Counts of Part I committed in San Mateo County from 1985 on. This dataset also includes Part II crimes from 2013 on.

Part I crimes include: homicide, rape, robbery, aggravated assault, burglary, motor vehicle theft, larceny-theft, and arson. These counts include crimes committed at San Francisco International Airport (SFO), Unincorporated San Mateo County, Woodside, Portola Valley, San Carlos from 10/31/10 forward; Half Moon Bay from 6/12/11 forward; and Millbrae from 3/4/12 forward.

Part II crimes do not include San Francisco International Airport (SFO) cases and is an estimate only. An estimate is required because there are no specific data types used when keying in Type II crime types. Therefore, Records Manager judgment is used.

Different graph types may differ in their suitability to support group comparisons, due to the underlying graph schemas. This study examined whether graph schemas are based on perceptual features (i.e., each graph type, e.g., bar or line graph, has its own graph schema) or common invariant structures (i.e., graph types share common schemas). Furthermore, it was of interest which graph type (bar, line, or pie) is optimal for comparing discrete groups. A switching paradigm was used in three experiments. Two graph types were examined at a time (Experiment 1: bar vs. line, Experiment 2: bar vs. pie, Experiment 3: line vs. pie). On each trial, participants received a data graph presenting the data from three groups and were to determine the numerical difference of group A and group B displayed in the graph. We scrutinized whether switching the type of graph from one trial to the next prolonged RTs. The slowing of RTs in switch trials in comparison to trials with only one graph type can indicate to what extent the graph schemas differ. As switch costs were observed in all pairings of graph types, none of the different pairs of graph types tested seems to fully share a common schema. Interestingly, there was tentative evidence for differences in switch costs among different pairings of graph types. Smaller switch costs in Experiment 1 suggested that the graph schemas of bar and line graphs overlap more strongly than those of bar graphs and pie graphs or line graphs and pie graphs. This implies that results were not in line with completely distinct schemas for different graph types either. Taken together, the pattern of results is consistent with a hierarchical view according to which a graph schema consists of parts shared for different graphs and parts that are specific for each graph type. Apart from investigating graph schemas, the study provided evidence for performance differences among graph types. We found that bar graphs yielded the fastest group comparisons compared to line graphs and pie graphs, suggesting that they are the most suitable when used to compare discrete groups.

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Prepared for second bar chart in relevant Figure (12b) of Marine chapter of State of the environment report. Data compiled by CSIRO. Prepared for second bar chart in relevant Figure (12b) of Marine chapter of State of the environment report. Data compiled by CSIRO.

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This is a bar graph showing the prevalence of men and women aged 65 years and older who are up-to-date with the recommended core set of clinical preventive services. This project provides model-based small area estimates for 27 measures of chronic disease related to unhealthy behaviors (5), health outcomes (13), and use of preventive services (9). Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. It represents a first-of-its kind effort to release information on a large scale for cities and for small areas within those cities. It includes estimates for the 500 largest US cities and approximately 28,000 census tracts within these cities. These estimates can be used to identify emerging health problems and to inform development and implementation of effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these measures include Behavioral Risk Factor Surveillance System (BRFSS) data 2014, Census Bureau 2010 census population data, and American Community Survey (ACS) 2010-2014 estimates. More information about the methodology can be found at www.cdc.gov/500cities.

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The H1B Sponsorship Trends linear chart shows the number of H1B cases filed by Birmingham Autobody Parts Supply 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.

The PERM Sponsorship Trends linear chart visualizes the number of PERM cases filed by Tvh Parts 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.

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This horizontal bar chart displays polarity sentiment score by section using the aggregation average. The data is filtered where the entities includes companies and the keywords includes El Paso.

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This horizontal bar chart displays news by section using the aggregation count. The data is filtered where the entities includes universities and the keywords includes Carlos Alcaraz.

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This bar chart displays land area (km²) by countries yearly using the aggregation sum in Ecuador. The data is filtered where the date is 2021. The data is about countries per year.

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This horizontal bar chart displays polarity sentiment score by section using the aggregation average. The data is filtered where the entities includes cities, the keywords includes El Paso and the section is politics.