31:T536,markdeep`

Rabindranath Tagore (1861-1941) composed around 2,000 songs that came to be considered as a genre in Bengali music: Rabindrasangit or Rabindrasangeet, literally Rabindra-music. The songs are organized under 17 categories in the compendium Gitabitan / Gītabitān / Geetabitan (the *Garden of Songs*). As a dataset, Rabindrasangeet has approximately **280** unique Raags/Rāgas/*tunes*, **64** Taals/Tālas/*rhythms*, **17** Parjay/Paryāya/*thematic categories* further divided into **36** Upa-parjays or *sub-categories*. The categorization was mostly done under Tagore's guidance, when the first edition of the **Gītabitān** was published. The dataset used in this draft visualization is follows the romanization scheme of the website [geetabitan.com](https://www.geetabitan.com/). The data has been cleaned, the romanization has been slightly altered in the *thematic categories* and *sub-categories*. However, most duplicate listings of songs have been retained, on the basis of variation in categorization of Parjay or Raag or Taal. The uniqe number of songs in the dataset is **1,713**, and the number with duplicate listings is **1,982**.

`32:T444,chartP = { const arcs = pie(Prakriti); const svg = d3 .create("svg") .attr("viewBox", [-width / 2, -height1 / 2, width, height1]); svg .append("g") .attr("stroke", "white") .selectAll("path") .data(arcs) .join("path") .attr("fill", (d) => colorUpa(d.data.UpaParjay)) .attr("d", arc) .append("title") .text((d) => `${d.data.UpaParjay}: ${d.data.count} songs`); svg .append("g") .attr("font-family", "sans-serif") .attr("font-size", 12) .attr("text-anchor", "middle") .selectAll("text") .data(arcs) .join("text") .attr("transform", (d) => `translate(${arcLabel.centroid(d)})`) .call((text) => text .append("tspan") .attr("y", "-0.4em") .attr("font-weight", "bold") .text((d) => d.data.UpaParjay) ) .call((text) => text .filter((d) => d.endAngle - d.startAngle > 0.25) .append("tspan") .attr("x", 0) .attr("y", "0.7em") .attr("fill-opacity", 0.7) .text((d) => d.data.count) ); return svg.node(); }33:T43f,chartT = { const arcs = pieTaal(onlyTaal); const svg = d3 .create("svg") .attr("viewBox", [-width / 2, -height1 / 2, width, height1]); svg .append("g") .attr("stroke", "white") .selectAll("path") .data(arcs) .join("path") .attr("fill", (d) => colorTaal2(d.data.Taal)) .attr("d", arcTaal) .append("title") .text((d) => `${d.data.Taal}: ${d.data.count} songs`); svg .append("g") .attr("font-family", "sans-serif") .attr("font-size", 12) .attr("text-anchor", "middle") .selectAll("text") .data(arcs) .join("text") .attr("transform", (d) => `translate(${arcLabel.centroid(d)})`) .call((text) => text .append("tspan") .attr("y", "-0.4em") .attr("font-weight", "bold") .text((d) => d.data.Taal) ) .call((text) => text .filter((d) => d.endAngle - d.startAngle > 0.25) .append("tspan") .attr("x", 0) .attr("y", "0.7em") .attr("fill-opacity", 0.7) .text((d) => d.data.count) ); return svg.node(); }34:Ta70,chart = { replay; const links = dataClusters.links.map((d) => Object.create(d)); const nodes = dataClusters.nodes.map((d) => Object.create(d)); console.log(nodes); //create simulation, nodes, links const simulation = d3 .forceSimulation(nodes) .force( "link", d3.forceLink(links).id((d) => d.name) ) .force("charge", d3.forceManyBody().strength(-1)) .force("center", d3.forceCenter(width / 2, heightH / 2)); const svg = d3.create("svg").attr("viewBox", [0, 0, width, heightH]); //create links const link = svg .append("g") .selectAll(".link") .data(links) .join("g") .attr("class", "link") .call(drag(simulation)); //create