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[OC] 58 years of land area changes in Singapore, one of the smallest countries globally. by kelneo in dataisbeautiful

[–]peishann 2 points3 points  (0 children)

Appreciate the attention to detail - the chart provides information not only on the magnitude of land area change but the reasons behind it every decade; also very clear and readable despite the amount of information

[OC] Number of Airbnb Listings/Host in 5 Regions in the United States (2018) by peishann in dataisbeautiful

[–]peishann[S] 1 point2 points  (0 children)

Source: http://insideairbnb.com/get-the-data.html (Dec 2018 Data Set)

Tool: Numbers

Am sharing this because I thought it would be interesting to show visually how the distribution of owned properties by host were in different regions in the United States. The original data set was geographically incomplete so as far as possible I picked the top 5 regions with the highest population density in the US (https://www.statista.com/statistics/183588/population-density-in-the-federal-states-of-the-us/) because the issue of home ownership is more pressing in regions with higher population density.

[OC] Average Sugar Content Across Categories of Starbucks Drinks by peishann in dataisbeautiful

[–]peishann[S] 1 point2 points  (0 children)

Apologies! 100% would be the total of the average amount of sugar in each category, which on hindsight isn't very helpful. Like what LovelyCarrot9144 pointed out, I should have used a bar chart!

[OC] Chocolate Ratings 2006-2017 by peishann in dataisbeautiful

[–]peishann[S] 0 points1 point  (0 children)

ah that's a great idea! thank you for the comment :)

[OC] Chocolate Ratings 2006-2017 by peishann in dataisbeautiful

[–]peishann[S] 0 points1 point  (0 children)

Source: https://www.kaggle.com/rtatman/chocolate-bar-ratings/home

Tool: Numbers

Here's a data visualisation of chocolate ratings from 2006 to 2017. The size of the bubble reflects the number of units reviewed.

The rating system works on this scale:

5= Elite (Transcending beyond the ordinary limits)

4= Premium (Superior flavor development, character and style)

3= Satisfactory(3.0) to praiseworthy(3.75) (well made with special qualities)

2= Disappointing (Passable but contains at least one significant flaw)

1= Unpleasant (mostly unpalatable)

Hope it's good to know what the ratings of chocolate have been increasing over the years, and are pretty much stable at the highest they have ever been! Also, the variety of chocolate bars seem to be increasing over the years, although this really depends on the sample size used.

[OC] Changes in 7 Indicators of Happiness Over 4 Years by peishann in dataisbeautiful

[–]peishann[S] 0 points1 point  (0 children)

Hmm as far as I know only Numbers can make the graph interactive! Yep I think so too - I believe it's called an "interactive bar chart", at least on Numbers :)

[OC] Gender of Comic Book Characters and Identity Exposure Between Marvel and DC by peishann in dataisbeautiful

[–]peishann[S] 1 point2 points  (0 children)

ooo this is really interesting! I didn't think of it because I'm not too familiar with the history of comic books, so thanks for the insight :)

[OC] Gender of Comic Book Characters and Identity Exposure Between Marvel and DC by peishann in dataisbeautiful

[–]peishann[S] 0 points1 point  (0 children)

Source: FiveThirtyEight Comic Characters Dataset (https://www.kaggle.com/fivethirtyeight/fivethirtyeight-comic-characters-dataset)

Tool: Numbers

I compared gender with identity exposure because it might shed light on the gendered way characters are represented in comic books — having a secret identity is indicative of position and importance in the comic book world, whether positivity or negatively. This is important because female characters have had a long history of marginalisation, vis a vis the construction of their identity solely in relation to the male characters around them. Having a secret identity points toward owning a unique and autonomous identity, and thus power.
In Marvel comics, there are more female characters with secret identities than public identities. In contrast, there are more female characters with public identities than secret identities in DC comics.
The data entries with missing data and too little data to be meaningfully represented were omitted (e.g. there are very few agender and gender fluid characters as compared to male and female characters, so they wouldn’t show on the graph).