2b:null 2c:["$","title",null,{"children":"Visualization - Group Duplicates in Medicaid | haerin99 | Observable"}] 31:T49f,clean_data = { let combined = [], res = [], nested = sorted_data[0], i = 0; if(sorted_data.length == 1) { combined = [sorted_data[0]]; } // Combine data of same medication across different years for(let i=0; i { res.push([]); for(let j=0; j < combined[i].length; j++) { let o = {ndc_description: combined[i][j].ndc_description, nadac_per_unit: parseFloat(combined[i][j].nadac_per_unit), // Convert string to float as_of_date: new Date(combined[i][j].as_of_date), // Convert string to date effective_date: new Date(combined[i][j].effective_date)} res[i].push(o) } }) return res; }32:T547,// Put objs into first or second nested array based on whether the prices are closer to the minimum or maximum group_duplicates = function(date) { let res = []; for(let i=0; i 1) { let p1 = Math.min.apply(null, filter_dt(date)[i].map(o => o.nadac_per_unit)) let p2 = Math.max.apply(null, filter_dt(date)[i].map(o => o.nadac_per_unit)) for(let j=0; j < filter_dt(date)[i].length; j++) { if(Math.abs(filter_dt(date)[i][j].nadac_per_unit - p1) < Math.abs(filter_dt(date)[i][j].nadac_per_unit - p2)) { o = {ndc_description: filter_dt(date)[i][j].ndc_description, nadac_per_unit: filter_dt(date)[i][j].nadac_per_unit, date: filter_dt(date)[i][j].date, date_type: '0_' + date}; a[0].push(o); } else { o = {ndc_description: filter_dt(date)[i][j].ndc_description, nadac_per_unit: filter_dt(date)[i][j].nadac_per_unit, date: filter_dt(date)[i][j].date, date_type: '1_' + date}; a[1].push(o); } } a.sort((a,b) => (a.date > b.date ? -1 : 1)); res.push(a); } else { res.push([filter_dt(date)[i]]) } } return res.flat().filter(o => o.length !== 0); }33:[] 2f:{"id":"b60b7826b900c0ba","slug":"group-duplicates-in-medicaid-haerin","title":"Visualization - Group Duplicates in Medicaid","thumbnail":"3d45db33725cfbaae6f06f0ac0190bc8ffd90b91f743400936917544a1bc25f1","access_level":"public","create_time":"$D2023-07-10T20:19:31.652Z","update_time":"$D2023-07-14T16:38:24.019Z","view_time":null,"first_public_time":"$D2023-07-11T15:27:18.327Z","fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"c0e8b380dee1e1d5","login":"haerin99workspace","name":"haerin99","avatar_url":"https://avatars-next.observableusercontent.com/9afd2e14693a32440c6089cf7c2043771da4c0937c8ad0bf3f7f678266dcc49a","tier":"starter_2024"},"version":553,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"9a41c27f85b5d6c6","login":"haerin99","name":"Hae Rin Kim","avatar_url":"https://avatars-next.observableusercontent.com/0fdfcb7981eb57c843329cd32bf4d53e012e7b3b1e61c95b89af630088c70ad6","tier":null}],"members":[{"type":"individual","id":"9a41c27f85b5d6c6","login":"haerin99","name":"Hae Rin Kim","avatar_url":"https://avatars-next.observableusercontent.com/0fdfcb7981eb57c843329cd32bf4d53e012e7b3b1e61c95b89af630088c70ad6","tier":null,"role":"editor"},{"type":"team","id":"c0e8b380dee1e1d5","login":"haerin99workspace","name":"haerin99","avatar_url":"https://avatars-next.observableusercontent.com/9afd2e14693a32440c6089cf7c2043771da4c0937c8ad0bf3f7f678266dcc49a","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Visualization - Group Duplicates in Medicaid","cells":[{"id":0,"value":"# Visualization - Group Duplicates in Medicaid","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":263,"value":"## Introduction","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":265,"value":"Some of the Medicaid datasets have different prices on the same day. In the NADAC (National Average Drug Acquisition Cost) 2021 dataset, the ACNE MEDICATION 10% GEL has prices of approximately 0.2 and 0.08 on each recorded date (as_of_date) as shown below. Different prices on the same date are put into two groups in order to visualize the data. One group consists of prices that are closer to the minimum, and the second group has prices that are closer to the maximum.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":428,"value":"Additionally, there are two different types of dates in the datasets: as_of_date and effective_date. The prices were plotted across both date types.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":422,"value":"nadac_2021_data","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":25,"value":"variables = `ndc_description,nadac_per_unit,as_of_date,effective_date` //","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":423,"value":"nadac_2021_data = await sdk.getDatastoreQuerySql(`[SELECT ${variables} FROM ${\"88b0eac5-6164-5737-b746-16eaefd52664\"}]`);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":47,"value":"## Import","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":15,"value":"sdk = await import (\"https://kunaalagarwal.github.io/medicaid/sdk.