lines to SHOW the links const line = link .append("line") .attr("stroke", "#cccccc") .attr("stroke-opacity", 0) .attr("stroke-dasharray", "2"); //add css attribute "title" to each link; this is visible only with a tooltip link.append("title").text((d) => d.relation); //create colors for each node const groups = [ "Puja", "Prem", "Prakriti", "Geetinatya O Nrityanatya", "Bichitra", "Natyageeti", "Prem O Prakriti", "Puja O Prarthana", "Swadesh", "Anushthanik", "Bhanusingha Thakurer Padabali", "Jatiya Sangeet", "Aanushthanik Sangeet", "Nrityanatya Mayar Khela", "Porishishta 3", "Bhumika", "Porishodh" ]; const colorN = d3.scaleOrdinal().domain(groups).range(d3.schemeTableau10); //create the nodes const node = svg .append("g") .selectAll(".node") .data(nodes) .join("g") .attr("class", "node") .call(drag(simulation)); //create circles to SHOW the nodes const circle = node .append("circle") .attr("stroke", null) .attr("stroke-width", 1.5) .attr("fill", (d) => colorN(d.group)) .attr("opacity", 1) .attr("r", function (d) { return r(d.nodesize); }) .call(drag(simulation)); node .append("title") .text((d) => `${d.nodesize} songs in the cluster "${d.name}" `); const text = node .append("text") .attr("font-family", "HelveticaNeue-Light") .attr("font-size", "18px") .attr("text-anchor", "middle") .attr("stroke", "#2D2D34") .text(function (d) { return ""; }); simulation.on("tick", () => { line .attr("x1", (d) => d.source.x) .attr("y1", (d) => d.source.y) .attr("x2", (d) => d.target.x) .attr("y2", (d) => d.target.y); text.attr("x", (d) => d.x).attr("y", (d) => d.y); circle.attr("cx", (d) => d.x).attr("cy", (d) => d.y); }); invalidation.then(() => simulation.stop()); return svg.node(); }35:[{"id":"62f0c7b9aa62d94e4765338fea3d2ab6435a3f2af39efa4ab9febc99c14c5a6f3d79f79f18e36bf7a572b84f8cd426b4ca87abf79ea272646a3dafed127cc103","href":"https://static.observableusercontent.com/files/62f0c7b9aa62d94e4765338fea3d2ab6435a3f2af39efa4ab9febc99c14c5a6f3d79f79f18e36bf7a572b84f8cd426b4ca87abf79ea272646a3dafed127cc103","name":"onlyPrakriti-2.csv","type":"text/csv","lastModified":1652831923553.187,"size":23749},{"id":"efc5589e90e7d759d449474f4c1d5da41a57da7353391d672e32f14f39b59087f9f88cfd1ac52351883bd1ef109075d5657a0c046db7299e7960152f27a7d84e","href":"https://static.observableusercontent.com/files/efc5589e90e7d759d449474f4c1d5da41a57da7353391d672e32f14f39b59087f9f88cfd1ac52351883bd1ef109075d5657a0c046db7299e7960152f27a7d84e","name":"tagoreclusters.json","type":"application/json","lastModified":1652831923553.187,"size":245506},{"id":"d0cc453c6f637559e097ea324d383ed20c6736ed5829c2ae7b0eb3fd845b4322e4c5fa57bd7bf60b7452f9cd6bb984fa6269da30b24d8d20f34d785774467ff7","href":"https://static.observableusercontent.com/files/d0cc453c6f637559e097ea324d383ed20c6736ed5829c2ae7b0eb3fd845b4322e4c5fa57bd7bf60b7452f9cd6bb984fa6269da30b24d8d20f34d785774467ff7","name":"groupbyParjayTaal@2.csv","type":"text/csv","lastModified":1652831923553.187,"size":4935},{"id":"484e3b83271028df6a6a3195c47ff3297708876fdd5e2bfa957a5a4f876b18a74f41da0bfbf4d8f05b7a1a33de256eeb38379293740ec3b30ef66426c6133c39","href":"https://static.observableusercontent.com/files/484e3b83271028df6a6a3195c47ff3297708876fdd5e2bfa957a5a4f876b18a74f41da0bfbf4d8f05b7a1a33de256eeb38379293740ec3b30ef66426c6133c39","name":"tagoreAll_nodupl@3.csv","type":"text/csv","lastModified":1652831923553.187,"size":145004},{"id":"6d20833bc44a1712a97d049b6dcefe577f3c1e074ce91f9e8c58af4f083e46d62d243bfc4f7940899832577eec41c9795e5d