{"nbformat_minor": 2, "cells": [{"source": "# A sentiment(al) analysis of why Red Dwarf is no longer funny (to me)", "cell_type": "markdown", "metadata": {}}, {"source": "## A Jupyter [Data] Mining Corp Investigation", "cell_type": "markdown", "metadata": {}}, {"source": "What follows is a faux analysis of the humour in Red Dwarf and why it seems to be waning in recent series. While undoubtedly tounge-in-cheek, I have endeavoured to bring modern method, tools and techniques to bear on the question of whether Red Dwarf is less amusing now than when it started.\n\nThis investigation uses F# as the central language for data analysis and employs the following packages:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 1, "cell_type": "code", "source": "#load \"Paket.fsx\"\n\nPaket.Dependencies.Install \"\"\"\nframeworks: net45\nsource https://nuget.org/api/v2\nnuget FSharp.Data\nnuget XPlot.GoogleCharts\n\"\"\"\n\nPaket.LoadingScripts.ScriptGeneration.generateScriptsForRootFolder \n   Paket.LoadingScripts.ScriptGeneration.FSharp\n   (Paket.FrameworkIdentifier.DotNetFramework Paket.FrameworkVersion.V4_5)\n   (System.IO.DirectoryInfo __SOURCE_DIRECTORY__)\n   \n#load \"paket-files/include-scripts/net45/include.main.group.fsx\"\n//#load \"XPlot.Plotly.Paket.fsx\"\n//#load \"XPlot.Plotly.fsx\"\n\nopen System\nopen System.IO\nopen FSharp.Data\nopen FSharp.Data.JsonExtensions\nopen XPlot\nopen XPlot.GoogleCharts", "outputs": [], "metadata": {"collapsed": false}}, {"source": "I also (temporarily) need a custom display printer to support XPlot.GoogleCharts (pending the resolution of an [issue](https://github.com/fsprojects/IfSharp/issues/118))", "cell_type": "markdown", "metadata": {}}, {"execution_count": 2, "cell_type": "code", "source": "open IfSharp.Kernel.App\n\n@\"<script src=\"\"https://www.google.com/jsapi\"\"><\/script>\" |> Util.Html |> Display\n\ntype XPlot.GoogleCharts.GoogleChart with\n  member __.GetContentHtml() =\n    let html = __.GetInlineHtml()\n    html\n      .Replace (\"google.setOnLoadCallback(drawChart);\", \"google.load('visualization', '1.0', { packages: ['corechart'], callback: drawChart })\")\n\ntype XPlot.GoogleCharts.Chart with\n  static member Content (chart : GoogleChart) =\n    { ContentType = \"text/html\"; Data = chart.GetContentHtml() }\n\nAddDisplayPrinter (fun (plot: XPlot.GoogleCharts.GoogleChart) -> { ContentType = \"text/html\"; Data = plot.GetContentHtml() })", "outputs": [{"output_type": "display_data", "data": {"text/html": "<script src=\"https://www.google.com/jsapi\"><\/script>"}, "metadata": {}}, {"execution_count": 2, "output_type": "execute_result", "data": {"text/plain": "<null>"}, "metadata": {}}], "metadata": {"collapsed": false}}, {"source": "## Observation\nWhen I read that there would be [new series](https://science.slashdot.org/story/16/09/16/0153249/28-years-a-smeghead-red-dwarf-is-coming-back) of [Red Dwarf](https://en.wikipedia.org/wiki/Red_Dwarf) I was filled with both excitment and dread. Excitement by the thought of new episodes of one of my all time favourite shows and dread that it would be as bad - if not worse - than the series 8, 9 and (shiver) \"X\".\n\nAnd so it was that on 23rd September 2016, I sat with 'bated breath as the opening credits of [Red Dwarf XI](https://www.themoviedb.org/tv/326-red-dwarf/season/11/episode/1) began to roll. Half an hour and just a couple of chuckles later, the best I could say about it was \"Meh\".\n\nUnfortunately, the opening show seemed to be the highlight of the series and, as I ground my way through episode 4, I formed the central observation of this investigation, namely: \"Red Dwarf just isn't funny as funny as it used to be\".\n\n## Formulation\nBut then it occured to me, Red Dwarf's crew weren't the only ones to have aged. I am also older and my tastes have changed significantly since being the spotty pre-teen who first started watching the show back in '88. Perhaps Red Dwarf is as funny now as it always was and *I'm* the one who is no longer funny.\n\nSo: **\"Is Red Dwarf still funny and has my transformation into an adult and parent simply robbed me of my ability to appreciate it? Or has it truely become as humourless as I found it?\"**\n\nAmused by the idea of trying to objectively answer this question, I added a card to the \"Ideas\" column of [my public trello board](https://trello.com/b/KoTWuFUi/public-board) and promptly forgot about it. That was until recently when I encountered [Project Jupyter](http://jupyter.org/) and, consequently, [Azure Notebooks](https://notebooks.azure.com/). The [play-on words](http://reddwarf.wikia.com/wiki/Jupiter_Mining_Corporation) I could use to form the lead of this investigating were just too alluring and so it was that I moved my trello card to \"in-progress\" and began the process of answering this question.