sum. The data is filtered where the industry is Multi-Utilities. The data is about companies.

The PERM Sponsorship Trends linear chart visualizes the number of PERM cases filed by Tisch Multiple Sclerosis Research Center Of New York from 2020 to 2023, highlighting the company’s long-term sponsorship patterns. The horizontal bar chart titled Distribution of Job Fields Receiving PERM Sponsorship further categorizes sponsored roles by job type.

This bar chart displays employees (people) by foundation year using the aggregation sum. The data is filtered where the industry is Multi-Utilities. The data is about companies.

The Charts extension for CKAN enhances the platform's data visualization capabilities, allowing users to create, manage, and share charts that are linked to CKAN datasets. It allows users to create interactive and visually appealing chart representations of data directly within the CKAN environment, providing essential data analysis tools. This streamlines the process of visualizing data for a more intuitive and accessible experience. Key Features: Chart Creation: Enables users to create charts directly from CKAN datasets. Chart Editing: Allows users to modify and customize existing charts. Chart Embedding: Provides the ability to embed created charts into other web applications or platforms for wider dissemination. Chart Sharing: Supports sharing of chart visualizations with other users or groups within or outside the CKAN ecosystem. Multiple Chart Types: Supports a variety of common chart types, including bar charts, line charts, and pie charts. Further chart types are not mentioned explicitly, but it is implied the extension can be extended as well. Technical Integration: The extension integrates with CKAN primarily as a plugin. To enable the Charts extension, the chartsview and chartsbuilderview plugins must be added to the CKAN configuration file. The documentation also mentions the need to set CHARTS_FIELDS when autogenerating documentation for chart types fields, which implies a level of customization and extensibility for different chart types. It requires proper initialization of the CKAN instance and relies on validators and helpers, emphasizing the need for a correctly configured CKAN environment. Benefits & Impact: The primary benefit of the CKAN Charts extension is the enhancement of data analysis and presentation capabilities within CKAN. By providing tools to create, manage, and share charts, the extension makes it easier for users to understand and communicate insights from their data, fostering better data-driven decision-making. Also the documentation for chart types can be autogenerated.

The H1B Sponsorship Trends linear chart shows the number of H1B cases filed by Tisch Multiple Sclerosis Research Center Of New York from 2020 to 2023, providing a clear view of filing trends over time. Alongside, the horizontal bar chart titled Distribution of Job Fields Receiving H1B Sponsorship breaks down which roles and industries are most commonly sponsored.

In this lesson, learners participate in activities to develop concepts of measurement and statistics. Learners are asked to measure distances using non-standard units and to record their measurement in a bar graph. Then, they are asked to make comparisons using the bar graph.

This repository contains the materials used in the Systematic Literature Review (SLR) on the application of Howard Gardner’s Theory of Multiple Intelligences in digital educational technologies. The structure is organized as follows:bib_database/: Contains .bib files with all bibliographic entries returned from the search string applied in selected digital libraries. Also includes a Python script used to merge and process these entries into a single database.plot_scripts/: Includes data files and Python scripts used to generate the visualizations presented in the review (e.g., bar charts, pie charts, distribution graphs).all_articles.xlsx: Master list of all studies retrieved using the search string, including metadata such as title, authors, year, and source.srl_protocol.xlsx: Final set of selected articles after applying inclusion/exclusion criteria. Also includes quality assessment scores and detailed classification for each research question (Q1–Q4), along with written justifications.

Data DescriptionThe layers on this map contain population, employed labour force counts, private dwelling counts, and employment counts at Census Subdivision and Census Tract geographies from the 2006, 2011, and 2016 Census. The definition of each variable is described next:Population counts: the total population aggregated from different ages in each census tract.Employment counts: the number of labour force aged 15 years and over having an usual work place or working at home at places of work in each census tract, excluding workers with a non-fixed place-of-work.Employed labour force counts: the number of employed labour force aged 15 years and over having a usual work place or working at home at places of residence in each census tract including workers with a non-fixed place-of-work.Private dwellings count: the number of households aggregated from different types of dwellings in each census tract.Note: Population counts are from long census survey forms, covering 25% of the population. The other three variables are from short census survey forms, covering 100% population.Note about the Legend: the Employment and Population values are normalized by Quantiles. Each colour has the same number of features and will not necessarily represent the same values in different layers.InstructionsZoom in and out of the map to update the bar charts. Use the Select Tool to select specific geographies to display on the bar chart.“Select by rectangle” allows you to draw a rectangle and select multiple geography to view in the chart.“Select by point” allows you select an area by clicking on its geography."Add Data" allows you add separate public data as need from ArcGIS Online, URL (an ArcGIS Server Web Service, a WMS OGC Web Service, a KML file, a GeoRSS file, a CSV file), and local files (shapefile, csv, kml, gpx, geojson)Project lead: A.MaruicioDevelopers: C.Riccardo, W.Huang, D.Robbin

This bar chart displays books by publication date using the aggregation count. The data is filtered where the author is Thomas W. Many. The data is about books.