8ca41904b25dd05956def77e04d8","href":"https://static.observableusercontent.com/files/6d20833bc44a1712a97d049b6dcefe577f3c1e074ce91f9e8c58af4f083e46d62d243bfc4f7940899832577eec41c9795e5d8ca41904b25dd05956def77e04d8","name":"tagoreParjayCounts@4.csv","type":"text/csv","lastModified":1652831923553.187,"size":641},{"id":"8f05d607845693d4ad79d1c6c8d62470bd79318fa2e71776719d2c89cf2f2a3bcb9080eb0aa96539901c8b2cb455998ce9f8adbc1751e6f198fafd2c6e927c75","href":"https://static.observableusercontent.com/files/8f05d607845693d4ad79d1c6c8d62470bd79318fa2e71776719d2c89cf2f2a3bcb9080eb0aa96539901c8b2cb455998ce9f8adbc1751e6f198fafd2c6e927c75","name":"groupbyTraag@1.csv","type":"text/csv","lastModified":1652831923553.187,"size":10304},{"id":"e0a7e88e59e58c8d31a852cdefffbc344bee488c6f756e42c065bad732e10e6f27c93b11c8753f7b558ab8b5d5567a4006645ce6918d6785446b9cec7b03b9e7","href":"https://static.observableusercontent.com/files/e0a7e88e59e58c8d31a852cdefffbc344bee488c6f756e42c065bad732e10e6f27c93b11c8753f7b558ab8b5d5567a4006645ce6918d6785446b9cec7b03b9e7","name":"tagoreUpaParjayC@3.csv","type":"text/csv","lastModified":1652831923553.187,"size":438},{"id":"cf100a48db8170b6a235847a8bfb0a11db34d97907e5a3996f858afce91298ba4466eb3dd5d40c4e511a1e7bb730de5283a1c2113a9e92fdfdaf9eb8628e686e","href":"https://static.observableusercontent.com/files/cf100a48db8170b6a235847a8bfb0a11db34d97907e5a3996f858afce91298ba4466eb3dd5d40c4e511a1e7bb730de5283a1c2113a9e92fdfdaf9eb8628e686e","name":"ParjayRaag.csv","type":"text/csv","lastModified":1652831923553.187,"size":18101},{"id":"c339d39183665fd48dd3466263eb472d4ffb35415f309581998ab0b0843593453b9c13f834c694d9132ec1edc836678fd5b63df1f43b3c1fcf9bf53dfeb0b9d8","href":"https://static.observableusercontent.com/files/c339d39183665fd48dd3466263eb472d4ffb35415f309581998ab0b0843593453b9c13f834c694d9132ec1edc836678fd5b63df1f43b3c1fcf9bf53dfeb0b9d8","name":"prakriti@1.csv","type":"text/csv","lastModified":1652831923553.187,"size":88},{"id":"4a60ca7b5e0379debd8421e70bf8042b2a0bf05d0787d9e57a85db2f8751596fa687cacc0c89fbedfa6c7632b06098b3f561b8ae3d4655231d5f0038597e3428","href":"https://static.observableusercontent.com/files/4a60ca7b5e0379debd8421e70bf8042b2a0bf05d0787d9e57a85db2f8751596fa687cacc0c89fbedfa6c7632b06098b3f561b8ae3d4655231d5f0038597e3428","name":"musicnotes@1.png","type":"image/png","lastModified":1652831923553.187,"size":6827},{"id":"0f7ebefafe9409e45dcef3c59147b8c9d92aabc2d110e136a30b23fa3bf51eae6b80df05cda5c26409485563f85bcdbc4169c092a64ca9cd3f4d1dc300515e66","href":"https://static.observableusercontent.com/files/0f7ebefafe9409e45dcef3c59147b8c9d92aabc2d110e136a30b23fa3bf51eae6b80df05cda5c26409485563f85bcdbc4169c092a64ca9cd3f4d1dc300515e66","name":"tabla1.jpg","type":"image/jpeg","lastModified":1652831923553.187,"size":133595},{"id":"42d300b336dae168e6e8825b831e37f4afd499c6580536fd2cc72767709b5ae610fa045f20a89d7c706939cd295607a7e42773b0800fe31dd4f79d1a0761e85b","href":"https://static.observableusercontent.com/files/42d300b336dae168e6e8825b831e37f4afd499c6580536fd2cc72767709b5ae610fa045f20a89d7c706939cd295607a7e42773b0800fe31dd4f79d1a0761e85b","name":"onlyTaalmini.csv","type":"text/csv","lastModified":1652831923553.187,"size":130},{"id":"c6490300e970c48ba34a14669ab5ed40ab99f38f0e6ab6e1555ec5db7bc21aa5501e716fde79b04d8aed85205a4f3759253f2e0de725fea36cf8bae1d183128e","href":"https://static.observableusercontent.com/files/c6490300e970c48ba34a14669ab5ed40ab99f38f0e6ab6e1555ec5db7bc21aa5501e716fde79b04d8aed85205a4f3759253f2e0de725fea36cf8bae1d183128e","name":"groupbyPupa.csv","type":"text/csv","lastModified":1652831923553.187,"size":1083}] 2f:{"title":"Working Tagore Songs Dataset: Draft 1","cells":[{"id":522,"value":"md`\n # Working Tagore Songs Dataset: Draft 1\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":629,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":640,"value":" *This project will be updated in future with [ITRANS](https://en.wikipedia.org/wiki/ITRANS) transliteration, and with more links.