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","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":886,"value":"#### Disclaimer: This is work in progress. This is a live document and it will be updated once the last episode is released.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":987,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":761,"value":"So what is **Cillian Murphy's limited Edition Show?** A quote from BBC website:\n> A nocturnal playlist made to play after dark, with music from all corners of Cillian Murphy's record collection","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":766,"value":"As we approach the end of Cillian's program, I have decided to gather data about tracks Cillian played across **9 shows** to break it down and do a bit of analysis. I wanted to understand if I could see or find any patterns in song/artists selection.\n\nI have** 4 charts and a CSV table**. The CSV table is searchable and contains data related to each episode and each track. I used the `search` Spotify API endpoint to get track related information. For some of them I had to use old school Google method to cover gaps in release dates or genres.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":989,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":811,"value":"## Summary:\nAcross **${combindeByEpisode.length}** episodes:\n* **${combinedArray.length} ** unique tracks were played.\n* **${arrayOfArtists.length} ** unique artists were featured.\n* Tracks featured on the show belonged to **${arrayOfGenreObjects.length}** different genres.\n* The most featured artist is **Walter Wanderley** with ***9*** features. **Walter Wanderley** appeared in every single episode so far.\n* On the second place **PJ Harvey** with *3* features.\n* Third place belongs to *${arrayOfArtists.filter(artist => artist.songs.length === 2).map(({artist}) => artist).join(\", \")}* with **2** features.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":991,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":789,"value":"## Songs Genre","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":608,"value":"viewof numberOfSongsGenre = Inputs.range([0, d3.max(arrayOfGenreObjects, d => d.songs.length)], {label: \"Minimum Songs Filter Selector\", step: 1})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":791,"value":"Probably the most interesting chart in this notebook. This chart is _looooooooooooong_, due to the high number of genres **(${arrayOfGenreObjects.length})**. This chart is interactive. It allows you to tweak the minimum number of songs that belong to a specific genre. I set the number high, but if you'd like to explore all the possible genres that were featured on the show, just set a slider to 1","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":219,"value":"Plot.plot({\n\tmarginBottom: 32,\n marginLeft: 100,\n height: 100 + word_count.length * 28,\n x: { label: \"Count\", tickRotate: 90 },\n y: { label: \"Words\" },\n grid: true,\n color: { label: \"Word Frequency\", legend: true, scheme: \"Viridis\" },\n marks: [\n Plot.barX(\n word_count,\n {\n x: \"count\",\n y: \"word\",\n fill: \"count\",\n sort: { y: \"x\", reverse: true },\n }\n ),\n ],\n\ttooltip: {\n\t\tstroke: \"orange\",\n\t\topacity: 0.75,\n\t},\n});\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":993,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":757,"value":"## Number of Tracks player per Episode","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":769,"value":"A simple line chart that shows the number of tracks played for each episode. We can see that the median number of tracks played was **30**. Episode# 3 had the least amount of tracks **(26)**, while Episode# 6 had the record amount of **(32)**.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":698,"value":"Plot.plot({\n\tgrid: true,\n\tx: {\n\t\tticks: combindeByEpisode.length,\n\t},\n y: {\n tickFormat: d3.format(\"d\"),\n tickStep: 1 \n },\n\tmarks: [\n\t\tPlot.ruleY([d3.median(combindeByEpisode, (d) => d.count)], {\n\t\t\tstroke: \"orange\",\n\t\t\tstrokeWidth: 2,\n\t\t}),\n\t\tPlot.lineY(combindeByEpisode, {\n\t\t\tx: \"episode\",\n\t\t\ty: \"count\",\n\t\t\tcurve: \"cardinal\",\n\t\t\tstrokeWidth: 3,\n stroke: \"steelblue\"\n\t\t}),\n\t\tPlot.dot(combindeByEpisode, {\n\t\t\tx: \"episode\",\n\t\t\ty: \"count\",\n\t\t\tstroke: \"steelblue\",\n\t\t\tr: 6,\n\t\t\tfill: \"white\",\n\t\t\ttitle: (d) => d.count,\n\t\t}),\n\t],\n});\n","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":996,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":778,"value":"## Number of Songs for a Specific Year","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":776,"value":"This chart is a bit more interesting. It shows a pattern that Cillian tried to play the most recently released tracks **from 2023 (52)**. The oldest track **is from 1929**. It was _featured in Episode 6, Artist - \"Amadie Breaux, Ophey Breaux & Cleoma Breaux, Amédée Breaux, Ophy Breaux & Cléoma Falcon\" & title - \"Ma Blond Est Partie\"_. The genre of this track is called Cajun (Cajun music, an emblematic music of Louisiana played by the Cajuns, is rooted in the ballads of the French-speaking Acadians of Canada).