\n\n## Information\nAs I form a central part of the question, I needed to remove myself from the equation and endeavour to find an objective measure (well, as objective as possible where humour is involved) of the humourousness of each episode of Red Dwarf. Imdb was the obvious first point of call and, sure enough, they provide a wealth of information about each episode of Red Dwarf including release date and rating. As pretty much every other source of information re tv/movies is able to access information by Imdb rating, I defined the following collection:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 3, "cell_type": "code", "source": "type EpisodeInformation = {\n    Id : string;\n    Season : int\n    Episode : int\n}\n\nlet episodeInformation = [\n    { Id = \"tt0684181\"; Season = 1; Episode = 1 };\n    { Id = \"tt0684157\"; Season = 1; Episode = 2 };\n    { Id = \"tt0684145\"; Season = 1; Episode = 3 };\n    { Id = \"tt0684186\"; Season = 1; Episode = 4 };\n    { Id = \"tt0684151\"; Season = 1; Episode = 5 };\n    { Id = \"tt0684165\"; Season = 1; Episode = 6 };\n    { Id = \"tt0684161\"; Season = 2; Episode = 1 };\n    { Id = \"tt0684146\"; Season = 2; Episode = 2 };\n    { Id = \"tt0684180\"; Season = 2; Episode = 3 };\n    { Id = \"tt0684177\"; Season = 2; Episode = 4 };\n    { Id = \"tt0684175\"; Season = 2; Episode = 5 };\n    { Id = \"tt0684169\"; Season = 2; Episode = 6 };\n    { Id = \"tt0684144\"; Season = 3; Episode = 1 };\n    { Id = \"tt0767232\"; Season = 3; Episode = 2 };\n    { Id = \"tt0684172\"; Season = 3; Episode = 3 };\n    { Id = \"tt0684148\"; Season = 3; Episode = 4 };\n    { Id = \"tt0684185\"; Season = 3; Episode = 5 };\n    { Id = \"tt0684183\"; Season = 3; Episode = 6 };\n    { Id = \"tt0684149\"; Season = 4; Episode = 1 };\n    { Id = \"tt0684152\"; Season = 4; Episode = 2 };\n    { Id = \"tt0684160\"; Season = 4; Episode = 3 };\n    { Id = \"tt0684187\"; Season = 4; Episode = 4 };\n    { Id = \"tt0684153\"; Season = 4; Episode = 5 };\n    { Id = \"tt0684164\"; Season = 4; Episode = 6 };\n    { Id = \"tt0684159\"; Season = 5; Episode = 1 };\n    { Id = \"tt0684182\"; Season = 5; Episode = 2 };\n    { Id = \"tt0684179\"; Season = 5; Episode = 3 };\n    { Id = \"tt0684174\"; Season = 5; Episode = 4 };\n    { Id = \"tt0756588\"; Season = 5; Episode = 5 };\n    { Id = \"tt0684143\"; Season = 5; Episode = 6 };\n    { Id = \"tt0684173\"; Season = 6; Episode = 1 };\n    { Id = \"tt0684163\"; Season = 6; Episode = 2 };\n    { Id = \"tt0684158\"; Season = 6; Episode = 3 };\n    { Id = \"tt0684155\"; Season = 6; Episode = 4 };\n    { Id = \"tt0684176\"; Season = 6; Episode = 5 };\n    { Id = \"tt0756589\"; Season = 6; Episode = 6 };\n    { Id = \"tt0684184\"; Season = 7; Episode = 1 };\n    { Id = \"tt0684178\"; Season = 7; Episode = 2 };\n    { Id = \"tt0684168\"; Season = 7; Episode = 3 };\n    { Id = \"tt0684154\"; Season = 7; Episode = 4 };\n    { Id = \"tt0756587\"; Season = 7; Episode = 5 };\n    { Id = \"tt0684147\"; Season = 7; Episode = 6 };\n    { Id = \"tt0684156\"; Season = 7; Episode = 7 };\n    { Id = \"tt0684166\"; Season = 7; Episode = 8 };\n    { Id = \"tt0684140\"; Season = 8; Episode = 1 };\n    { Id = \"tt0684141\"; Season = 8; Episode = 2 };\n    { Id = \"tt0684142\"; Season = 8; Episode = 3 };\n    { Id = \"tt0684150\"; Season = 8; Episode = 4 };\n    { Id = \"tt0684162\"; Season = 8; Episode = 5 };\n    { Id = \"tt0684170\"; Season = 8; Episode = 6 };\n    { Id = \"tt0684171\"; Season = 8; Episode = 7 };\n    { Id = \"tt0684167\"; Season = 8; Episode = 8 };\n    { Id = \"tt1365540\"; Season = 9; Episode = 1 };\n    { Id = \"tt1371606\"; Season = 9; Episode = 2 };\n    { Id = \"tt1400975\"; Season = 9; Episode = 3 };\n    { Id = \"tt1997038\"; Season = 10; Episode = 1 };\n    { Id = \"tt1999714\"; Season = 10; Episode = 2 };\n    { Id = \"tt1999715\"; Season = 10; Episode = 3 };\n    { Id = \"tt1999716\"; Season = 10; Episode = 4 };\n    { Id = \"tt1999717\"; Season = 10; Episode = 5 };\n    { Id = \"tt1999718\"; Season = 10; Episode = 6 };\n    { Id = \"tt5218244\"; Season = 11; Episode = 1 };\n    { Id = \"tt5218254\"; Season = 11; Episode = 2 };\n    { Id = \"tt5218266\"; Season = 11; Episode = 3 };\n    { Id = \"tt5218284\"; Season = 11; Episode = 4 };\n    { Id = \"tt5218308\"; Season = 11; Episode = 5 };\n    { Id = \"tt5218316\"; Season = 11; Episode = 6 }\n]", "outputs": [], "metadata": {"collapsed": true}}, {"source": "Unfortunately, Imdb doesn't provide any public API for accessing information from their website (apart from some [patchy flat file \"reports\"](http://www.imdb.com/interfaces)) so I looked at using [Omdb](http://www.omdbapi.com/) and [WeMakeSites's IMDB](http://imdb.wemakesites.net/) api but found both these sources returned patchy data. Finally I turned to the [The Movie Db](https://www.themoviedb.org/?language=en) (TMDB) which, once you're registered and have an API key, provided a much better API and very consistent show information.