31:T921,md`# HaniehBarazandehA3 I have created 8 subsets, and combining the categorical and nominal dimensions from the original dataset(gender(female vs male), status in Canada(Canadian vs International), Classification of Instructional Programs(STEM vs total)), now I have 8 new nominal dimensions, that I chose according to the initial questions that I defined in the first milestone of the project. I have created the histogram for each one, that shows the number of each group over the years 2016, 2017, and 2018. \n As required in the assignment, I have: computed min and max for the number of female international students in stem in 3 years. computed total number of female international students in stem in 3 years. found the median number of male Canadian students in stem over the 3 years. computed the number of records that match this criteria: country of citizenship=Asia, year of admission=2018 created histograms for all dimensions, with suitable bin size dataset source: https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3710018401 source of the bar charts: https://observablehq.com/@observablehq/vega-lite-chart-types?collection=@observablehq/observable-for-vega-lite All the other codes are written by me, and I have included comments that explain each code, above each one. the challenges I had with the dataset: \n the years were taken as string in Observable because of the bad format, so I had to change them. \n In my filtering tasks, I notice that there are records that are the total number of a dimension, and I had to take that into account, so that I do not have wrong numbers. For instance, where I computed the number of records that matched certain criteria, I had to add in my code dataFile[i].Classification_of_Instructional_Programs=="Total, instructional program", so that I do not over count. \n country of citizenship dimension also has values for Canadians, which means for isntance, there are records that status in Canada is Canadian, and also country of citiizenship is Americas, in order to not overcount numbers, I had to include dataFile[i].Country_of_Citizenship=="Total, country of citizenship" in filtering data. \n And finally, there were some dimensions that there sort of vague, and the value of them was the same for all records, so I had to get rid of them for a cleaner dataset. `32:[{"id":"5f16b5badc984ed93d85d1d486ea8e2863ba16b2de19d59f7945f4892e2674ce89d2b363a88e5e1110046fa91aaed71177fbcae67a6ce69fe08823bd2925828d","href":"https://static.observableusercontent.com/files/5f16b5badc984ed93d85d1d486ea8e2863ba16b2de19d59f7945f4892e2674ce89d2b363a88e5e1110046fa91aaed71177fbcae67a6ce69fe08823bd2925828d","name":"my_dataset2@7.csv","type":"text/csv","lastModified":1616038054494.745,"size":112995}] 2f:{"title":"HaniehBarazandehA3","cells":[{"id":141,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":152,"value":"md`## Subsets That I have created through filtering\n\nfemale internationals in STEM \\n\nmale internationals in STEM \\n\nfemale Canadians in STEM \\n\nmale Canadians in STEM \\n\n\nfemale internationals in Total, instructional program(STEM+BHASE) \\n\nmale internationals in Total, instructional program(STEM+BHASE) \\n\nfemale Canadians in Total, instructional program(STEM+BHASE) \\n\nmale Canadians in Total, instructional program(STEM+BHASE) \\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":256,"value":"md`## Students of Asian Background`","pinned":false,"hidden":false,"mode":"ojs"},{"id":248,"value":"//I loop through the array that holds all the records \n//I check if they meet the criteria: country of citizenship=Asia, in year 2018 and from all programs of study\n//I create an array that holds all the records matching the criteria \n//and finally, I return the length of that array which is 5, so 5 records match this criteria \nStudentsOfAsianBackground={ \n let StudentsOfAsianBackground=[];\n let j=0;\n for(let i=0; i d.REF_DATE)","pinned":true,"hidden":false,"mode":"ojs"},{"id":202,"value":"md`## Min and Max for number of female international students over the years`","pinned":false,"hidden":false,"mode":"ojs"},{"id":69,"value":"d3.extent(femaleInternationalsInSTEM, d => d.VALUE)","pinned":true,"hidden":false,"mode":"ojs"},{"id":268,"value":"md`## female Internationals in Total`","pinned":false,"hidden":false,"mode":"ojs"},{"id":260,"value":"femaleInternationalsInTotal={ \n let femaleInternationalsInTotal=[];\n let j=0;\n for(let i=0; i