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Showing posts with the label Data

Boy vs Girl Marvel Movies?

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Purpose: To investigate what, if any, Marvel (MCU) movies males prefer more than females.     Source(s): I used the Wikipedia list of MCU films  Wikipedia page . I scraped most IMDB ratings mid-2019, but manually added in the post-2019 movies last week. When you have an IMDB account, there is a page that shows you gender demographics and age demographics. IMDB gets these demographics from their IMDB members who have registered with their gender and age. Excel Data  | Annotated R Code | Disney version | Pixar version   Highlights and Considerations: •           IMDb ratings are rated on a 10-point scale. The average IMDb rating (across the 26,000 most rated movies) is 6.92 with a standard deviation of 0.96. This means most average movie ratings (68%) across   movies are within 1 point of each other. Therefore, while a decimal point difference between gender ratings might seem negligible on a 10-point scal...

The Gender of Genre

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  Purpose: To determine what percent of Billboard top artists were male versus female.     Source(s): Billboard 100 year-end Top Artists charts 2011-2020 ( https://billboard.com/charts/year-end ) ( n = 850). I manually scraped the information and used my personal knowledge, Wikipedia, and images to determine gender. There might be an error or two in coding. Corrections are welcome.   Data is available here ( https://u.nu/kkIMw ).   Highlights and Considerations: •       Billboard rankings are based on digital songs sales, streaming, radio airplay, touring, and social engagement. •       “Top Artists” were defined as lead singer(s) or primary composer for instrumentals. Bands wherein artist(s) gender was ambiguous were excluded (e.g., mixed-gender duos, choirs, orchestras; n = 33) and were common in Classical ( n = 16) and Christian ( n = 12) music. •       Across above genres, women...

Boys vs Girls Disney Movies?

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  Purpose: To investigate if what Walt Disney Animation Studio Movies males prefer more than females (if any).   Source(s): I used the List of Walt Disney Animation Studios films Wikipedia page (https://u.nu/tAsiC). I scraped IMDB ratings mid-2019 to get the ratings. When you have an IMDB account, there is a page that shows you gender demographics and age demographics. IMDB gets these demographics from their IMDB members who have registered with their gender and age. Excel Data: (https://u.nu/OKPYh). Annotated R Code: ( https://u.nu/WTLnX )   Highlights and Considerations: •       Females tend to rate movies more favorably than males (Δ = 0.14). I group mean-centered the data (by gender) to see if women still liked Disney movies more than men after controlling for this small systematic bias. •       Disney movies are rated higher than the average IMDB rating (Δ = .45), but are more favorably rated by females than males c...

COVID-19 Canadian Dashboard

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Canadian Covid 19 Dashboard Social isolation can really change one's behavior. For me, it has meant spending a lot more time compiling and exploring different datasets in R. As I'm sure many others are, I have recently been playing with COVID-19 data. I was curious about how my home country of Canada has been handling COVID-19 so I created this dashboard to monitor the progress. Each graph hosted here is generated by my publicly available R code 1 and updates whenever I run the code (which tends to be daily). The data comes from official Canadian government reports 2 . If you have any questions, do not hesitate to ask. A few notes on the data... As one might expect, data during a pandemic isn't always accurate and up-to-date. There are several considerations when interpreting this data: New cases and deaths are reported on a 14-day rolling average. As day-to-day statistics can be volitile and influenced by systematic varaibles, I used a rolling ...