\n\nUsing the code below, I retrieved all information Tmdb had available for each episode of Red Dwarf and saved it locally for future use.", "cell_type": "markdown", "metadata": {}}, {"source": "```\nopen System.IO;\n\nlet writeFile path id (json : string) =\n  let fileName = \"./Data/\" + path + \"/\" + id + \".json\"\n  use streamWriter = new StreamWriter(fileName, false)\n  streamWriter.WriteLine(json)\n\nepisodeInformation\n|> Seq.map (fun es -> System.Threading.Thread.Sleep(1000); es)\n|> Seq.map (fun es -> (es.Id, Http.RequestString (\"https://api.themoviedb.org/3/tv/326/season/\" + es.Season.ToString() + \"/episode/\" + es.Episode.ToString(), query=[\"api_key\", \"<API KEY>\"])))\n|> Seq.iter (fun (id, json) -> writeFile \"TheMovieDb\" id json)\n```", "cell_type": "markdown", "metadata": {"collapsed": true}}, {"source": "> I thought I'd be able to save this data locally within this library but neither the above script nor attempting to manually upload the data to this library succeeded. Reading the [guidance here](https://notebooks.azure.com/faq) I decided to host the data in [Github](https://github.com/ibebbs/RedDwarfAnalysis) instead", "cell_type": "markdown", "metadata": {}}, {"source": "With the Tmdb data stored locally, I could then use the ```JsonValue``` parser from FSharp.Data to dynamically query the content. For example, with the code below:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 4, "cell_type": "code", "source": "let loadTmdbJson id =\n  let fileName = \"https://raw.githubusercontent.com/ibebbs/RedDwarfAnalysis/master/TheMovieDb/\" + id + \".json\"\n  JsonValue.Load(fileName)\n  \ntype TmdbEpisode = {\n  Name : string;\n  Season : int;\n  Episode : int;\n  AirDate : DateTime;\n  Overview : string;\n}\n\nlet parseTmdbJson (json : JsonValue) = {\n  Name = json?name.AsString(); \n  Season = json?season_number.AsInteger(); \n  Episode = json?episode_number.AsInteger(); \n  AirDate = json?air_date.AsDateTime();\n  Overview = json?overview.AsString()\n}", "outputs": [], "metadata": {"collapsed": false}}, {"source": "I can parse any episode's information as shown here:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 5, "cell_type": "code", "source": "\"tt0684181\" |> loadTmdbJson |> parseTmdbJson", "outputs": [{"execution_count": 5, "output_type": "execute_result", "data": {"text/plain": "{Name = \"The End\";\n Season = 1;\n Episode = 1;\n AirDate = 02/15/1988 00:00:00;\n Overview =\n  \"Third technician Dave Lister wakes from stasis to find himself alone aboard the mining ship Red Dwarf, three million years after the end of humanity. His new existence isn\u00e2\u0080\u0099t entirely lonely: also aboard are cowardly hologram Arnold J Rimmer, the ship\u00e2\u0080\u0099s senile computer Holly, and an evolved, self-absorbed descendant of his pet cat. Unfortunately, there\u00e2\u0080\u0099s little left to do in the universe but bicker with his unlikely new friends, make a pig sty out of his bunk and, unwittingly, eat the powdered remains of his former crewmates.\";}"}, "metadata": {}}], "metadata": {"collapsed": false}}, {"source": "While Tmdb provides some rating information, to answer the fundamental question of this investigation I needed to find detailed rating information, at a show level, ideally with a demographic breakdown. In this it seemed that [Imdb](http://www.imdb.com/title/tt0684181/ratings) was the only game in town so, although against their terms of service, I decided to scrape the information from the site.\n\nAs before I wrote the code below to download all rating information Imdb had for each episode of Red Dwarf into a local store:", "cell_type": "markdown", "metadata": {}}, {"source": "```\nepisodeInformation\n|> Seq.map (fun es -> System.Threading.Thread.Sleep(1000); es)\n|> Seq.map (fun es -> (es.Id, Http.RequestString (\"http://www.imdb.com/title/\" + es.Id + \"/ratings\")))\n|> Seq.iter (fun (id, json) -> writeHtml \"Ratings\" id json)\n```", "cell_type": "markdown", "metadata": {"collapsed": true}}, {"source": "I then wrote the following to parse the vote/rating information for each category of demographic and for a specific episode:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 6, "cell_type": "code", "source": "let ratingCategoryNames = [\n  \"Males\";\n  \"Females\";\n  \"Aged under 18\";\n  \"Males under 18\";\n  \"Aged 18-29\";\n  \"Males Aged 18-29\";\n  \"Females Aged 18-29\";\n  \"Aged 30-44\";\n  \"Males Aged 30-44\";\n  \"Females Aged 30-44\";\n  \"Aged 45+\";\n  \"Males Aged 45+\";\n  \"Females Aged 45+\";\n  \"Top 1000 voters\";\n  \"US users\";\n  \"Non-US users\";\n]\n\ntype RatingCategory =\n  | ``Males`` = 0\n  | ``Females`` = 1\n  | ``Aged under 18`` = 2\n  | ``Males under 18`` = 3\n  | ``Aged 18-29`` = 4\n  | ``Males Aged 18-29`` = 5\n  | ``Females Aged 18-29`` = 6\n  | ``Aged 30-44`` = 7\n  | ``Males