This dashboard focuses on Netflix movie offerings and compares the stock values for Netflix and AMC.
This dashboard examines Netflix’s movie offerings across multiple dimensions and pairs this analysis with a comparison of stock values for Netflix and AMC. Together, these visuals illustrate how content trends and industry changes appear both on-platform and in the stock market.
Value boxes show the present day values of Netflix and AMC stocks. The interactive Highchart plots show the trend over time for the range of data examined in the Netflix plots on the following pages. Stock data was downloaded from Yahoo Finance.
Last Update
Tue. Nov. 18, 2025
Netflix Adjusted Close
114.09
AMC Adjusted Close
2.18
The trend in the two plots appear similar but the y-axis axis scale differs.
This plot is an alternative to the High-Low Candlestick plot which can also be created as a highchart.
This section visualizes Netflix and AMC stock values from 2013 to 2022. The highlighted periods reflect industry-wide disruptions, allowing for a clear comparison between how streaming and theater companies responded to market changes.
Number of Netflix Movies from each Genre and Release Period.
| Release Time Period | Int | Dr | C | Do | K | A/A |
|---|---|---|---|---|---|---|
| 1981-2000 | 123 | 165 | 151 | 10 | 35 | 111 |
| 2001-2010 | 347 | 323 | 314 | 31 | 92 | 168 |
| 2011-2015 | 574 | 483 | 397 | 132 | 133 | 163 |
| 2016-2021 | 1627 | 1372 | 1105 | 656 | 374 | 372 |
Genres are shown in plot and table in order of prevalence.
Information on grouped and stacked bar charts
Information on plots with facets
Bonus link for multi-panel plots
This plot does not include genre information (shown on Page 2).
Further analyses would benefit from having data that differentiates between Netflix original content and Netflix content purchased from other sources.
Information on Area plots
Information on R Color Options
This pie chart series is similar to the area plot in terms of the information it provides but this option allows for a more intuitive comparison of the distribution of movie age ratings across individual years..
The plots below provide a comparison of Netflix’s revenue, expenditures, and net income from 2013 to 2021, giving insight into the company’s financial growth and spending patterns.
This dashboard was created using Quarto in RStudio, and the R Language and Environment.
The data used to create this dashboard were downloaded from:
Allaire J, Dervieux C (2024). quarto: R Interface to ‘Quarto’ Markdown Publishing System. R package version 1.4.4, https://CRAN.R-project.org/package=quarto.
Arnold J (2024). ggthemes: Extra Themes, Scales and Geoms for ‘ggplot2’. R package version 5.1.0, https://github.com/jrnold/ggthemes, https://jrnold.github.io/ggthemes/.
Auguie B (2017). gridExtra: Miscellaneous Functions for “Grid” Graphics. R package version 2.3.
Bache S, Wickham H (2025). magrittr: A Forward-Pipe Operator for R. doi:10.32614/CRAN.package.magrittr https://doi.org/10.32614/CRAN.package.magrittr, R package version 2.0.4, https://CRAN.R-project.org/package=magrittr.
Dancho M, Vaughan D (2025). tidyquant: Tidy Quantitative Financial Analysis. R package version 1.0.11, https://business-science.github.io/tidyquant/.
Kunst J (2022). highcharter: A Wrapper for the ‘Highcharts’ Library. R package version 0.9.4, https://CRAN.R-project.org/package=highcharter.
Neuwirth E (2022). RColorBrewer: ColorBrewer Palettes. R package version 1.1-3, https://CRAN.R-project.org/package=RColorBrewer.
Posit team (2025). RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA. URL http://www.posit.co/.
R Core Team (2025). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.https://www.R-project.org/.
Rinker, T. W. & Kurkiewicz, D. (2017). pacman: Package Management for R. version 0.5.0. Buffalo, New York. http://github.com/trinker/pacman
Vanderkam D, Allaire J, Owen J, Gromer D, Thieurmel B (2018). dygraphs: Interface to ‘Dygraphs’ Interactive Time Series Charting Library. R package version 1.1.1.6, https://github.com/rstudio/dygraphs.
Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019). “Welcome to the tidyverse.” Journal of Open Source Software, 4(43), 1686. doi:10.21105/joss.01686 https://doi.org/10.21105/joss.01686.
Xie Y (2025). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.50, https://yihui.org/knitr/.
Yihui Xie (2015) Dynamic Documents with R and knitr. 2nd edition. Chapman and Hall/CRC. ISBN 978-1498716963
Yihui Xie (2014) knitr: A Comprehensive Tool for Reproducible Research in R. In Victoria Stodden, Friedrich Leisch and Roger D. Peng, editors, Implementing Reproducible Computational Research. Chapman and Hall/CRC. ISBN 978-1466561595
Zhu H (2024). kableExtra: Construct Complex Table with ‘kable’ and Pipe Syntax. R package version 1.4.0, https://github.com/haozhu233/kableExtra, http://haozhu233.github.io/kableExtra/.