*","pinned":false,"hidden":false,"mode":"md"},{"id":181,"value":" ","pinned":false,"hidden":false,"mode":"md"},{"id":16,"value":"Plot.plot({\n height: 800,\n width: 1000,\n marginBottom: 150,\n marginTop: 30,\n marginRight: 50,\n marginLeft: 50,\n x: {\n tickRotate: 45,\n label: null,\n domain: tagoreParjayC\n .sort((a, b) => d3.descending(a.count, b.count))\n .map((d) => d.parjay)\n },\n y: {\n grid: true,\n nice: true,\n label: \"Hover over the bars for more information about the categories:\"\n },\n\n marks: [\n Plot.barY(\n tagoreParjayC,\n\n {\n y: \"count\",\n x: \"parjay\",\n order: (a, b) => d3.descending(a.count, b.count),\n title: (d) => `${d.count} songs in category ${d.parjay} (${d.trans})`\n //title: \"parjay\"\n }\n ),\n Plot.crosshairX(tagoreParjayC, { x: \"parjay\", color: \"red\", opacity: 1 }),\n\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1219,"value":"------------------------","pinned":false,"hidden":false,"mode":"md"},{"id":557,"value":"The following **table** allows you to select a single **Parjay** to see all the songs that are categorized under it. \nYou can sort each column alphabetically by clicking the column heading.","pinned":true,"hidden":false,"mode":"md"},{"id":564,"value":"viewof Parjay = Inputs.select(\n dataA.map((d) => d.Parjay),\n { sort: true, unique: true, label: \"Parjay: Thematic Category\" }\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":45,"value":"Inputs.table(selectedParjay, { columnsA })","pinned":true,"hidden":false,"mode":"ojs"},{"id":421,"value":"md`\n\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":161,"value":" \n---------------------\n","pinned":false,"hidden":false,"mode":"md"},{"id":391,"value":" \n\nRabindrasangeet inherits its **6** seasons from the Sanskrit literary tradition. The songs on Barsha, the rainy season, often evoke motifs from Kalidasa's works. \nBesides the songs that are categorized under the **6** seasons, there are 8 songs that are categorized as 'Sadharon/General' under 'Prakriti.'","pinned":false,"hidden":false,"mode":"md"},{"id":398,"value":"| Grīshma: **Summer**, 15 songs \n| Barsha: **Rainy Season**, 107 songs \n| Sharat: **Early Autumn**, 35 songs \n| Hemanta: **Late Autumn**, 5 songs \n| Sheet: **Winter**, 13 songs \n| Basanta: **Spring**, 94 songs \n Besides these, there are **8** songs that are categorized as **Sadharon/General** under **Prakriti.**","pinned":false,"hidden":false,"mode":"md"},{"id":323,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1004,"value":"md`\n\n\n\n\n\n\n\n\n\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1224,"value":"Here are all the songs from the Prakriti Parjay, in tabular form. Select by each Season, or browse the general/Sadharon category.","pinned":false,"hidden":false,"mode":"md"},{"id":1233,"value":"viewof Ritu = Inputs.select(\n onlyPrakriti.map((d) => d.Ritu),\n { sort: true, unique: true, label: \"Select Ritu or Season\" }\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":1252,"value":"Inputs.table(selectedRitu, { columnsP })","pinned":true,"hidden":false,"mode":"ojs"},{"id":1236,"value":"md`\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n`\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":1240,"value":"md`\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":468,"value":"markdeep`\n## Parjay and Taal: Synergy Part 1\n\n