Aged 30-44`` = 8\n  | ``Females Aged 30-44`` = 9\n  | ``Aged 45`` = 10\n  | ``Males Aged 45`` = 11\n  | ``Females Aged 45`` = 12\n  | ``Top 1000 voters`` = 13\n  | ``US users`` = 14\n  | ``Non-US users`` = 15\n\ntype EpisodeRatings = {\n    Id : string;\n    Category : RatingCategory;\n    Votes : int;\n    Rating : decimal\n}\n\nlet parseCategory c =\n  let index = Seq.tryFindIndex (fun cn -> cn = c) ratingCategoryNames\n  match index with\n  | Some x -> Some (enum<RatingCategory>(x))\n  | None -> None\n\nlet parseRatings id =\n  let title (node : HtmlNode) =\n      node.Descendants[\"a\"]\n      |> Seq.map (fun d -> d.InnerText())\n  \n  let votes (node : HtmlNode) =\n      [ node.InnerText() ]\n  \n  let rating (node : HtmlNode) =\n      [ node.InnerText() ]\n  let document = HtmlDocument.Load(\"https://raw.githubusercontent.com/ibebbs/RedDwarfAnalysis/master/Ratings/\" + id + \".html\")\n  let content = document.CssSelect(\"#tn15content\").[0]\n  let tables = \n    content.Descendants[\"table\"]\n    |> Seq.toArray\n  let rows =\n    tables.[1].Descendants[\"tr\"]\n    |> Seq.map (fun row -> (row, row.Descendants[\"td\"] |> Seq.toArray))\n    |> Seq.where (fun (row, data) -> data.Length = 3)\n    |> Seq.map (fun (row, data) -> ( (title data.[0]), (votes data.[1]), (rating data.[2])))\n    |> Seq.collect (fun (t, v, r) -> Seq.zip3 t v r)\n    |> Seq.map (fun (t, v, r) -> ((parseCategory t), System.Int32.Parse(v.Trim()), System.Decimal.Parse(r.Trim())))\n    |> Seq.where (fun (t, v, r) -> t.IsSome)\n    |> Seq.map (fun (t, v, r) -> { Id = id; Category = t.Value; Votes = v; Rating = r })\n  rows\n  \ntype EpisodeRating = {\n  ``Males`` : decimal option;\n  ``Females`` : decimal option;\n  ``Aged under 18`` : decimal option;\n  ``Males under 18`` : decimal option;\n  ``Aged 18-29`` : decimal option;\n  ``Males Aged 18-29`` : decimal option;\n  ``Females Aged 18-29`` : decimal option;\n  ``Aged 30-44`` : decimal option;\n  ``Males Aged 30-44`` : decimal option;\n  ``Females Aged 30-44`` : decimal option;\n  ``Aged 45`` : decimal option;\n  ``Males Aged 45`` : decimal option;\n  ``Females Aged 45`` : decimal option;\n  ``Top 1000 voters`` : decimal option;\n  ``US users`` : decimal option;\n  ``Non-US users`` : decimal option;\n}\n\nlet tryFind (dict : System.Collections.Generic.IDictionary<'a,'b>) (key : 'a) =\n  let containsKey = dict.ContainsKey(key)\n  match containsKey with\n  | true -> Some dict.[key]\n  | false -> None\n\nlet pivotRatings (ratings : EpisodeRatings seq) =\n   let dictionary = \n     ratings\n     |> Seq.map (fun r -> (r.Category, r.Rating))\n     |> dict\n   let rating = {\n     ``Males`` = (tryFind dictionary RatingCategory.``Males``);\n     ``Females`` = (tryFind dictionary RatingCategory.``Females``);\n     ``Aged under 18`` = (tryFind dictionary RatingCategory.``Aged under 18``);\n     ``Males under 18`` = (tryFind dictionary RatingCategory.``Males under 18``);\n     ``Aged 18-29`` = (tryFind dictionary RatingCategory.``Aged 18-29``);\n     ``Males Aged 18-29`` = (tryFind dictionary RatingCategory.``Males Aged 18-29``);\n     ``Females Aged 18-29`` = (tryFind dictionary RatingCategory.``Females Aged 18-29``);\n     ``Aged 30-44`` = (tryFind dictionary RatingCategory.``Aged 30-44``);\n     ``Males Aged 30-44`` = (tryFind dictionary RatingCategory.``Males Aged 30-44``);\n     ``Females Aged 30-44`` = (tryFind dictionary RatingCategory.``Females Aged 30-44``);\n     ``Aged 45`` = (tryFind dictionary RatingCategory.``Aged 45``);\n     ``Males Aged 45`` = (tryFind dictionary RatingCategory.``Males Aged 45``);\n     ``Females Aged 45`` = (tryFind dictionary RatingCategory.``Females Aged 45``);\n     ``Top 1000 voters`` = (tryFind dictionary RatingCategory.``Top 1000 voters``);\n     ``US users`` = (tryFind dictionary RatingCategory.``US users``);\n     ``Non-US users`` = (tryFind dictionary RatingCategory.``Non-US users``)\n   }\n   rating\n\nlet loadRatings id =\n  let ratings = parseRatings id\n  let rating = pivotRatings ratings\n  rating", "outputs": [], "metadata": {"collapsed": true}}, {"source": "Which lets me retrieve ratings for each demographic per episode. For example, \"The End\" (Series 1, Episode 1) gives:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 7, "cell_type": "code", "source": "loadRatings \"tt0684181\"", "outputs": [{"execution_count": 7, "output_type": "execute_result", "data": {"text/plain": "{Males = Some 8.0M;\n Females = Some 8.3M;\n Aged under 18 = Some 8.0M;\n Males under 18 = Some 8.0M;\n Aged 18-29 = Some 8.1M;\n Males Aged 18-29 = Some 8.2M;\n Females Aged 18-29 = Some 7.2M;\n Aged 30-44 = Some 8.1M;\n Males Aged 30-44 = Some 8.0M;\n Females Aged 30-44 = Some 8.8M;\n Aged 45 = Some 7.8M;\n Males Aged 45 = Some 7.8M;\n Females Aged 45 = Some 7.4M;\n Top 1000 voters = Some 7.5M;\n US users = Some 7.9M;\n Non-US users = Some 