From 4323f5153325de2626ca5cb8652a76796a500f20 Mon Sep 17 00:00:00 2001 From: dreimer7 <112495919+dreimer7@users.noreply.github.com> Date: Fri, 23 Jan 2026 14:37:41 -0500 Subject: [PATCH 1/5] Add files via upload --- presentations/BasePres.Rmd | 656 +++++++++++++++++++++++++++++++++++++ 1 file changed, 656 insertions(+) create mode 100644 presentations/BasePres.Rmd diff --git a/presentations/BasePres.Rmd b/presentations/BasePres.Rmd new file mode 100644 index 0000000..9292b24 --- /dev/null +++ b/presentations/BasePres.Rmd @@ -0,0 +1,656 @@ +--- +title: "Test Slide" +subtitle: "⚔
with xaringan" +author: "Delaney Reimer" +institute: "RStudio, PBC" +date: "2026/1/23 (updated: `r Sys.Date()`)" +output: + xaringan::moon_reader: + css: xaringan-themer.css + lib_dir: libs + nature: + highlightStyle: github + highlightLines: true + countIncrementalSlides: false +--- + +```{r xaringan-themer, include=FALSE, warning=FALSE} +library(xaringanthemer) +style_mono_accent( + base_color = "#1c5253", + header_font_google = google_font("Josefin Sans"), + text_font_google = google_font("Montserrat", "300", "300i"), + code_font_google = google_font("Fira Mono") +) +``` + +background-image: url(https://upload.wikimedia.org/wikipedia/commons/b/be/Sharingan_triple.svg) + +```{r setup, include=FALSE} +options(htmltools.dir.version = FALSE) +``` + +??? + +Image credit: [Wikimedia Commons](https://commons.wikimedia.org/wiki/File:Sharingan_triple.svg) + + +--- +class: center, middle + +# xaringan + +### /ʃaː.'riŋ.ɡan/ + +--- +class: inverse, center, middle + +# Get Started + +--- + +eval=False means it will not run the chunk + +echo=False means code will not be displayed on screen + +'--' is a pause + +--- + +# Hello World + +Install the **xaringan** package from [Github](https://github.com/yihui/xaringan): + +```{r eval=FALSE, tidy=FALSE} +remotes::install_github("yihui/xaringan") +``` + +-- + +You are recommended to use the [RStudio IDE](https://www.rstudio.com/products/rstudio/), but you do not have to. + +- Create a new R Markdown document from the menu `File -> New File -> R Markdown -> From Template -> Ninja Presentation`;1 + +-- + +- Click the `Knit` button to compile it; + +-- + +- or use the [RStudio Addin](https://rstudio.github.io/rstudioaddins/)2 "Infinite Moon Reader" to live preview the slides (every time you update and save the Rmd document, the slides will be automatically reloaded in RStudio Viewer. + +.footnote[ +[1] 中文用户请看[这份教程](https://slides.yihui.org/xaringan/zh-CN.html) + +[2] See [#2](https://github.com/yihui/xaringan/issues/2) if you do not see the template or addin in RStudio. +] + +--- +background-image: url(`r xaringan:::karl`) +background-position: 50% 50% +class: center, bottom, inverse + +# You only live once! + +--- + +# Hello Ninja + +As a presentation ninja, you certainly should not be satisfied by the "Hello World" example. You need to understand more about two things: + +1. The [remark.js](https://remarkjs.com) library; + +1. The **xaringan** package; + +Basically **xaringan** injected the chakra of R Markdown (minus Pandoc) into **remark.js**. The slides are rendered by remark.js in the web browser, and the Markdown source needed by remark.js is generated from R Markdown (**knitr**). + +--- + +# remark.js + +You can see an introduction of remark.js from [its homepage](https://remarkjs.com). You should read the [remark.js Wiki](https://github.com/gnab/remark/wiki) at least once to know how to + +- create a new slide (Markdown syntax* and slide properties); + +- format a slide (e.g. text alignment); + +- configure the slideshow; + +- and use the presentation (keyboard shortcuts). + +It is important to be familiar with remark.js before you can understand the options in **xaringan**. + +.footnote[[*] It is different with Pandoc's Markdown! It is limited but should be enough for presentation purposes. Come on... You do not need a slide for the Table of Contents! Well, the Markdown support in remark.js [may be improved](https://github.com/gnab/remark/issues/142) in the future.] + +--- +background-image: url(`r