\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":350,"value":"Plot.plot({\n marginBottom: 72,\n width: 1000,\n grid: true,\n x: {tickRotate: 90},\n color: {label: \"Number of Songs\", scheme: \"Viridis\", legend: true, domain: [0, d3.max(transformedDataByYear, d => d.count)]},\n marks: [\n Plot.barY(transformedDataByYear, {x: d => new Date(d.year, 0, 1).getFullYear(), y: \"count\", fill: \"count\", \n title: (d) =>\n\t\t\t\t\t\t`Number of songs: ${d.songs.length}\\n` +\n\t\t\t\t\t\td.songs.map((song) => song.Artist + \" - \" + song.Title).join(\"\\n\"),\n\t\t\t\t}) \n ],\n tooltip: {\n stroke: \"orange\",\n opacity: 0.75\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":999,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":780,"value":"## Number of Songs per Decade","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":782,"value":"Cillian Murphy's playlists lean heavily towards the new era, favoring songs released from the year 2000 onwards. In fact, **${transformedDataByDecade.filter(d => d.year >= 2000).reduce((acc, d) => acc + d.count, 0)}** out of **${transformedDataByDecade.reduce((acc, d) => acc + d.count, 0)}** songs played come from this period, making up **${((transformedDataByDecade.filter(d => d.year >= 2000).reduce((acc, d) => acc + d.count, 0) / transformedDataByDecade.reduce((acc, d) => acc + d.count, 0)) * 100).toFixed(2)}%** of his selections. This shows a clear preference for keeping the show's vibe current. \n\nYet, Cillian doesn't forget the classics; there's a solid mix of tracks from the '70s, '60s, '80s, and '90s that get their time to shine, adding a touch of nostalgia to the otherwise modern lineup.\n\n* 90's - ${count90s.toFixed(2)}%\n* 80's - ${count80s.toFixed(2)}%\n* 70's - ${count70s.toFixed(2)}%\n* 60's - ${count60s.toFixed(2)}%\n* 50's - ${count50s.toFixed(2)}%\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":59,"value":"Plot.plot({\n grid: true,\n color: { scheme: \"Viridis\", legend: true, domain: [0, d3.max(transformedDataByDecade, d => d.count)] },\n x: {\n label: \"Decade\",\n tickFormat: d => \"'\" + String(new Date(d).getFullYear()).slice(-2) + \"s\"\n },\n marks: [\n Plot.ruleY([d3.median(transformedDataByDecade, (d) => d.count)], {\n\t\t\tstroke: \"orange\",\n\t\t\tstrokeWidth: 2,\n\t\t}),\n Plot.barY(transformedDataByDecade, {x: d => new Date(d.year, 1,0), y: \"count\", fill: \"count\", title: \"count\"}),\n ],\n tooltip: {\n stroke: \"orange\",\n opacity: 0.75\n }\n});","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1002,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":799,"value":"### CSV Table","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":800,"value":"This table is not very easy to navigate. However, it is searchable. You can search by artist, genre or release date. It also contains the entire dataset for all 9 shows. I assumed if you scrolled all the way down here, I might as well show this to you.\n\nThis can be used as a database. Unfortunately, some some release dates might be a bit messed up, but I tried my beast to rely on Spotify or otherwise google the dates myself.\n\nI spent the most amount of time trying to find release dates for some of the not very known tracks.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":681,"value":"DataSet = await FileAttachment(\"convertcsv.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1025,"value":"viewof artistSearchValue = Inputs.text({label: \"Find Artist\"})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1018,"value":"### List of Artists Featured on the Show","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1016,"value":"Plot.plot({\n marginBottom: 48,\n marginLeft: 180,\n height: artistSearchValue.length ? (fileteredArrayOfArtists.length * 24) + 100 : (arrayOfArtists.length * 24) + 100,\n x: {label: null, tickRotate: 90, ticks: 1},\n y: {label: null},\n grid: true,\n color: {label: \"Number of Songs\", legend: true, scheme: \"Viridis\"},\n marks: [\n Plot.barX(artistSearchValue.length ? fileteredArrayOfArtists : arrayOfArtists, Plot.groupY({x: (d) => d[0].songs.length}, {fill: (d) => d.songs.length, y: \"artist\", title: (d) => d.songs.length, sort: {y: \"x\", reverse: true}})),\n Plot.ruleX([0])\n ], \n tooltip: {\n stroke: \"orange\",\n opacity: 0.75\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":883,"value":"Thank you for your attention :)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":5,"value":"### Appendix","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":260,"value":"arrayOfGenreObjects = Array.from(combinedByGenre, ([genre, songs]) => ({\n genre: genre,\n songs: songs\n}));","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1022,"value":"fileteredArrayOfArtists = arrayOfArtists.filter(d => d.artist.includes(artistSearchValue))","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":437,"value":"arrayOfArtists = Array.from(combinedArtistData, ([artist, songs]) => ({\n artist: artist,\n songs: songs\n}));","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":617,"value":"genreFiltered = arrayOfGenreObjects.filter(genre => genre.songs.length >= numberOfSongsGenre);","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":224,"value":"combinedByGenre = Object.entries(combinedArray.reduce((acc, song) => {\n if (song && song[\"Genre\"] && song[\"Genre\"].length > 0 && Array.isArray(song[\"Genre\"])) {\n song[\"Genre\"].forEach(genre => {\n if (!acc[genre]) {\n acc[genre] = [];\n }\n acc[genre].push(song);\n });\n }\n return acc; // Return the accumulator for the next iteration\n}, {}))\n\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":178,"value":"transformedDataByDecade = Object.values(Array.from(combinedYearlyData).reduce((acc, [year, data]) => {\n // Calculate the decade\n const decade = Math.floor(year / 10) * 10;\n\n // If the decade doesn't exist in the accumulator, initialize it\n if (!acc[decade]) {\n acc[decade] = { year: decade, count: 0 };\n }\n\n // Sum up the count for the decade\n acc[decade].count += data.length;\n\n return acc;\n}, {}));\n ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":76,"value":"transformedDataByYear = Array.from(combinedYearlyData).map(([year, data]) => ({\n year: year,\n count: data.length,\n songs: data\n}));","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":64,"value":"combinedYearlyData = d3.group(combinedArray, d => new Date(d[\"Release Date\"]).getFullYear())","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":455,"value":"combindeByEpisode = Array.from(d3.group(combinedArray, d => d.Episode)).map(([episode, data]) => ({\n episode: episode,\n count: data.length,\n songs: data\n}));","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":66,"value":"combinedArray = [...bbc_c_murphy_e12, ...bbcCilliamM2, ...bbcCilliamM34, ...bbcCillian41, ...bbcCilliamM51, ...bbcCilliamM62, ...bbcCilliamM71, ...bbcCilliamM81, ...bbcCilliamM92]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":38,"value":"combinedArtistData = d3.group(combinedArray, d => d.Artist)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":569,"value":"bbc_c_murphy_e12 = FileAttachment(\"bbc_c_murphy_e1@2.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":503,"value":"bbcCilliamM2 = FileAttachment(\"bbc-cilliam-m-2.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":572,"value":"bbcCilliamM34 = FileAttachment(\"bbc-cilliam-m-3@4.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":524,"value":"bbcCillian41 = FileAttachment(\"bbc-cillian-4@1.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":527,"value":"bbcCilliamM51 = FileAttachment(\"bbc-cilliam-m-5@1.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":537,"value":"bbcCilliamM62 = FileAttachment(\"bbc-cilliam-m-6@2.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":534,"value":"bbcCilliamM71 = FileAttachment(\"bbc-cilliam-m-7@1.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":540,"value":"bbcCilliamM81 = FileAttachment(\"bbc-cilliam-m-8@1.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":576,"value":"bbcCilliamM92 = FileAttachment(\"bbc-cilliam-m-9@2.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":374,"value":"import {Plot} from \"@mkfreeman/plot-tooltip\"","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":941,"value":"count90s = (transformedDataByDecade.filter(d => d.year >= 1990 && d.year < 2000).reduce((acc, d) => acc + d.count, 0) / transformedDataByDecade.reduce((acc, d) => acc + d.count, 0)) * 100","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":944,"value":"count80s = (transformedDataByDecade.filter(d => d.year >= 1980 && d.year < 1990).reduce((acc, d) => acc + d.count, 0) / transformedDataByDecade.reduce((acc, d) => acc + d.count, 0)) * 100","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":946,"value":"count70s = (transformedDataByDecade.filter(d => d.year >= 1970 && d.year < 1980).reduce((acc, d) => acc + d.count, 0) / transformedDataByDecade.reduce((acc, d) => acc + d.count, 0)) * 100","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":948,"value":"count60s = (transformedDataByDecade.filter(d => d.year >= 1960 && d.year < 1970).reduce((acc, d) => acc + d.count, 0) / transformedDataByDecade.reduce((acc, d) => acc + d.count, 0)) * 100","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":950,"value":"count50s = (transformedDataByDecade.filter(d => d.year >= 1950 && d.year < 1960).reduce((acc, d) => acc + d.count, 0) / +transformedDataByDecade.reduce((acc, d) => acc + d.count, 0)) * 100","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"}],"files":"$W31","stdlib":"1","titling":"auto"}} 30:"$2f:body"