8.1M;}"}, "metadata": {}}], "metadata": {"collapsed": false}}, {"source": "Finally I'll combine these two data sources into a tuple so they can be used together:", "cell_type": "markdown", "metadata": {}}, {"execution_count": 8, "cell_type": "code", "source": "let loadData id =\n  let episode = id |> loadTmdbJson |> parseTmdbJson\n  let ratings = id |> loadRatings\n  (episode, ratings)", "outputs": [], "metadata": {"collapsed": true}}, {"source": "With these two sources in hand I can finally start digging into the data.", "cell_type": "markdown", "metadata": {}}, {"source": "## Exploration\nTo evaluate whether it's Red Dwarf or me who has changed, I will look at the \"Top 1000 voters\" rating for each episode to see if there is a trend.", "cell_type": "markdown", "metadata": {}}, {"execution_count": 9, "cell_type": "code", "source": "let ratingsByDate = \n  episodeInformation\n  |> Seq.map (fun ei -> loadData ei.Id)\n  |> Seq.map (fun (episode, ratings) -> (episode.AirDate, ratings.``Top 1000 voters``))\n  |> Seq.where (fun (date, rating) -> rating.IsSome)\n  |> Seq.map (fun (date, rating) -> (date, rating.Value))\n  |> Seq.sortBy (fun (date, rating) -> date)\n  |> Seq.toList", "outputs": [], "metadata": {"collapsed": false}}, {"execution_count": 10, "cell_type": "code", "source": "let options = Options(pointSize=3, colors=[|\"#3B8FCC\"|], trendlines=[|Trendline(opacity=0.5,lineWidth=5,color=\"#C0D9EA\")|], hAxis=Axis(title=\"Date\"), vAxis=Axis(title=\"Rating\"))\nChart.Scatter(ratingsByDate) |> Chart.WithOptions (options)", "outputs": [{"execution_count": 10, "output_type": "execute_result", "data": {"text/html": "<script type=\"text/javascript\">\r\n    google.load('visualization', '1.0', { packages: ['corechart'], callback: drawChart })\r\n            function drawChart() {\r\n                var data = new google.visualization.DataTable({\"cols\": [{\"type\": \"datetime\" ,\"id\": \"Column 1\" ,\"label\": \"Column 1\" }, {\"type\": \"number\" ,\"id\": \"Column 2\" ,\"label\": \"Column 2\" }], \"rows\" : [{\"c\" : [{\"v\": \"Date(1988, 1, 15, 0, 0, 0)\"}, {\"v\": 7.5}]}, {\"c\" : [{\"v\": \"Date(1988, 1, 22, 0, 0, 0)\"}, {\"v\": 7.5}]}, {\"c\" : [{\"v\": \"Date(1988, 1, 29, 0, 0, 0)\"}, {\"v\": 7.3}]}, {\"c\" : [{\"v\": \"Date(1988, 2, 7, 0, 0, 0)\"}, {\"v\": 7.2}]}, {\"c\" : [{\"v\": \"Date(1988, 2, 14, 0, 0, 0)\"}, {\"v\": 7.3}]}, {\"c\" : [{\"v\": \"Date(1988, 2, 21, 0, 0, 0)\"}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(1988, 8, 6, 0, 0, 0)\"}, {\"v\": 7.8}]}, {\"c\" : [{\"v\": \"Date(1988, 8, 13, 0, 0, 0)\"}, {\"v\": 7.9}]}, {\"c\" : [{\"v\": \"Date(1988, 8, 20, 0, 0, 0)\"}, {\"v\": 8.0}]}, {\"c\" : [{\"v\": \"Date(1988, 8, 27, 0, 0, 0)\"}, {\"v\": 7.8}]}, {\"c\" : [{\"v\": \"Date(1988, 9, 4, 0, 0, 0)\"}, {\"v\": 8.2}]}, {\"c\" : [{\"v\": \"Date(1988, 9, 11, 0, 0, 0)\"}, {\"v\": 7.6}]}, {\"c\" : [{\"v\": \"Date(1989, 10, 14, 0, 0, 0)\"}, {\"v\": 8.2}]}, {\"c\" : [{\"v\": \"Date(1989, 10, 21, 0, 0, 0)\"}, {\"v\": 8.0}]}, {\"c\" : [{\"v\": \"Date(1989, 10, 28, 0, 0, 0)\"}, {\"v\": 8.5}]}, {\"c\" : [{\"v\": \"Date(1989, 11, 5, 0, 0, 0)\"}, {\"v\": 7.5}]}, {\"c\" : [{\"v\": \"Date(1989, 11, 12, 0, 0, 0)\"}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(1989, 11, 19, 0, 0, 0)\"}, {\"v\": 7.9}]}, {\"c\" : [{\"v\": \"Date(1991, 1, 14, 0, 0, 0)\"}, {\"v\": 7.3}]}, {\"c\" : [{\"v\": \"Date(1991, 1, 21, 0, 0, 0)\"}, {\"v\": 7.6}]}, {\"c\" : [{\"v\": \"Date(1991, 1, 28, 0, 0, 0)\"}, {\"v\": 8.1}]}, {\"c\" : [{\"v\": \"Date(1991, 2, 7, 0, 0, 0)\"}, {\"v\": 8.2}]}, {\"c\" : [{\"v\": \"Date(1991, 2, 14, 0, 0, 0)\"}, {\"v\": 8.2}]}, {\"c\" : [{\"v\": \"Date(1991, 2, 21, 0, 0, 0)\"}, {\"v\": 7.8}]}, {\"c\" : [{\"v\": \"Date(1992, 1, 20, 0, 0, 0)\"}, {\"v\": 7.8}]}, {\"c\" : [{\"v\": \"Date(1992, 1, 27, 0, 0, 0)\"}, {\"v\": 7.6}]}, {\"c\" : [{\"v\": \"Date(1992, 2, 5, 0, 0, 0)\"}, {\"v\": 7.5}]}, {\"c\" : [{\"v\": \"Date(1992, 2, 12, 0, 0, 0)\"}, {\"v\": 8.5}]}, {\"c\" : [{\"v\": \"Date(1992, 2, 19, 0, 0, 0)\"}, {\"v\": 7.6}]}, {\"c\" : [{\"v\": \"Date(1992, 2, 26, 0, 0, 0)\"}, {\"v\": 8.4}]}, {\"c\" : [{\"v\": \"Date(1993, 9, 7, 0, 0, 0)\"}, {\"v\": 7.5}]}, {\"c\" : [{\"v\": \"Date(1993, 9, 14, 0, 0, 0)\"}, {\"v\": 8.4}]}, {\"c\" : [{\"v\": \"Date(1993, 9, 21, 0, 0, 0)\"}, {\"v\": 7.6}]}, {\"c\" : [{\"v\": \"Date(1993, 9, 28, 0, 0, 0)\"}, {\"v\": 7.3}]}, {\"c\" : [{\"v\": \"Date(1993, 10, 4, 0, 0, 0)\"}, {\"v\": 7.8}]}, {\"c\" : [{\"v\": \"Date(1993, 10, 11, 0, 0, 0)\"}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(1997, 0, 17, 0, 0, 0)\"}, {\"v\": 7.6}]}, {\"c\" : [{\"v\": \"Date(1997, 0, 24, 0, 0, 0)\"}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(1997, 0, 31, 0, 0, 0)\"}, {\"v\": 7.1}]}, {\"c\" : [{\"v\": \"Date(1997, 1, 7, 0, 0, 0)\"}, {\"v\": 6.9}]}, {\"c\" : [{\"v\": \"Date(1997, 1, 14, 0, 0, 0)\"}, {\"v\": 7.0}]}, {\"c\" : [{\"v\": \"Date(1997, 1, 21, 0, 0, 0)\"}, {\"v\": 6.8}]}, {\"c\" : [{\"v\": \"Date(1997, 1, 28, 