Exploring Female Nobel Laureates in JMP Featuring HTML5
Discover the trends of female Nobel Laureates across decades and categories using interactive charts and geographic information. Explore the impact and underrepresentation of women in Nobel Prizes through data analysis and visualization techniques.
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Exploring Female Nobel Laureates in JMP Featuring HTML5 Hui Di, JMP, SAS Institute Throughout the history of the Nobel awards, do you know which Prize category women are most likely to win? Do you know if the number of female Nobel Laureates increases over the decades? Abstract Abstract Introduction With JMP and by sharing through HTML5, you can easily discover and share this information. Hover on bar charts to find answers. In addition, we can find details about each female Nobel Laureate. Hover on a marker on the Points chart to see female Nobel Laureate s picture and her category of Nobel prize. Introduction Methods Methods In this poster, I'll show: 1) Importing the source data and preparing data for further analysis 2) Exploring geographic information for these female Nobel laureates on a global map 3) Using JMP to predict which kind of people are most likely to be awarded a Nobel Prize in the future Results Results Conclusions Conclusions Finally, a JMP HTML5 dashboard will display all the information above with dynamic linking between all the graphs. Users can explore and discover the details on Female Nobel Laureates by hovering and clicking. Also, users can share this HTML5 outside of JMP. References References
Exploring Female Nobel Laureates in JMP Featuring HTML5 Hui Di, JMP, SAS Institute Context Abstract Abstract The Nobel Prize is an international award administered by the Nobel Foundation in Stockholm, Sweden, and based on the fortune of Alfred Nobel, Swedish inventor and entrepreneur. In 1968, Sveriges Riksbank established The SverigesRiksbank Prize in Economic Sciences in Memory of Alfred Nobel, founder of the Nobel Prize. Each Prize consists of a medal, a personal diploma, and a cash award. A person or organization awarded the Nobel Prize is called a Nobel Laureate. The word "laureate" refers to being signified by the laurel wreath. In ancient Greece, laurel wreaths were awarded to victors as a sign of honor. Introduction Introduction Methods Methods Results Results Stories of female scientists are inspiring Vera Robin, an American astronomer who pioneered work on galaxy rotation rates, said in her book Bright Galaxies, Dark Matters that There is no problem in science that can be solved by a man that cannot be solved by a woman . Conclusions Conclusions References References Are women underrepresented?
Exploring Female Nobel Laureates in JMP Featuring HTML5 Hui Di, JMP, SAS Institute 3. Adding decades and age columns 1. Importing the source data and data cleaning Abstract Abstract 1) Retrieve data from nobelprize.org using PHP 2) Data Cleaning to remove duplicates 1) For same Nobel Laureate, because of different organizations he or she worked for, there were multiple entries 2) Use Summary to clean up multiples. (https://community.jmp.com/t5/Discussions/Selecting-Duplicate-Rows-in-a- Data-Table/td-p/2633) 3) Create unique winner entry Introduction Introduction Methods Methods Results Results 2. Adding Images 4. Generate charts, create dashboard, and export to HTML5 1) Create an Expression data type column and copy pictures for females from https://www.nobelprize.org/ 2) Make sure to define size of images Conclusions Conclusions References References
Exploring Female Nobel Laureates in JMP Featuring HTML5 Hui Di, JMP, SAS Institute HTML5 Female Nobel Laureates Dashboard : data are linked 1. Over the decades, is there any progress on female winners? 3. See categories that women win over decades. 6. Who is most likely to win in the future? 5. Who were the Female winners? Abstract Abstract Introduction Introduction Methods Methods --Hover over the bar chart to find about 9 percent of female winners on 2000s. --There was only one female winners for Economics over several decades. Results Results 2. Explore the HTML5 to see categories which females are most likely to win. 4. See where the female winners were from Conclusions Conclusions References References --Women have been most likely to win on Peace and literature. --Male aged 60-65 from the US in the field of Medicine are most likely to win. --Most female winners were from US. --Hover over the purple pointer to see female winners.
Exploring Female Nobel Laureates in JMP Featuring HTML5 Hui Di, JMP, SAS Institute Abstract Conclusions Abstract With JMP HTML5, it s easy to share the results across computers and mobile devices Introduction Introduction Data are all linked. When selecting a point on the Points chart, the corresponding bar charts will be highlighted Methods Methods JMP and JMP HTML5 make it easy to visualize Female Nobel Laureates Results Results References Nobel Prize official web site https://www.nobelprize.org/ Conclusions Conclusions Acknowledges Colleagues who helped on this project(Audrey Shull and Craige Hale) JMP community References
Exploring Female Nobel Laureates in JMP Featuring HTML5 Hui Di, JMP, SAS Institute Female Nobel Laureates dashboard: When clicking a purple bar on the top left bar chart for 2010s, the dots are highlighted on the Points chart. You can explore those dots to see female Nobel Laureates detailed information.
Exploring Female Nobel Laureates in JMP Featuring HTML5 Hui Di, JMP, SAS Institute Who is most likely to receive the award in future? With bar charts on category, sex, age, and countries, we can discover that a male who is from US in the category of the Medicine around 60-65 years old has a better chance.