xaringan:::karl`) +background-size: cover +class: center, bottom, inverse + +# I was so happy to have discovered remark.js! + +--- +class: inverse, middle, center + +# Using xaringan + +--- + +# xaringan + +Provides an R Markdown output format `xaringan::moon_reader` as a wrapper for remark.js, and you can use it in the YAML metadata, e.g. + +```yaml +--- +title: "A Cool Presentation" +output: + xaringan::moon_reader: + yolo: true + nature: + autoplay: 30000 +--- +``` + +See the help page `?xaringan::moon_reader` for all possible options that you can use. + +--- + +# remark.js vs xaringan + +Some differences between using remark.js (left) and using **xaringan** (right): + +.pull-left[ +1. Start with a boilerplate HTML file; + +1. Plain Markdown; + +1. Write JavaScript to autoplay slides; + +1. Manually configure MathJax; + +1. Highlight code with `*`; + +1. Edit Markdown source and refresh browser to see updated slides; +] + +.pull-right[ +1. Start with an R Markdown document; + +1. R Markdown (can embed R/other code chunks); + +1. Provide an option `autoplay`; + +1. MathJax just works;* + +1. Highlight code with `{{}}`; + +1. The RStudio addin "Infinite Moon Reader" automatically refreshes slides on changes; +] + +.footnote[[*] Not really. See next page.] + +--- + +# Math Expressions + +You can write LaTeX math expressions inside a pair of dollar signs, e.g. $\alpha+\beta$ renders $\alpha+\beta$. You can use the display style with double dollar signs: + +``` +$$\bar{X}=\frac{1}{n}\sum_{i=1}^nX_i$$ +``` + +$$\bar{X}=\frac{1}{n}\sum_{i=1}^nX_i$$ + +Limitations: + +1. The source code of a LaTeX math expression must be in one line, unless it is inside a pair of double dollar signs, in which case the starting `$$` must appear in the very beginning of a line, followed immediately by a non-space character, and the ending `$$` must be at the end of a line, led by a non-space character; + +1. There should not be spaces after the opening `$` or before the closing `$`. + +1. Math does not work on the title slide (see [#61](https://github.com/yihui/xaringan/issues/61) for a workaround). + +--- + +# R Code + +```{r comment='#'} +# a boring regression +fit = lm(dist ~ 1 + speed, data = cars) +coef(summary(fit)) +dojutsu = c('地爆天星', '天照', '加具土命', '神威', '須佐能乎', '無限月読') +grep('天', dojutsu, value = TRUE) +``` + +--- + +# R Plots + +```{r cars, fig.height=4, dev='svg'} +par(mar = c(4, 4, 1, .1)) +plot(cars, pch = 19, col = 'darkgray', las = 1) +abline(fit, lwd = 2) +``` + +--- + +# Tables + +If you want to generate a table, make sure it is in the HTML format (instead of Markdown or other formats), e.g., + +```{r} +knitr::kable(head(iris), format = 'html') +``` + +--- + +# HTML Widgets + +I have not thoroughly tested HTML widgets against **xaringan**. Some may work well, and some may not. It is a little tricky. + +Similarly, the Shiny mode (`runtime: shiny`) does not work. I might get these issues fixed in the future, but these are not of high priority to me. I never turn my presentation into a Shiny app. When I need to demonstrate more complicated examples, I just launch them separately. It is convenient to share slides with other people when they are plain HTML/JS applications. + +See the next page for two HTML widgets. + +--- + +```{r out.width='100%', fig.height=6, eval=require('leaflet')} +library(leaflet) +leaflet() %>% addTiles() %>% setView(-93.65, 42.0285, zoom = 17) +``` + +--- + +```{r eval=require('DT'), tidy=FALSE} +DT::datatable( + head(iris, 10), + fillContainer = FALSE, options = list(pageLength = 8) +) +``` + +--- + +# Some Tips + +- Do not forget to try the `yolo` option of `xaringan::moon_reader`. + + ```yaml + output: + xaringan::moon_reader: + yolo: true + ``` + +--- + +# Some Tips + +- Slides can be automatically played if you set the `autoplay` option under `nature`, e.g. go to the next slide every 30 seconds in a lightning talk: + + ```yaml + output: + xaringan::moon_reader: + nature: + autoplay: 30000 + ``` + +- If you want to restart the play after it reaches the last slide, you may set the sub-option `loop` to TRUE, e.g., + + ```yaml + output: + xaringan::moon_reader: + nature: + autoplay: + interval: 30000 + loop: true + ``` + +--- + +# Some Tips + +- A countdown timer can be added to every page of the slides using the `countdown` option under `nature`, e.g. if you want to spend one minute on every page when you give the talk, you can set: + + ```yaml + output: + xaringan::moon_reader: + nature: + countdown: 60000 + ``` + + Then you will see a timer counting down from `01:00`, to `00:59`, `00:58`, ... When the time is out, the timer will continue but the time turns red. + +--- + +# Some Tips + +- The title slide is created automatically by **xaringan**, but it is just another remark.js slide added before your other slides. + + The title slide is set to `class: center, middle, inverse, title-slide` by default. You can change the classes applied to the title slide with the `titleSlideClass` option of `nature` (`title-slide` is always applied). + + ```yaml + output: + xaringan::moon_reader: + nature: + titleSlideClass: [top, left, inverse] + ``` + +-- + +- If you'd like to create your own title slide, disable **xaringan**'s title slide with the `seal = FALSE` option of `moon_reader`. + + ```yaml + output: + xaringan::moon_reader: + seal: false + ``` + +--- + +# Some Tips + +- There are several ways to build incremental slides. See [this presentation](https://slides.yihui.org/xaringan/incremental.html) for examples. + +- The option `highlightLines: true` of `nature` will highlight code lines that start with `*`, or are wrapped in `{{ }}`, or have trailing comments `#<<`; + + ```yaml + output: + xaringan::moon_reader: + nature: + highlightLines: true + ``` + + See examples on the next page. + +--- + +# Some Tips + + +.pull-left[ +An example using a leading `*`: + + ```r + if (TRUE) { + ** message("Very important!") + } + ``` +Output: +```r +if (TRUE) { +* message("Very important!") +} +``` + +This is invalid R code, so it is a plain fenced code block that is not executed. +] + +.pull-right[ +An example using `{{}}`: + +```` +`r ''````{r tidy=FALSE} +if (TRUE) { +*{{ message("Very important!") }} +} +``` +```` +Output: +```{r tidy=FALSE} +if (TRUE) { +{{ message("Very important!") }} +} +``` + +It is valid R code so you can run it. Note that `{{}}` can wrap an R expression of multiple lines. +] + +--- + +# Some Tips + +An example of using the trailing comment `#<<` to highlight lines: + +````markdown +`r ''````{r tidy=FALSE} +library(ggplot2) +ggplot(mtcars) + + aes(mpg, disp) + + geom_point() + #<< + geom_smooth() #<< +``` +```` + +Output: + +```{r tidy=FALSE, eval=FALSE} +library(ggplot2) +ggplot(mtcars) + + aes(mpg, disp) + + geom_point() + #<< + geom_smooth() #<< +``` + +--- + +# Some Tips + +When you enable line-highlighting, you can also use the chunk option `highlight.output` to highlight specific lines of the text output from a code chunk. For example, `highlight.output = TRUE` means highlighting all lines, and `highlight.output = c(1, 3)` means highlighting the first and third line. + +````md +`r ''````{r, highlight.output=c(1, 3)} +head(iris) +``` +```` + +```{r, highlight.output=c(1, 3), echo=FALSE} +head(iris) +``` + +Question: what does `highlight.output = c(TRUE, FALSE)` mean? (Hint: think about R's recycling of vectors) + +--- + +# Some Tips + +- To make slides work offline, you need to download a copy of remark.js in advance, because **xaringan** uses the online version by default (see the help page `?xaringan::moon_reader`). + +- You can use `xaringan::summon_remark()` to download the latest or a specified version of remark.js. By default, it is downloaded to `libs/remark-latest.min.js`. + +- Then change the `chakra` option in YAML to point to this file, e.g. + + ```yaml + output: + xaringan::moon_reader: + chakra: libs/remark-latest.min.js + ``` + +- If you used Google fonts in slides (the default theme uses _Yanone Kaffeesatz_, _Droid Serif_, and _Source Code Pro_), they won't work offline unless you download or install them locally. The Heroku app [google-webfonts-helper](https://google-webfonts-helper.herokuapp.com/fonts) can help you download fonts and generate the necessary CSS. + +--- + +# Macros + +- remark.js [allows users to define custom macros](https://github.com/yihui/xaringan/issues/80) (JS functions) that can be applied to Markdown text using the syntax `![:macroName arg1, arg2, ...]