\n**Dadra**, a rhythm of 6 beats divided into two parts of 3 beats each, is the most popular Taal in the entire corpus of Rabindrasangeet. A total of **675** songs are set to *Dadra* rhythm, followed by **348** songs in *Kaharwa*, **220** songs in *Ektaal*, **181** songs in *Tritaal*, 115 in *Jhaptaal*, 95 songs in *Teora* etc. \n\nBut how are the Taals aligned with the themes of the songs? There is not much anomaly there, as *Dadra* seems to be the dominant Taal in each Parjay.\n\nThe color code for the most used *Taals* are given below: you can also hover over the color blocks in the graph to see the name of the *Taal*.

\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":705,"value":"| Dadra: 6 beats: 3|3 \n| Kaharwa: 8 beats: 4|4 \n| Tritaal: 16 beats: 4|4|4|4 \n| Jhaptaal: 10 beats: 2|3|2|3 \n| Teora: 7 beats: 3|2|2 \n| Sasthi: 6 beats: 4|2 \n| Ektaal: 12 beats: 3|3|3|3 \n","pinned":false,"hidden":false,"mode":"md"},{"id":680,"value":"Plot.plot({\n marginLeft: 50,\n marginBottom: 150,\n marginTop: 50,\n width: 1200,\n height: 900,\n color: {\n range: d3.schemePastel2\n .concat(d3.schemeTableau10)\n .concat(d3.schemeCategory10)\n },\n\n x: {\n tickRotate: 45,\n label: \"Parjay\",\n domain: tagoreParjayC\n .sort((a, b) => d3.descending(a.count, b.count))\n .map((d) => d.parjay)\n },\n y: {\n grid: true,\n label: \"count\"\n },\n\n marks: [\n Plot.barY(byParjayTaal, {\n x: \"Parjay\",\n order: (a, b) => d3.descending(a.count, b.count),\n y: \"count\",\n rx: 5,\n title: (d) =>\n `${d.count} Song/s set to ${d.Taal} Taal in ${d.Parjay} Parjay`,\n fill: (d) => d.Taal\n }),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1007,"value":"Here is a view of the frequency of **Taals** in the entire corpus.","pinned":false,"hidden":false,"mode":"md"},{"id":878,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":1012,"value":"md`\n\n\n\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":733,"value":"------------------","pinned":false,"hidden":false,"mode":"md"},{"id":1072,"value":"The following table allows you to select a single Taal to see all songs that utilize it. \nYou can sort each column alphabetically by clicking the column heading.","pinned":false,"hidden":false,"mode":"md"},{"id":1058,"value":"viewof Taal = Inputs.select(\n dataA.map((d) => d.Taal),\n { sort: true, unique: true, label: \"Taal\" }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1067,"value":"Inputs.table(selectedTaal, { columnsA })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1016,"value":"md`\n\n\n\n\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1243,"value":"md`\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":761,"value":"markdeep`\n## Parjay and Raag: Synergy Part 2\n\n

\n**Bhairavi**, a morning Raag, is the most popular Raag in the entire corpus of Rabindrasangeet. A total of **181** songs are set to *Bhairavi*, followed by **82** songs in *Baul-Sur*, **82** songs in *Pilu*, **81** songs in *Behag*, 77 in the *Kirtan* style, **77** songs in *Khambaj*, **60** songs in *Kafi*, etc. \n\nHow are the Raags aligned with the themes of the songs? *Bhairavi* seems to be the dominant Raag in the top Parjays. \n\nHover over each block of color in the following graph to have the name of the *Raag* displayed.\n