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":49,"value":"## Fetch data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":256,"value":"//sdk.clearCache()","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":19,"value":"medicaid = (await fetch(\"https://data.medicaid.gov/api/1/metastore/schemas/dataset/items\")).json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":21,"value":"viewof medicaid_datasets = Inputs.select( medicaid.map(({ title}) => title).sort().filter(el => el.includes(\"\")), {multiple: 14, width: '750px', label: \"Select Medicaid datasets\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":23,"value":"distrIDs= Promise.all(medicaid_datasets.map(title=> {return medicaid.find(obj => obj.title === title)[\"identifier\"]}).map(id=> sdk.convertDatasetToDistributionId(id)))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":51,"value":"## Select drugs","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":29,"value":"viewof results = Inputs.select(await sdk.getNadacMeds(), {multiple: 10, width: 300})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":31,"value":"viewof selectedMeds = Inputs.table(sdk.getSimilarMeds(results))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":33,"value":"medicines = (sdk.parseSelectedMeds(selectedMeds)).flat()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":311,"value":"## Get data for selected drugs","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":479,"value":"async function getAllData(items, vars, distributions){\n let varsString = \"\"\n const fetchDataPromises = [];\n Object.values(vars).forEach(v => {varsString += `,${v}`})\n varsString = varsString.slice(1, varsString.length)\n const fetchData = async (identifier, item) => {\n let sql = `[SELECT ${varsString} FROM ${identifier}][WHERE ${vars.filter} = \"${item}\"]`;\n return await sdk.getDatastoreQuerySql(sql);\n }\n\n for (let distributionId of distributions) {\n items.forEach(item => {\n fetchDataPromises.push(fetchData(distributionId, item));\n })\n }\n\n return await Promise.all(fetchDataPromises);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":37,"value":"raw_data = getAllData(medicines, {filter: \"ndc_description\", xAxis: \"nadac_per_unit\", yAxis: \"as_of_date\", zAxis: \"effective_date\"}, distrIDs)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":39,"value":"sorted_data = (raw_data.filter(o => o.length !== 0)).sort((a,b) => (a[0].ndc_description < b[0].ndc_description) ? 1 : -1)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":483,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":41,"value":"clean_data.sort((a,b) => (a.as_of_date > b.as_of_date ? 1 : -1));","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":53,"value":"## Filter data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":379,"value":"An array of objects on either as_of_date or effective_date is needed for plotting. In the NADAC 2021 dataset, the ACNE MEDICATION 10% GEL has the same prices for the same values in effective_date as shown below. The filter_dt(date) method results in an array of objects that have a unique combination of date and price. In other words, filter_dt('effective_date') removes repeats from the array.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":440,"value":"nadac_2021_data","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":43,"value":"filter_dt = function(date){\n let res = [];\n for(let i=0; i item[0] == o1[0] && item[1] == o1[1]))) {\n arr.push(o1)\n let o2 = {ndc_description: clean_data[i][j].ndc_description, \n nadac_per_unit: clean_data[i][j].nadac_per_unit, \n date: clean_data[i][j][date], \n pricetype: date}\n res[i].push(o2); \n }\n }\n res = res.sort((a,b) => (a.date > b.date ? 1 : -1));\n }\n \n return res;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":58,"value":"## Group duplicates","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":524,"value":"filter_dt('effective_date')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":533,"value":"group_duplicates('effective_date')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7,"value":"// To be used on a specific type of drug\ncheck_duplicates = function(date) {\n let res = [], x;\n for(let i=0; i (a.date > b.date ? 1 : -1)), {x: \"date\", y: \"nadac_per_unit\", fy: \"ndc_description\", stroke: \"date_type\"}) // fy: vertical facets\n ]\n})\n","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W33","stdlib":"1","titling":"auto"}} 30:"$2f:body"