` or `![:macroName arg1, arg2, ...](this)`. For example, before remark.js initializes the slides, you can define a macro named `scale`: + + ```js + remark.macros.scale = function (percentage) { + var url = this; + return ''; + }; + ``` + + Then the Markdown text + + ```markdown + ![:scale 50%](image.jpg) + ``` + + will be translated to + + ```html + + ``` + +--- + +# Macros (continued) + +- To insert macros in **xaringan** slides, you can use the option `beforeInit` under the option `nature`, e.g., + + ```yaml + output: + xaringan::moon_reader: + nature: + beforeInit: "macros.js" + ``` + + You save your remark.js macros in the file `macros.js`. + +- The `beforeInit` option can be used to insert arbitrary JS code before `remark.create()`. Inserting macros is just one of its possible applications. + +--- + +# CSS + +Among all options in `xaringan::moon_reader`, the most challenging but perhaps also the most rewarding one is `css`, because it allows you to customize the appearance of your slides using any CSS rules or hacks you know. + +You can see the default CSS file [here](https://github.com/yihui/xaringan/blob/master/inst/rmarkdown/templates/xaringan/resources/default.css). You can completely replace it with your own CSS files, or define new rules to override the default. See the help page `?xaringan::moon_reader` for more information. + +--- + +# CSS + +For example, suppose you want to change the font for code from the default "Source Code Pro" to "Ubuntu Mono". You can create a CSS file named, say, `ubuntu-mono.css`: + +```css +@import url(https://fonts.googleapis.com/css?family=Ubuntu+Mono:400,700,400italic); + +.remark-code, .remark-inline-code { font-family: 'Ubuntu Mono'; } +``` + +Then set the `css` option in the YAML metadata: + +```yaml +output: + xaringan::moon_reader: + css: ["default", "ubuntu-mono.css"] +``` + +Here I assume `ubuntu-mono.css` is under the same directory as your Rmd. + +See [yihui/xaringan#83](https://github.com/yihui/xaringan/issues/83) for an example of using the [Fira Code](https://github.com/tonsky/FiraCode) font, which supports ligatures in program code. + +--- + +# CSS (with Sass) + +**xaringan** also supports Sass support via **rmarkdown**. Suppose you want to use the same color for different elements, e.g., first heading and bold text. You can create a `.scss` file, say `mytheme.scss`, using the [sass](https://sass-lang.com/) syntax with variables: + +```scss +$mycolor: #ff0000; +.remark-slide-content > h1 { color: $mycolor; } +.remark-slide-content strong { color: $mycolor; } +``` + +Then set the `css` option in the YAML metadata using this file placed under the same directory as your Rmd: + +```yaml +output: + xaringan::moon_reader: + css: ["default", "mytheme.scss"] +``` + +This requires **rmarkdown** >= 2.8 and the [**sass**](https://rstudio.github.io/sass/) package. You can learn more about **rmarkdown** and **sass** support in [this blog post](https://blog.rstudio.com/2021/04/15/2021-spring-rmd-news/#sass-and-scss-support-for-html-based-output) and in [**sass** overview vignette](https://rstudio.github.io/sass/articles/sass.html). + +--- + +# Themes + +Don't want to learn CSS? Okay, you can use some user-contributed themes. A theme typically consists of two CSS files `foo.css` and `foo-fonts.css`, where `foo` is the theme name. Below are some existing themes: + +```{r, R.options=list(width = 70)} +names(xaringan:::list_css()) +``` + +--- + +# Themes + +To use a theme, you can specify the `css` option as an array of CSS filenames (without the `.css` extensions), e.g., + +```yaml +output: + xaringan::moon_reader: + css: [default, metropolis, metropolis-fonts] +``` + +If you want to contribute a theme to **xaringan**, please read [this blog post](https://yihui.org/en/2017/10/xaringan-themes). + +--- +class: inverse, middle, center +background-image: url(https://upload.wikimedia.org/wikipedia/commons/3/39/Naruto_Shiki_Fujin.svg) +background-size: contain + +# Naruto + +--- +background-image: url(https://upload.wikimedia.org/wikipedia/commons/b/be/Sharingan_triple.svg) +background-size: 100px +background-position: 90% 8% + +# Sharingan + +The R package name **xaringan** was derived1 from **Sharingan**, a dōjutsu in the Japanese anime _Naruto_ with two abilities: + +- the "Eye of Insight" + +- the "Eye of Hypnotism" + +I think a presentation is basically a way to communicate insights to the audience, and a great presentation may even "hypnotize" the audience.2,3 + +.footnote[ +[1] In Chinese, the pronounciation of _X_ is _Sh_ /ʃ/ (as in _shrimp_). Now you should have a better idea of how to pronounce my last name _Xie_. + +[2] By comparison, bad presentations only put the audience to sleep. + +[3] Personally I find that setting background images for slides is a killer feature of remark.js. It is an effective way to bring visual impact into your presentations. +] + +--- + +# Naruto terminology + +The **xaringan** package borrowed a few terms from Naruto, such as + +- [Sharingan](https://naruto.fandom.com/wiki/Sharingan) (写輪眼; the package name) + +- The [moon reader](https://naruto.fandom.com/wiki/Moon_Reader) (月読; an attractive R Markdown output format) + +- [Chakra](https://naruto.fandom.com/wiki/Chakra) (查克拉; the path to the remark.js library, which is the power to drive the presentation) + +- [Nature transformation](https://naruto.fandom.com/wiki/Nature_Transformation) (性質変化; transform the chakra by setting different options) + +- The [infinite moon reader](https://naruto.fandom.com/wiki/Infinite_Tsukuyomi) (無限月読; start a local web server to continuously serve your slides) + +- The [summoning technique](https://naruto.fandom.com/wiki/Summoning_Technique) (download remark.js from the web) + +You can click the links to know more about them if you want. The jutsu "Moon Reader" may seem a little evil, but that does not mean your slides are evil. + +--- + +class: center + +# Hand seals (印) + +Press `h` or `?` to see the possible ninjutsu you can use in remark.js. + +![](https://upload.wikimedia.org/wikipedia/commons/7/7e/Mudra-Naruto-KageBunshin.svg) + +--- + +class: center, middle + +# Thanks! + +Slides created via the R package [**xaringan**](https://github.com/yihui/xaringan). + +The chakra comes from [remark.js](https://remarkjs.com), [**knitr**](https://yihui.org/knitr/), and [R Markdown](https://rmarkdown.rstudio.com). From 2eb0df9f7090ffa597a1ae67ec9f34695e05b0fa Mon Sep 17 00:00:00 2001 From: dreimer7 <112495919+dreimer7@users.noreply.github.com> Date: Fri, 23 Jan 2026 14:39:37 -0500 Subject: [PATCH 2/5] Add files via upload --- presentations/BasePres.html | 930 ++++++++++++++++++++++++++++++++++++ 1 file changed, 930 insertions(+) create mode 100644 presentations/BasePres.html diff --git a/presentations/BasePres.html b/presentations/BasePres.html new file mode 100644 index 0000000..370b297 --- /dev/null +++ b/presentations/BasePres.html @@ -0,0 +1,930 @@ + + + + Test Slide + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + From 4c1f372d3712de9c3bdf763c7e84a113d4d4b3c2 Mon Sep 17 00:00:00 2001 From: dreimer7 <112495919+dreimer7@users.noreply.github.com> Date: Fri, 30 Jan 2026 13:49:00 -0500 Subject: [PATCH 3/5] added first idea --- .DS_Store | Bin 0 -> 6148 bytes mini project/ReimerIdea1.md | 16 ++++++++++++++++ mini project/ReimerIdea1.md.html | 16 ++++++++++++++++ 3 files changed, 32 insertions(+) create mode 100644 .DS_Store create mode 100644 mini project/ReimerIdea1.md create mode 100644 mini project/ReimerIdea1.md.html diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..f03625d8d3934104bf8faff7263bd3bf3a3acec2 GIT binary patch literal 6148 zcmeHKyH3L}6g@62DvyeejDZiRXoZ*<(kdMoSm+PXHl-A`P1VQ1mTzES;2RJFKf%C9 z!MV1Pl9VDb6an&$u1{>A8`~$29RpB}MOX#O0E%?M{5F$MOzOp#EN4qfL?zES8%EvE zFzPTb4|L`fa0>ix1?1b!BSaf>v@_ptgLRcRZF&#~2n-J%j&a1xLkkm3F~Aso=4vdf z;Y63;V#uqF4i=c9LSBfgObgGM7B}CswF%m{t=qdy;By zQuzgEgUpt0hAZReimerIdea1.md +