This bar graph compares how many people were employed in the transport sector in France in 2017. Road passenger transport in France accounted for the majority of the transport workforce, as just under 400,000 people were estimated to be employed in this sector in 2017.

The graph displays the top 15 states by an estimated number of homeless people in the United States for the year 2025. The x-axis represents U.S. states, while the y-axis shows the number of homeless individuals in each state. California has the highest homeless population with 187,084 individuals, followed by New York with 158,019, while Hawaii places last in this dataset with 11,637. This bar graph highlights significant differences across states, with some states like California and New York showing notably higher counts compared to others, indicating regional disparities in homelessness levels across the country.

This document presents the complete questionnaire and the aggregated survey results from an expert study on the design and technical requirements for data trustees. It includes Likert scale items, multiple-answer questions, and associated visualizations (bar charts) that illustrate the collective responses. This is the blinded version intended for the review process. After the blind review, an updated (authorized) version may be uploaded under the same DOI via Zenodo’s versioning system.

This bar chart displays books by publication date using the aggregation count. The data is filtered where the book publisher is Centre for Multi-Cultural Education. The data is about books.

(C) MEF cell lines lacking the indicated genes were treated for 12h with 50 nM BafA1 fixed and immunolabeled for PC1 (568, red) and LAMP1 (488, green). CST was added where indicated. Scale bar = 10 µm. Inset panels show magnification of the boxed area. Bar graph on the right shows quantification of LAMP1 vesicles positive for PC1, expressed as % of total lysosomes (mean +/- SEM), n=8, 8, 12, 8, 8, 8 cells respectively; 3 independent experiments. One-way ANOVA with Dunnett's multiple comparisons test performed and P value adjusted for multiple comparisons. *** P<0.0001.. List of tagged entities: Lamp1 (uniprot:P11438), Plod3 (uniprot:Q9R0E1), lysosome (go:GO:0005764), vesicle (go:GO:0031982), castanospermine (CHEBI:27860), Calr (ncbigene:12317), Canx (ncbigene:12330), Pdia3 (ncbigene:14827), Uggt1 (ncbigene:320011), immunolabeling method (bao:BAO_0002425),localization assay (bao:BAO_0002196)

This bar chart displays books by publication date using the aggregation count. The data is filtered where the book publisher is Multi-Cultural Resource Centre N-I. The data is about books.

This bar chart displays books by publication date using the aggregation count. The data is filtered where the book is Too many cooks. The data is about books.

Snickers is among the most well-known chocolate & candy bar brand in the United States. Around 93 percent of internet respondents are aware of Snickers. Hershey's, KitKat, Twix, and Reese's, were similarly known among the U.S. online population.For this study, brand awareness was surveyed employing the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name. Interested in more detailed results covering all brands of this ranking and many more? Explore Brand Profiles. These statistics show the results of the Statista Consumer Insights Brand KPIs.

Data DescriptionThe layer on this map contains population, employed labour force counts, private dwelling counts, and employment counts at a Census Subdivision geography from the 2016 Census. The definition of each variable is described next:Population counts: the total population aggregated from different ages in each census tract.Employment counts: the number of labour force aged 15 years and over having an usual work place or working at home at places of work in each census tract, excluding workers with a non-fixed place-of-work.Employed labour force counts: the number of employed labour force aged 15 years and over having a usual work place or working at home at places of residence in each census tract including workers with a non-fixed place-of-work.Private dwellings count: the number of households aggregated from different types of dwellings in each census tract.Note: Population counts are from long census survey forms, covering 25% of the population. The other three variables are from short census survey forms, covering 100% population.Note about the Legend: the Employment and Population values are normalized by Quantiles. Each colour has the same number of features and will not necessarily represent the same values in different layers.InstructionsZoom in and out of the map to update the bar charts. Use the Select Tool to select specific geographies to display on the bar chart.“Select by rectangle” allows you to draw a rectangle and select multiple geography to view in the chart.“Select by point” allows you select an area by clicking on its geography."Add Data" allows you add separate public data as need from ArcGIS Online, URL (an ArcGIS Server Web Service, a WMS OGC Web Service, a KML file, a GeoRSS file, a CSV file), and local files (shapefile, csv, kml, gpx, geojson)