0, 0, 0)\"}, {\"v\": 7.0}]}, {\"c\" : [{\"v\": \"Date(1997, 2, 7, 0, 0, 0)\"}, {\"v\": 7.0}]}, {\"c\" : [{\"v\": \"Date(1999, 1, 18, 0, 0, 0)\"}, {\"v\": 7.2}]}, {\"c\" : [{\"v\": \"Date(1999, 1, 25, 0, 0, 0)\"}, {\"v\": 7.1}]}, {\"c\" : [{\"v\": \"Date(1999, 2, 4, 0, 0, 0)\"}, {\"v\": 7.0}]}, {\"c\" : [{\"v\": \"Date(1999, 2, 11, 0, 0, 0)\"}, {\"v\": 7.5}]}, {\"c\" : [{\"v\": \"Date(1999, 2, 18, 0, 0, 0)\"}, {\"v\": 6.9}]}, {\"c\" : [{\"v\": \"Date(1999, 2, 25, 0, 0, 0)\"}, {\"v\": 6.6}]}, {\"c\" : [{\"v\": \"Date(1999, 3, 1, 0, 0, 0)\"}, {\"v\": 6.6}]}, {\"c\" : [{\"v\": \"Date(1999, 3, 5, 0, 0, 0)\"}, {\"v\": 6.7}]}, {\"c\" : [{\"v\": \"Date(2009, 3, 10, 0, 0, 0)\"}, {\"v\": 5.9}]}, {\"c\" : [{\"v\": \"Date(2009, 3, 11, 0, 0, 0)\"}, {\"v\": 6.2}]}, {\"c\" : [{\"v\": \"Date(2009, 3, 12, 0, 0, 0)\"}, {\"v\": 6.5}]}, {\"c\" : [{\"v\": \"Date(2012, 8, 23, 0, 0, 0)\"}, {\"v\": 7.8}]}, {\"c\" : [{\"v\": \"Date(2012, 9, 11, 0, 0, 0)\"}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(2012, 9, 18, 0, 0, 0)\"}, {\"v\": 7.4}]}, {\"c\" : [{\"v\": \"Date(2012, 9, 25, 0, 0, 0)\"}, {\"v\": 7.4}]}, {\"c\" : [{\"v\": \"Date(2012, 10, 1, 0, 0, 0)\"}, {\"v\": 7.3}]}, {\"c\" : [{\"v\": \"Date(2012, 10, 8, 0, 0, 0)\"}, {\"v\": 7.8}]}, {\"c\" : [{\"v\": \"Date(2016, 8, 23, 0, 0, 0)\"}, {\"v\": 7.3}]}, {\"c\" : [{\"v\": \"Date(2016, 8, 30, 0, 0, 0)\"}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(2016, 9, 7, 0, 0, 0)\"}, {\"v\": 7.6}]}, {\"c\" : [{\"v\": \"Date(2016, 9, 14, 0, 0, 0)\"}, {\"v\": 7.6}]}, {\"c\" : [{\"v\": \"Date(2016, 9, 21, 0, 0, 0)\"}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(2016, 9, 28, 0, 0, 0)\"}, {\"v\": 7.9}]}]});\r\n\r\n                var options = {\"colors\":[\"#3B8FCC\"],\"hAxis\":{\"title\":\"Date\"},\"legend\":{\"position\":\"none\"},\"pointSize\":3,\"vAxis\":{\"title\":\"Rating\"},\"trendlines\":[{\"color\":\"#C0D9EA\",\"lineWidth\":5,\"opacity\":0.5}]} \r\n\r\n                var chart = new google.visualization.ScatterChart(document.getElementById('8f0792eb-fb69-44d8-8bd7-54ba06cdd7c8'));\r\n                chart.draw(data, options);\r\n            }\r\n<\/script>\r\n<div id=\"8f0792eb-fb69-44d8-8bd7-54ba06cdd7c8\" style=\"width: 900px; height: 500px;\"><\/div>"}, "metadata": {}}], "metadata": {"collapsed": false}}, {"source": "As we can see, there is a definite downward trend in rating which suggests that the show is getting less funny, but it's not as stark as I was expecting. Indeed, a rating of 7.184 (based on the trend value at the time of the last show) would still place Red Dwarf in IMDB's Top 1000 TV Shows which, to me, seems incongruous given how poor the most recent episodes have been.\n\nI therefore wonder whether reviews are being buoyed up by younger viewers rating the show highly without an appreciation of how inferior they are (in my opinion) to the earlier series.\n\nI'll therefore add a few more datapoints to the chart here based on each age category's rating:", "cell_type": "markdown", "metadata": {"collapsed": true}}, {"execution_count": 11, "cell_type": "code", "source": "let ratingsByDateAndAgeCategory = \n  episodeInformation\n  |> Seq.map (fun ei -> loadData ei.Id)\n  |> Seq.collect (fun (episode, ratings) -> [| (episode.AirDate, RatingCategory.``Aged under 18``, ratings.``Aged under 18``); (episode.AirDate, RatingCategory.``Aged 18-29``, ratings.``Aged 18-29``); (episode.AirDate, RatingCategory.``Aged 30-44``, ratings.``Aged 30-44``); (episode.AirDate, RatingCategory.``Aged 45``, ratings.``Aged 45``)|])\n  |> Seq.where (fun (date, category, rating) -> rating.IsSome)\n  |> Seq.map (fun (date, category, rating) -> (date, category, rating.Value))\n  |> Seq.groupBy (fun (date, category, rating) -> category)\n  |> Seq.map (fun (key, values) -> values |> Seq.map (fun (date, category, rating) -> (date, rating)) |> Seq.sortBy (fun (date, rating) -> date))\n  |> Seq.toList\n\nlet options = \n  Options(\n    pointSize=3, \n    colors=[|\"#6AA590\"; \"#7DE6C1\"; \"#57E6B3\"; \"#60A6D0\"; \"#3B8FCC\"|], \n    trendlines=[|\n      Trendline(opacity=0.5,lineWidth=5,color=\"#6AA590\");\n      Trendline(opacity=0.5,lineWidth=5,color=\"#7DE6C1\");\n      Trendline(opacity=0.5,lineWidth=5,color=\"#57E6B3\");\n      Trendline(opacity=0.5,lineWidth=5,color=\"#60A6D0\");\n      Trendline(opacity=0.5,lineWidth=5,color=\"#3B8FCC\")|],      \n    hAxis=Axis(title=\"Date\"),\n    vAxis=Axis(title=\"Rating\"))\n\nChart.Scatter(ratingsByDateAndAgeCategory, [|\"Aged under 18\"; \"Aged 18-29\";\"Aged 30-44\";\"Aged 45+\";\"????