First Idea

+

Delaney Reimer

+

My idea is to look at Netflix original shows that were cancelled after only one season. I plan to look at all of these measures to see if there are patterns or outliers in the shows that were cancelled:

+ +

For viewership stats, I can pull data from 2023-2025 from Netflix’s Engagement Reports, which have been compiled here. Rotten Tomatoes ratings will obviously be available on Rotten Tomatoes, which can potentially be scraped or individually input depending on the volume of data. I’m not sure where to find production and marketing costs, or if that’ll even be publicly available for all of the shows I’m looking at yet. I’ve found a dataset with genre information on Kaggle, so that’s already settled.

+

For this, I will be using an inferential model to determine correlation between viewership, rating, and genre and cancellation/lack of renewal.

+

This research will be important to both executives/stakeholders in knowing which shows are most likely to be cancelled after only one season (vs. ones that will be renewed and likely more profitable), as well as consumers to reveal the reasoning behind cancellation and whether they can expect other shows they enjoy to be renewed or cancelled down the line.

+

Since all of this data will be public (except for possibly costs), there is no ethical issues with data usage. This model could potentially assist in future creation or production, as well as make the process more transparent for consumers/subscribers.

+ + \ No newline at end of file From f068b88f500bb2249342f5da65c9758c5be922e6 Mon Sep 17 00:00:00 2001 From: dreimer7 <112495919+dreimer7@users.noreply.github.com> Date: Fri, 30 Jan 2026 14:28:52 -0500 Subject: [PATCH 4/5] updated idea 1 --- .DS_Store | Bin 6148 -> 6148 bytes mini project/.DS_Store | Bin 0 -> 6148 bytes mini project/ReimerIdea1.md | 8 ++++---- mini project/ReimerIdea1.md.html | 8 ++++---- 4 files changed, 8 insertions(+), 8 deletions(-) create mode 100644 mini project/.DS_Store diff --git a/.DS_Store b/.DS_Store index f03625d8d3934104bf8faff7263bd3bf3a3acec2..14dc33ce7378cadc472b41081af8a9d76409946f 100644 GIT binary patch delta 252 zcmZoMXfc@J&&aW}?5J|k2iUjwKTw&UiHrjkXQD+aig>SBISkb5e6`%rCfC^B7dlj(W3mZKKGExC5Kn1=Ouc*2 literal 0 HcmV?d00001 diff --git a/mini project/ReimerIdea1.md b/mini project/ReimerIdea1.md index 9bd5ca3..f584f38 100644 --- a/mini project/ReimerIdea1.md +++ b/mini project/ReimerIdea1.md @@ -7,10 +7,10 @@ My idea is to look at Netflix original shows that were cancelled after only one - Rotten Tomatoes Rating - Genre(s)/Categorization in Netflix -For viewership stats, I can pull data from 2023-2025 from Netflix's Engagement Reports, which have been compiled [here](https://www.whats-on-netflix.com/most-popular/netflix-engagement-report-search/). Rotten Tomatoes ratings will obviously be available on Rotten Tomatoes, which can potentially be scraped or individually input depending on the volume of data. I'm not sure where to find production and marketing costs, or if that'll even be publicly available for all of the shows I'm looking at yet. I've found a dataset with genre information on [Kaggle](https://www.kaggle.com/datasets/bhargavchirumamilla/netflix-movies-and-tv-shows-till-2025), so that's already settled. +For viewership stats, I can pull data from 2023-2025 from Netflix's Engagement Reports, which have been compiled [here](https://www.whats-on-netflix.com/most-popular/netflix-engagement-report-search/). Rotten Tomatoes ratings will obviously be available on Rotten Tomatoes, which can potentially be scraped or individually input depending on the volume of data. I'm not sure where to find production and marketing costs, or if that'll even be publicly available for all of the shows I'm looking at yet. I've found a dataset with genre information on [Kaggle](https://www.kaggle.com/datasets/bhargavchirumamilla/netflix-movies-and-tv-shows-till-2025), so that's already settled. As for a list of cancelled Netflix original shows, [this article](https://en.wikipedia.org/wiki/List_of_ended_Netflix_original_programming) contains a comprehensive list of ended Netflix shows, which I will filter to only look at those that were cancelled (i.e., not limited series that were only expected to have a single season) and that only had one season before cancellation. -For this, I will be using an inferential model to determine correlation between viewership, rating, and genre and cancellation/lack of renewal. +For this, I will be using an inferential model to determine if there is a correlation between viewership, rating, and genre and cancellation/lack of renewal, and if so, what it might be. -This research will be important to both executives/stakeholders in knowing which shows are most likely to be cancelled after only one season (vs. ones that will be renewed and likely more profitable), as well as consumers to reveal the reasoning behind cancellation and whether they can expect other shows they enjoy to be renewed or cancelled down the line. +This research will be important to both executives/stakeholders in knowing which shows are most likely to be cancelled after only one season and thus probably not as worth it to create, as viewers prefer complete stories over cliffhangers that will never be resolved. This will also be important to consumers to give an insight into the reasoning behind cancellation of shows and whether they can expect other shows they enjoy to be renewed or cancelled down the line. -Since all of this data will be public (except for possibly costs), there is no ethical issues with data usage. This model could potentially assist in future creation or production, as well as make the process more transparent for consumers/subscribers. \ No newline at end of file +Since all of this data will be public (except for possibly costs), there is no ethical issues with data privacy. In terms of benefits, this model could potentially assist in future creation or production (like what genres may be more popular/likely to be more widely enjoyed), as well as make the process more transparent for consumers/subscribers, since for the most part Netflix does not make a statement on the official reasoning behind cancellation. \ No newline at end of file diff --git a/mini project/ReimerIdea1.md.html b/mini project/ReimerIdea1.md.html index e3e0aee..2eee8de 100644 --- a/mini project/ReimerIdea1.md.html +++ b/mini project/ReimerIdea1.md.html @@ -8,9 +8,9 @@

Rotten Tomatoes Rating
  • Genre(s)/Categorization in Netflix
    • -

    For viewership stats, I can pull data from 2023-2025 from Netflix’s Engagement Reports, which have been compiled here. Rotten Tomatoes ratings will obviously be available on Rotten Tomatoes, which can potentially be scraped or individually input depending on the volume of data. I’m not sure where to find production and marketing costs, or if that’ll even be publicly available for all of the shows I’m looking at yet. I’ve found a dataset with genre information on Kaggle, so that’s already settled.