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1047,"value":"

","pinned":false,"hidden":false,"mode":"html"},{"id":1032,"value":"md`\n\n\n\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1026,"value":"Raags in each Parjay: hover over each color block in the following graph to see the name of the **Raag**.","pinned":false,"hidden":false,"mode":"md"},{"id":769,"value":"Plot.plot({\n marginLeft: 50,\n marginBottom: 150,\n marginTop: 50,\n width: 1200,\n height: 800,\n color: {\n range: d3.schemePastel1\n .concat(d3.schemeDark2)\n .concat(d3.schemeAccent)\n .concat(d3.schemePaired)\n },\n x: {\n tickRotate: 45,\n label: \"Parjay\",\n domain: byParjayRaag\n .sort((a, b) => d3.descending(a.count, b.count))\n .map((d) => d.Parjay)\n },\n y: {\n grid: true\n },\n\n marks: [\n Plot.barY(byParjayRaag, {\n x: \"Parjay\",\n order: (a, b) => d3.descending(a.count, b.count),\n y: \"count\",\n rx: 5,\n title: (d) => `${d.count} Song/s in ${d.Raag} within ${d.Parjay} Parjay`,\n fill: (d) => d.Raag\n }),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":677,"value":"------------------","pinned":false,"hidden":false,"mode":"md"},{"id":1077,"value":"The Raags used in Rabindrasangeet are far too many to provide a color index. \nThe following table allows you to select a single Raag to see all the songs based on it. \n*The Raag column also includes the Tunes, including the English songs that Tagore borrowed from \n*. \n\nYou can sort each column alphabetically by clicking the column heading.","pinned":false,"hidden":false,"mode":"md"},{"id":1083,"value":"viewof Raag = Inputs.select(\n dataA.map((d) => d.Raag),\n { sort: true, unique: true, label: \"Raags/Scales and Tunes\" }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1085,"value":"Inputs.table(selectedRaag, { columnsA })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1246,"value":"md`\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1307,"value":"\n## Clusters: Parjay + Raag + Taal\n\n

\nWe have so far seen the synergy between *Parjay and Raag* and *Parjay and Taal*. But how about popular combinations of all three? The following network graph is an experimental visualization of the clusters of *Parjay*-*Raag*-*Taal*. The biggest cluster is of **24** songs, in the *Puja Parjay*, *Baul*-*Sur* *Raag/Tune*, and *Dadra* *Taal/Rhythm*. The size of the circles correspond with the size of the cluster, i.e., the number of songs in each cluster. \n\n\n\nThe color code for the *Parjays* of ther clusters are given below: you can also **hover** over the circles for a description of the clusters and the number of songs included in it. To avoid overcrowding, the actual songs are not visible on hover; but you can see them in tabular form using the select function that follows the graph. Inside the graph, feel free to drag and move the circles around.

\n\n","pinned":false,"hidden":false,"mode":"md"},{"id":1338,"value":"swatches({\n color: d3.scaleOrdinal(\n [\n \"Puja\",\n \"Prem\",\n \"Prakriti\",\n \"Geetinatya O Nrityanatya\",\n \"Bichitra\",\n \"Natyageeti\",\n \"Prem O Prakriti\",\n \"Puja O Prarthana\",\n \"Swadesh\",\n \"Anushthanik\",\n \"Bhanusingha Thakurer Padabali\",\n \"Jatiya Sangeet\",\n \"Aanushthanik Sangeet\",\n \"Nrityanatya Mayar Khela\",\n \"Porishishta 3\",\n \"Bhumika\",\n \"Porishodh\"\n ],\n d3.schemeTableau10\n ),\n columns: \"180px\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1390,"value":"md`\n\n\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1438,"value":"viewof replay = html`

${pageTitle}