\"|])\n|> Chart.WithOptions(options) \n|> Chart.WithLegend(true)", "outputs": [{"execution_count": 11, "output_type": "execute_result", "data": {"text/html": "<script type=\"text/javascript\">\r\n    google.load('visualization', '1.0', { packages: ['corechart'], callback: drawChart })\r\n            function drawChart() {\r\n                var data = new google.visualization.DataTable({\"cols\": [{\"type\": \"datetime\" ,\"id\": \"Column 1\" ,\"label\": \"Column 1\" }, {\"type\": \"number\" ,\"id\": \"Aged under 18\" ,\"label\": \"Aged under 18\" }, {\"type\": \"number\" ,\"id\": \"Aged 18-29\" ,\"label\": \"Aged 18-29\" }, {\"type\": \"number\" ,\"id\": \"Aged 30-44\" ,\"label\": \"Aged 30-44\" }, {\"type\": \"number\" ,\"id\": \"Aged 45+\" ,\"label\": \"Aged 45+\" }], \"rows\" : [{\"c\" : [{\"v\": \"Date(1988, 1, 15, 0, 0, 0)\"}, {\"v\": 8.0}, {\"v\": 8.1}, {\"v\": 8.1}, {\"v\": 7.8}]}, {\"c\" : [{\"v\": \"Date(1988, 1, 22, 0, 0, 0)\"}, {\"v\": 8.3}, {\"v\": 8.1}, {\"v\": 8.1}, {\"v\": 7.9}]}, {\"c\" : [{\"v\": \"Date(1988, 1, 29, 0, 0, 0)\"}, {\"v\": 7.5}, {\"v\": 7.6}, {\"v\": 7.8}, {\"v\": 7.8}]}, {\"c\" : [{\"v\": \"Date(1988, 2, 7, 0, 0, 0)\"}, {\"v\": 7.1}, {\"v\": 7.8}, {\"v\": 7.6}, {\"v\": 7.9}]}, {\"c\" : [{\"v\": \"Date(1988, 2, 14, 0, 0, 0)\"}, {\"v\": 7.1}, {\"v\": 7.8}, {\"v\": 7.8}, {\"v\": 7.8}]}, {\"c\" : [{\"v\": \"Date(1988, 2, 21, 0, 0, 0)\"}, {\"v\": 7.6}, {\"v\": 8.3}, {\"v\": 8.2}, {\"v\": 8.3}]}, {\"c\" : [{\"v\": \"Date(1988, 8, 6, 0, 0, 0)\"}, {\"v\": 7.4}, {\"v\": 8.3}, {\"v\": 8.0}, {\"v\": 8.3}]}, {\"c\" : [{\"v\": \"Date(1988, 8, 13, 0, 0, 0)\"}, {\"v\": 7.9}, {\"v\": 8.6}, {\"v\": 8.5}, {\"v\": 8.5}]}, {\"c\" : [{\"v\": \"Date(1988, 8, 20, 0, 0, 0)\"}, {\"v\": 7.2}, {\"v\": 8.4}, {\"v\": 8.6}, {\"v\": 8.4}]}, {\"c\" : [{\"v\": \"Date(1988, 8, 27, 0, 0, 0)\"}, {\"v\": 7.7}, {\"v\": 8.4}, {\"v\": 8.4}, {\"v\": 8.2}]}, {\"c\" : [{\"v\": \"Date(1988, 9, 4, 0, 0, 0)\"}, {\"v\": 8.0}, {\"v\": 8.8}, {\"v\": 8.8}, {\"v\": 8.8}]}, {\"c\" : [{\"v\": \"Date(1988, 9, 11, 0, 0, 0)\"}, {\"v\": 8.2}, {\"v\": 8.1}, {\"v\": 8.1}, {\"v\": 8.3}]}, {\"c\" : [{\"v\": \"Date(1989, 10, 14, 0, 0, 0)\"}, {\"v\": 8.5}, {\"v\": 8.7}, {\"v\": 8.6}, {\"v\": 8.6}]}, {\"c\" : [{\"v\": \"Date(1989, 10, 21, 0, 0, 0)\"}, {\"v\": 8.2}, {\"v\": 8.7}, {\"v\": 8.6}, {\"v\": 8.6}]}, {\"c\" : [{\"v\": \"Date(1989, 10, 28, 0, 0, 0)\"}, {\"v\": 8.7}, {\"v\": 9.0}, {\"v\": 8.8}, {\"v\": 9.0}]}, {\"c\" : [{\"v\": \"Date(1989, 11, 5, 0, 0, 0)\"}, {\"v\": 7.2}, {\"v\": 8.0}, {\"v\": 8.0}, {\"v\": 8.2}]}, {\"c\" : [{\"v\": \"Date(1989, 11, 12, 0, 0, 0)\"}, {\"v\": 8.0}, {\"v\": 8.3}, {\"v\": 8.2}, {\"v\": 8.1}]}, {\"c\" : [{\"v\": \"Date(1989, 11, 19, 0, 0, 0)\"}, {\"v\": 7.2}, {\"v\": 8.3}, {\"v\": 8.2}, {\"v\": 8.4}]}, {\"c\" : [{\"v\": \"Date(1991, 1, 14, 0, 0, 0)\"}, {\"v\": 7.0}, {\"v\": 7.8}, {\"v\": 7.7}, {\"v\": 8.2}]}, {\"c\" : [{\"v\": \"Date(1991, 1, 21, 0, 0, 0)\"}, {\"v\": 6.8}, {\"v\": 8.3}, {\"v\": 8.2}, {\"v\": 8.4}]}, {\"c\" : [{\"v\": \"Date(1991, 1, 28, 0, 0, 0)\"}, {\"v\": 7.5}, {\"v\": 8.6}, {\"v\": 8.6}, {\"v\": 8.5}]}, {\"c\" : [{\"v\": \"Date(1991, 2, 7, 0, 0, 0)\"}, {\"v\": 8.5}, {\"v\": 8.8}, {\"v\": 8.5}, {\"v\": 8.7}]}, {\"c\" : [{\"v\": \"Date(1991, 2, 14, 0, 0, 0)\"}, {\"v\": 8.7}, {\"v\": 8.7}, {\"v\": 8.6}, {\"v\": 8.9}]}, {\"c\" : [{\"v\": \"Date(1991, 2, 21, 0, 0, 0)\"}, {\"v\": 8.2}, {\"v\": 8.5}, {\"v\": 8.1}, {\"v\": 8.2}]}, {\"c\" : [{\"v\": \"Date(1992, 1, 20, 0, 0, 0)\"}, {\"v\": 7.8}, {\"v\": 8.3}, {\"v\": 8.3}, {\"v\": 8.4}]}, {\"c\" : [{\"v\": \"Date(1992, 1, 27, 0, 0, 0)\"}, {\"v\": 7.5}, {\"v\": 8.2}, {\"v\": 8.3}, {\"v\": 8.4}]}, {\"c\" : [{\"v\": \"Date(1992, 2, 5, 0, 0, 0)\"}, {\"v\": 7.0}, {\"v\": 8.4}, {\"v\": 8.1}, {\"v\": 8.1}]}, {\"c\" : [{\"v\": \"Date(1992, 2, 12, 0, 0, 0)\"}, {\"v\": 8.6}, {\"v\": 9.2}, {\"v\": 9.0}, {\"v\": 9.0}]}, {\"c\" : [{\"v\": \"Date(1992, 2, 19, 0, 0, 0)\"}, {\"v\": 7.0}, {\"v\": 8.2}, {\"v\": 8.2}, {\"v\": 8.1}]}, {\"c\" : [{\"v\": \"Date(1992, 2, 26, 0, 0, 0)\"}, {\"v\": 9.4}, {\"v\": 8.7}, {\"v\": 9.3}, {\"v\": 9.4}]}, {\"c\" : [{\"v\": \"Date(1993, 9, 7, 0, 0, 0)\"}, {\"v\": 7.2}, {\"v\": 8.3}, {\"v\": 8.2}, {\"v\": 7.9}]}, {\"c\" : [{\"v\": \"Date(1993, 9, 14, 0, 0, 0)\"}, {\"v\": 8.6}, {\"v\": 8.8}, {\"v\": 9.0}, {\"v\": 8.6}]}, {\"c\" : [{\"v\": \"Date(1993, 9, 21, 0, 0, 0)\"}, {\"v\": 7.8}, {\"v\": 8.5}, {\"v\": 8.7}, {\"v\": 8.4}]}, {\"c\" : [{\"v\": \"Date(1993, 9, 28, 0, 0, 0)\"}, {\"v\": 7.0}, {\"v\": 8.0}, {\"v\": 7.8}, {\"v\": 7.9}]}, {\"c\" : [{\"v\": \"Date(1993, 10, 4, 0, 0, 0)\"}, {\"v\": 8.0}, {\"v\": 8.5}, {\"v\": 8.5}, {\"v\": 8.0}]}, {\"c\" : [{\"v\": \"Date(1993, 10, 11, 0, 0, 0)\"}, {\"v\": 8.0}, {\"v\": 8.5}, {\"v\": 8.5}, {\"v\": 8.2}]}, {\"c\" : [{\"v\": \"Date(1997, 0, 17, 0, 0, 0)\"}, {\"v\": 8.0}, {\"v\": 8.7}, {\"v\": 8.0}, {\"v\": 8.1}]}, {\"c\" : [{\"v\": \"Date(1997, 0, 24, 0, 0, 0)\"}, {\"v\": 8.2}, {\"v\": 8.5}, {\"v\": 8.2}, {\"v\": 8.3}]}, {\"c\" : [{\"v\": \"Date(1997, 0, 31, 0, 0, 0)\"}, {\"v\": 6.5}, {\"v\": 7.9}, {\"v\": 7.4}, {\"v\": 7.5}]}, {\"c\" : [{\"v\": \"Date(1997, 1, 7, 0, 0, 0)\"}, {\"v\": 7.0}, {\"v\": 7.4}, {\"v\": 7.1}, {\"v\": 7.1}]}, {\"c\" : [{\"v\": \"Date(1997, 1, 14, 0, 0, 0)\"}, {\"v\": 8.0}, {\"v\": 8.0}, {\"v\": 7.7}, {\"v\": 