I love food and I love travel. Naturally I decided to compile a list of all the best restaurants in the world. Still very much a work-in-progress but would love to get feedback.
Like others, bookmarked. So useful, thank you. Feedback as requested:
1. It's a map of "the best", so maybe the default filter shouldn't show "ok" recommendations
2. The numbers on the pins change regularly (I'm on mobile/Firefox). Maybe the pin could indicate the source of the review, or the quality, or the restaurant type? Or not have the number at all.
3. Moving the map around reloads the pins for the viewed area, but it sometimes loads a different set of pins for a big city. Is there a max number of pins being loaded on each map view change? If so, perhaps the max should be higher?
1. Agreed, I'll likely hide them by default. The results from Gayot/Eater are incredibly noisy, and I doubt most people are interested in seeing restaurants from Gayot's "Top 10 dog-friendly date brunch spots this holiday."
2/3. I was experimenting with numeric pins but have now switched back to pins which vary by size depending on the restaurant awards. I also increased the pin count to 50 by default. Can you try it again and see if it feels more intuitive?
I see what you mean now. This has become an interesting experiment in UX. I updated the platform to leave any previous pins on the map (even if they're no longer in the top 50 results). Hopefully it works better now!
Wow also had a similar idea! How are you getting the google review aggregate if you don't mind me asking? Even simply plotting Michelin restaurants seems like such a good idea in retrospect. I wanted to do something similar with famous food bloggers, maybe you can consider adding that to your list. Something like all of Mark Wein's recs on a map, with a link back to the original youtube video. Automatically adding data from different sources is the hard part I couldn't get over, especially since some of the videos don't have a location in the text.
This is amazing. So much easier than the official Michelin app. I’ve had the same idea to aggregate real reviews… because google reviews are pretty useless if you’re looking for special places.
Thanks! I struggled with the same problems. Existing search tools make it difficult to discover high-quality restaurants (either via poor UI, lack of granular filters, or low quality content). I'd be curious to hear if you have a better solution to filter/gather reviews.
Very cool - I assume most of the data is gathered through scraping? Quite a few of the sources you're pulling from don't look like they have APIs available.
So glad to hear that! After building the V1, I was similarly surprised by how many new restaurants I was able to instantly discover. Even found a few spots which I'm tempted to travel for.
Thanks for the kind words! Technically it's nothing to write home about. It's a Frankenstein's monster combination of vanilla CSS/JS stitched together with whatever random third-party libraries I could find online. I would not recommend looking under the hood :)
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Hi HN, I spent the last few weeks aggregating and playing with covid data. This is a compilation of my favorite data visualizations, along with multiple customization options for each chart. Happy to hear any feedback, suggestions for existing charts, as well as ideas for new charts!
I recently had to deal with this problem when building out Covidly (www.covidly.com)
Initially I tried using WHO and JHU, but quickly found their data to be riddled with discrepancies, occasional bugs, and direct contradictions with official statements from various countries.
I ended up aggregating multiple sources (including WHO/JHU/etc), performing some sanity checks to remove outliers, then doing my best to merge the remaining results.
Happy to share this data publicly if there's interest!
"Explosive growth" and "Virus is largely out of control" is dangerous risk communication.
How often are you updating the data? If there's manual deconfliction, do you clearly indicate how old data for a country or state/province is, or how accurate the reporting is that your massaged summary comes from?
If you're meaning to put this out in the world as a source of information please get some feedback first from people that do this sort of thing for a living. Inaccuracy or excitable language can do more harm than good in emergencies.
You make a very good point about risk communication. I already had to make a few updates (e.g. hiding the mortality rate) that were causing unnecessary panic. I'll work on optimizing the existing language as well.
Regarding the data, it's updated and processed automatically every 10 minutes.
I really appreciate the feedback! Let me know if anything else stands out to you.
Here, I would recommend that mortality rates are not bad. The goal in risk communication is to instill a level of concern equal to the current threat. It's all about context.
If you show infection, death and recovery rates, you have to provide context and help people understand what a thing means.
1-10 scales can make parsing difficult (3 and 4 have the same description right now, for example). Governments, militaries and emergency aid orgs put a lot of effort into color and coding systems.
Give Peter Sandman a Google, and check out his site here:
He's an expert in how to talk about scary, hard-to-visualize things (like a viral pandemic).
Also, how old is the data being drawn from, what algorithm do you use to de-conflict the sources, and how do you disclose this to your audience (other than the general about page)? If a source has different refresh rates for countries that it tracks, how are you reflecting that to your audience?
A note, China is missing from your nifty "First 20 days" graph, which maybe you should just call "First 20 days after 200 cases" or something like this to make it clearer what's being tracked.
I would love to see what you're doing here. I'm pulling it from JHU, it's been pretty consistent, but not as up to date as I would like. But I'm looking into aggregating data from other places such as Wikipedia. It would be great if there was more of a group effort here.
I've seen some efforts such as: https://github.com/covid19-data/covid19-data which is looking to separate out the data aggregation from the dashboard. However, they are scrubbing out the state-based information which I rely on.
I am a researcher, and I fail to find detailed data, please help! In all datasets we see cumulative confirmed, recovered and death numbers organized by day. We would need culumative confirmed by onset time (first symptoms), and confirmed by test time (the current value). We would also need recovered and death by onset time and confirmation time. Where are these numbers?
Unfortunately the existing public data sets I've seen lack this information. The level of detail for each confirmed case is largely dependent on which country is reporting the data (plus it's often in an unstructured and inconsistent format). I would love to know if you find any data source with more details.
For a site focused on "clarity", I sure didn't make the formula very clear :) I will work on clarifying it on the website.
The formula is a combination of:
40% - new cases / total cases (indicator of how much things are blowing up)
40% - absolute number of new cases (indicator for whether things are slowing down or not)
20% - recovered cases / total cases (indicator for recovery progress, although not all countries seem to post their recovery data)
The formula itself is somewhat arbitrary, but I felt it was a decently good metric that summarized the situation in every country. I'm open to suggestions on how to improve it as well!
Great question - I have heard both of the options you mentioned as possible explanations for the decline of new cases.
Personally I like to give countries the benefit of the doubt. As difficult as it sounds to quarantine and stop the spread of a virus in a country with 1+ billion people and multiple 10M+ cities, China is one of the few countries that could actually pull it off.
At the end of the day, the option you pick probably depends on whether or not you trust the numbers provided :)
1. https://mapofthebest.com - Simplifies finding the best restaurants & bars around the world
2. https://barspro.com - Helps me identify the healthiest energy & protein bars
3. https://www.foodie.bot - Automatic restaurant reservation checker & booker
I'm starting to realize all my projects are food-related...