    -

    For this, I will be using an inferential model to determine correlation between viewership, rating, and genre and cancellation/lack of renewal.

    -

    This research will be important to both executives/stakeholders in knowing which shows are most likely to be cancelled after only one season (vs. ones that will be renewed and likely more profitable), as well as consumers to reveal the reasoning behind cancellation and whether they can expect other shows they enjoy to be renewed or cancelled down the line.

    -

    Since all of this data will be public (except for possibly costs), there is no ethical issues with data usage. This model could potentially assist in future creation or production, as well as make the process more transparent for consumers/subscribers.

    +

    For viewership stats, I can pull data from 2023-2025 from Netflix’s Engagement Reports, which have been compiled here. Rotten Tomatoes ratings will obviously be available on Rotten Tomatoes, which can potentially be scraped or individually input depending on the volume of data. I’m not sure where to find production and marketing costs, or if that’ll even be publicly available for all of the shows I’m looking at yet. I’ve found a dataset with genre information on Kaggle, so that’s already settled. As for a list of cancelled Netflix original shows, this article contains a comprehensive list of ended Netflix shows, which I will filter to only look at those that were cancelled (i.e., not limited series that were only expected to have a single season) and that only had one season before cancellation.

    +

    For this, I will be using an inferential model to determine if there is a correlation between viewership, rating, and genre and cancellation/lack of renewal, and if so, what it might be.

    +

    This research will be important to both executives/stakeholders in knowing which shows are most likely to be cancelled after only one season and thus probably not as worth it to create, as viewers prefer complete stories over cliffhangers that will never be resolved. This will also be important to consumers to give an insight into the reasoning behind cancellation of shows and whether they can expect other shows they enjoy to be renewed or cancelled down the line.

    +

    Since all of this data will be public (except for possibly costs), there is no ethical issues with data privacy. In terms of benefits, this model could potentially assist in future creation or production (like what genres may be more popular/likely to be more widely enjoyed), as well as make the process more transparent for consumers/subscribers, since for the most part Netflix does not make a statement on the official reasoning behind cancellation.

    \ No newline at end of file From 68266c94b3bccd2399b5490875412445a7fb4eaf Mon Sep 17 00:00:00 2001 From: dreimer7 <112495919+dreimer7@users.noreply.github.com> Date: Fri, 30 Jan 2026 14:50:33 -0500 Subject: [PATCH 5/5] added other aspect to idea 1 --- mini project/.DS_Store | Bin 6148 -> 6148 bytes mini project/ReimerIdea1.md | 3 ++- mini project/ReimerIdea1.md.html | 11 ++++++----- 3 files changed, 8 insertions(+), 6 deletions(-) diff --git a/mini project/.DS_Store b/mini project/.DS_Store index 548e0840451dba73aec4830826959bc9cb0f4b7f..dcf0de91c5c67c5de0b382fb8470fcf840a12b1e 100644 GIT binary patch delta 16 XcmZoMXfc?uo7IB!efx&Cz0T*!qEvN+_ diff --git a/mini project/ReimerIdea1.md b/mini project/ReimerIdea1.md index f584f38..298be67 100644 --- a/mini project/ReimerIdea1.md +++ b/mini project/ReimerIdea1.md @@ -6,8 +6,9 @@ My idea is to look at Netflix original shows that were cancelled after only one - Cost to Produce/Market (if available) - Rotten Tomatoes Rating - Genre(s)/Categorization in Netflix +- Number of Weeks in Top 10 -For viewership stats, I can pull data from 2023-2025 from Netflix's Engagement Reports, which have been compiled [here](https://www.whats-on-netflix.com/most-popular/netflix-engagement-report-search/). Rotten Tomatoes ratings will obviously be available on Rotten Tomatoes, which can potentially be scraped or individually input depending on the volume of data. I'm not sure where to find production and marketing costs, or if that'll even be publicly available for all of the shows I'm looking at yet. I've found a dataset with genre information on [Kaggle](https://www.kaggle.com/datasets/bhargavchirumamilla/netflix-movies-and-tv-shows-till-2025), so that's already settled. As for a list of cancelled Netflix original shows, [this article](https://en.wikipedia.org/wiki/List_of_ended_Netflix_original_programming) contains a comprehensive list of ended Netflix shows, which I will filter to only look at those that were cancelled (i.e., not limited series that were only expected to have a single season) and that only had one season before cancellation. +For viewership stats, I can pull data from 2023-2025 from Netflix's Engagement Reports, which have been compiled [here](https://www.whats-on-netflix.com/most-popular/netflix-engagement-report-search/). Rotten Tomatoes ratings will obviously be available on Rotten Tomatoes, which can potentially be scraped or individually input depending on the volume of data. I'm not sure where to find production and marketing costs, or if that'll even be publicly available for all of the shows I'm looking at yet. I've found a dataset with genre information on [Kaggle](https://www.kaggle.com/datasets/bhargavchirumamilla/netflix-movies-and-tv-shows-till-2025), and a list of all shows (and films) in the Top 10 (and how many weeks they were in the Top 10) since July 2021 can be downloaded from [Tudum](https://www.netflix.com/tudum/top10), which I will cross-reference with the list of cancelled shows. As for compiling this list of Netflix original shows cancelled after one season, [this article](https://en.wikipedia.org/wiki/List_of_ended_Netflix_original_programming) contains a comprehensive list of ended Netflix shows, which I will filter to only look at those that were cancelled (i.e., not limited series that were only expected to have a single season) and that only had one season before cancellation. For this, I will be using an inferential model to determine if there is a correlation between viewership, rating, and genre and cancellation/lack of renewal, and if so, what it might be. diff --git a/mini project/ReimerIdea1.md.html b/mini project/ReimerIdea1.md.html index 2eee8de..70d9311 100644 --- a/mini project/ReimerIdea1.md.html +++ b/mini project/ReimerIdea1.md.html @@ -6,11 +6,12 @@