7.4}]}, {\"c\" : [{\"v\": \"Date(1997, 1, 21, 0, 0, 0)\"}, {\"v\": 6.5}, {\"v\": 7.6}, {\"v\": 6.8}, {\"v\": 7.3}]}, {\"c\" : [{\"v\": \"Date(1997, 1, 28, 0, 0, 0)\"}, {\"v\": 5.8}, {\"v\": 8.0}, {\"v\": 7.5}, {\"v\": 7.5}]}, {\"c\" : [{\"v\": \"Date(1997, 2, 7, 0, 0, 0)\"}, {\"v\": 6.0}, {\"v\": 7.3}, {\"v\": 7.3}, {\"v\": 7.5}]}, {\"c\" : [{\"v\": \"Date(1999, 1, 18, 0, 0, 0)\"}, {\"v\": 6.0}, {\"v\": 7.5}, {\"v\": 7.5}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(1999, 1, 25, 0, 0, 0)\"}, {\"v\": 6.5}, {\"v\": 7.3}, {\"v\": 7.5}, {\"v\": 7.9}]}, {\"c\" : [{\"v\": \"Date(1999, 2, 4, 0, 0, 0)\"}, {\"v\": 6.2}, {\"v\": 7.3}, {\"v\": 7.2}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(1999, 2, 11, 0, 0, 0)\"}, {\"v\": 7.2}, {\"v\": 8.0}, {\"v\": 8.0}, {\"v\": 8.3}]}, {\"c\" : [{\"v\": \"Date(1999, 2, 18, 0, 0, 0)\"}, {\"v\": 6.2}, {\"v\": 7.5}, {\"v\": 7.4}, {\"v\": 8.0}]}, {\"c\" : [{\"v\": \"Date(1999, 2, 25, 0, 0, 0)\"}, {\"v\": 4.8}, {\"v\": 6.8}, {\"v\": 6.8}, {\"v\": 7.5}]}, {\"c\" : [{\"v\": \"Date(1999, 3, 1, 0, 0, 0)\"}, {\"v\": 5.2}, {\"v\": 6.6}, {\"v\": 6.7}, {\"v\": 7.3}]}, {\"c\" : [{\"v\": \"Date(1999, 3, 5, 0, 0, 0)\"}, {\"v\": 7.3}, {\"v\": 7.4}, {\"v\": 7.3}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(2009, 3, 10, 0, 0, 0)\"}, {\"v\": 4.3}, {\"v\": 7.0}, {\"v\": 6.4}, {\"v\": 6.3}]}, {\"c\" : [{\"v\": \"Date(2009, 3, 11, 0, 0, 0)\"}, {\"v\": 5.0}, {\"v\": 7.3}, {\"v\": 6.1}, {\"v\": 6.5}]}, {\"c\" : [{\"v\": \"Date(2009, 3, 12, 0, 0, 0)\"}, {\"v\": 5.3}, {\"v\": 7.6}, {\"v\": 6.6}, {\"v\": 6.7}]}, {\"c\" : [{\"v\": \"Date(2012, 8, 23, 0, 0, 0)\"}, {\"v\": 6.3}, {\"v\": 8.8}, {\"v\": 8.4}, {\"v\": 8.4}]}, {\"c\" : [{\"v\": \"Date(2012, 9, 11, 0, 0, 0)\"}, {\"v\": 5.0}, {\"v\": 8.6}, {\"v\": 8.2}, {\"v\": 8.1}]}, {\"c\" : [{\"v\": \"Date(2012, 9, 18, 0, 0, 0)\"}, {\"v\": 5.7}, {\"v\": 8.8}, {\"v\": 7.9}, {\"v\": 8.5}]}, {\"c\" : [{\"v\": \"Date(2012, 9, 25, 0, 0, 0)\"}, {\"v\": 5.0}, {\"v\": 8.0}, {\"v\": 7.6}, {\"v\": 8.0}]}, {\"c\" : [{\"v\": \"Date(2012, 10, 1, 0, 0, 0)\"}, {\"v\": 4.7}, {\"v\": 8.1}, {\"v\": 7.7}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(2012, 10, 8, 0, 0, 0)\"}, {\"v\": 7.2}, {\"v\": 8.7}, {\"v\": 8.1}, {\"v\": 8.2}]}, {\"c\" : [{\"v\": \"Date(2016, 8, 23, 0, 0, 0)\"}, {\"v\": 6.5}, {\"v\": 7.6}, {\"v\": 7.2}, {\"v\": 7.7}]}, {\"c\" : [{\"v\": \"Date(2016, 8, 30, 0, 0, 0)\"}, {\"v\": 7.0}, {\"v\": 7.7}, {\"v\": 7.9}, {\"v\": 8.1}]}, {\"c\" : [{\"v\": \"Date(2016, 9, 7, 0, 0, 0)\"}, {\"v\": 7.0}, {\"v\": 8.1}, {\"v\": 7.9}, {\"v\": 7.9}]}, {\"c\" : [{\"v\": \"Date(2016, 9, 14, 0, 0, 0)\"}, {\"v\": 7.0}, {\"v\": 8.0}, {\"v\": 7.9}, {\"v\": 8.0}]}, {\"c\" : [{\"v\": \"Date(2016, 9, 21, 0, 0, 0)\"}, {\"v\": 7.0}, {\"v\": 7.8}, {\"v\": 7.9}, {\"v\": 8.0}]}, {\"c\" : [{\"v\": \"Date(2016, 9, 28, 0, 0, 0)\"}, {\"v\": 7.0}, {\"v\": 8.0}, {\"v\": 8.0}, {\"v\": 8.1}]}]});\r\n\r\n                var options = {\"colors\":[\"#6AA590\",\"#7DE6C1\",\"#57E6B3\",\"#60A6D0\",\"#3B8FCC\"],\"hAxis\":{\"title\":\"Date\"},\"legend\":{\"position\":\"right\"},\"pointSize\":3,\"vAxis\":{\"title\":\"Rating\"},\"trendlines\":[{\"color\":\"#6AA590\",\"lineWidth\":5,\"opacity\":0.5},{\"color\":\"#7DE6C1\",\"lineWidth\":5,\"opacity\":0.5},{\"color\":\"#57E6B3\",\"lineWidth\":5,\"opacity\":0.5},{\"color\":\"#60A6D0\",\"lineWidth\":5,\"opacity\":0.5},{\"color\":\"#3B8FCC\",\"lineWidth\":5,\"opacity\":0.5}]} \r\n\r\n                var chart = new google.visualization.ScatterChart(document.getElementById('1754a0eb-be89-451e-88f3-1a1e20f139b6'));\r\n                chart.draw(data, options);\r\n            }\r\n<\/script>\r\n<div id=\"1754a0eb-be89-451e-88f3-1a1e20f139b6\" style=\"width: 900px; height: 500px;\"><\/div>"}, "metadata": {}}], "metadata": {"collapsed": false}}, {"source": "And here's the kicker. Turns out that, while there is a general downward trend across all age groups, it's actually the oldest demographic that is rating the new series the highest. The younger generation are observing the biggest deterioration in rating (albeit from a lower initial rating) which is completely opposite to my expectations.\n\n## Conclusion\nThis investigation has been quite interesting. While most demographics (including my own) observe a slight decline in rating, the decline has been nowhere near what I was expecting and the latter series have been rating much higher than I would place them.\n\nI guess the only conclusion I can make from this is that either I'm extremely young at heart or my missus is correct: **I'm a miserably old git.**", "cell_type": "markdown", "metadata": {}}], "nbformat": 4, "metadata": {"kernelspec": {"display_name": "F#", "name": "ifsharp", "language": "fsharp"}, "language_info": {"mimetype": "text/x-fsharp", "nbconvert_exporter": "", "version": "4.3.1.0", "name": "fsharp", "file_extension": ".fs", "pygments_lexer": "", "codemirror_mode": ""}, "language": "fsharp"}}