    Viewership Stats (both hours watched and total watches [hours watched/length of show])
  • Cost to Produce/Market (if available)
  • Rotten Tomatoes Rating
    • -
  • Genre(s)/Categorization in Netflix
    • +
  • Genre(s)/Categorization in Netflix
    • +
  • Number of Weeks in Top 10
    • -

    For viewership stats, I can pull data from 2023-2025 from Netflix’s Engagement Reports, which have been compiled here. Rotten Tomatoes ratings will obviously be available on Rotten Tomatoes, which can potentially be scraped or individually input depending on the volume of data. I’m not sure where to find production and marketing costs, or if that’ll even be publicly available for all of the shows I’m looking at yet. I’ve found a dataset with genre information on Kaggle, so that’s already settled. As for a list of cancelled Netflix original shows, this article contains a comprehensive list of ended Netflix shows, which I will filter to only look at those that were cancelled (i.e., not limited series that were only expected to have a single season) and that only had one season before cancellation.

    -

    For this, I will be using an inferential model to determine if there is a correlation between viewership, rating, and genre and cancellation/lack of renewal, and if so, what it might be.

    -

    This research will be important to both executives/stakeholders in knowing which shows are most likely to be cancelled after only one season and thus probably not as worth it to create, as viewers prefer complete stories over cliffhangers that will never be resolved. This will also be important to consumers to give an insight into the reasoning behind cancellation of shows and whether they can expect other shows they enjoy to be renewed or cancelled down the line.

    -

    Since all of this data will be public (except for possibly costs), there is no ethical issues with data privacy. In terms of benefits, this model could potentially assist in future creation or production (like what genres may be more popular/likely to be more widely enjoyed), as well as make the process more transparent for consumers/subscribers, since for the most part Netflix does not make a statement on the official reasoning behind cancellation.

    +

    For viewership stats, I can pull data from 2023-2025 from Netflix’s Engagement Reports, which have been compiled here. Rotten Tomatoes ratings will obviously be available on Rotten Tomatoes, which can potentially be scraped or individually input depending on the volume of data. I’m not sure where to find production and marketing costs, or if that’ll even be publicly available for all of the shows I’m looking at yet. I’ve found a dataset with genre information on Kaggle, and a list of all shows (and films) in the Top 10 (and how many weeks they were in the Top 10) since July 2021 can be downloaded from Tudum, which I will cross-reference with the list of cancelled shows. As for compiling this list of Netflix original shows cancelled after one season, this article contains a comprehensive list of ended Netflix shows, which I will filter to only look at those that were cancelled (i.e., not limited series that were only expected to have a single season) and that only had one season before cancellation.

    +

    For this, I will be using an inferential model to determine if there is a correlation between viewership, rating, and genre and cancellation/lack of renewal, and if so, what it might be.

    +

    This research will be important to both executives/stakeholders in knowing which shows are most likely to be cancelled after only one season and thus probably not as worth it to create, as viewers prefer complete stories over cliffhangers that will never be resolved. This will also be important to consumers to give an insight into the reasoning behind cancellation of shows and whether they can expect other shows they enjoy to be renewed or cancelled down the line.

    +

    Since all of this data will be public (except for possibly costs), there is no ethical issues with data privacy. In terms of benefits, this model could potentially assist in future creation or production (like what genres may be more popular/likely to be more widely enjoyed), as well as make the process more transparent for consumers/subscribers, since for the most part Netflix does not make a statement on the official reasoning behind cancellation.

    \ No newline at end of file