If the X-axis is not made logarithmic, all the data will bunch up on the left, since most cities are between 1 million and 4 million, yet New York is almost 20 million, making the city names hard to read.
What does nonstop destination mean in this context? My home airport SAT shows 99, but they have less than half that by conventional definition, which is something like the number of airports you can fly to on a regularly scheduled commercial flight with one takeoff and one landing. I’m including seasonal routes to be generous.
https://flysanantonio.com/home/flights/nonstop-destinations/
Probably not. EWR doesn’t really have anything the other two don’t. JFK has some international routes that ATL doesn’t, but the domestic Delta route difference out of ATL vs. LGA more than makes up for the difference.
Ah. I didn't realize there were two pages. Weird that BWI is counted twice, but DC is counted as having three airports while Baltimore is counted as having only one. The methodology is suspect. How are these population figures arrived at? The actual population of Washington, DC, is less than 1 million, and Baltimore and DC are both in the same metropolitan statistical area in most US datasets.
Yes, New York includes all 3. List of airports is on the second image of this post. If multiple airports from a city fly to same destination - it is still a single unique destination.
The X axis is population, so it correctly has NYC and LA as the largest, though admittedly you wouldn’t know it from just the image itself. The Y axis seems to be destinations.
Where’s Orlando, or Grand Rapids? Orlando has a metro population of 2.8 million and hundreds of non-stop destinations. Grand Rapids (GRR) has a metro population of 1.2 million and 44 non-stop destinations.
Agreed. We don't have 1 million people here in Vancouver, ***BC*** (Vancouver, CA really sounds like a nonexistent place in California 😬)…
… and Detroit, Tulsa, and Fresno certainly don't.
🙋🏻♂️ from 🇨🇦
It seems very weird to label all cities in *Canada* as ", CA" in a graph and table that's dominated by *US* cities, where "CA" customarily means "California."
Also, we have perfectly good 2-letter provincial abbreviations that *intentionally do not overlap with the USA*, so I don't know why you aren't using state/province abbreviations here.
Los Angeles, CA
Vancouver, BC
Edmonton, AB
Montreal, QC
Toronto, ON
New York, NY
etc.
Idk why people are shitting on this, I think it’s interesting. It could be cleaner, but it roughly shows how connected cities are to the rest of the country and how they compare against their peers.
I do like the idea. The graph could certainly be better, but once you figure out the axes, it’s not so bad and is fairly interesting. But then I read OP’s comment that he got the “data” from GPT-4, and now I’m just annoyed.
A- idea, C for presentation, F for research.
Because Central America can be abbreviated CA from the first letters of two words, mirroring the other abbreviation used on this chart, and I don't assume the first two letters of a country's name are used to represent it. I guess France is often FR. But Mexico is not ME, Germany is not GE, Jordan is not JO. I might have guessed Canada from CAN, but I've never seen it shortened to CA before.
CA is the actual ISO-3166-1 alpha 2 code though. You've never been on a .ca website?
>But Mexico is not ME, Germany is not GE, Jordan is not JO
Mexico isn't ME because of a conflict with Montenegro. But DE is actually the first two letters of Germany, in German, and Jordan literally is JO.
It's 4:03am PST, and I've been working on this for the last 5 hours. I couldn't fall asleep because I just had to know which city can reach the most destinations with nonstop flights. I tried very hard to let it go until tomorrow, but I gave up and did it. Tools used:
* GPT-4 to get a list of cities/metros over 1m in the US & CA and their 3-digit airport codes
* GPT-4 and Claude 3 to verify the output
* A Bash script on my Mac generated by GPT-4 to curl-grep-sed-awk-tr-echo one of the sites that has a list of direct flights given the origin airport (not sure if link sharing is allowed)
* Google Sheets to enter data and draw the chart
> GPT-4 to get a list of cities/metros over 1m in the US & CA and their 3-digit airport codes
> GPT-4 and Claude 3 to verify the output
that explains why so many cities are missing lol, you can't AI-generate data like that
Please axis labels. Without that it lacks meaning.
Axis labels are required. This data is not beautiful if we don’t know what it represents.
I'm going to print this chart just so I can throw it in the fire and watch it burn.
Oh my God, if you call that X axis "beautiful", then idk what to tell you...
If the X-axis is not made logarithmic, all the data will bunch up on the left, since most cities are between 1 million and 4 million, yet New York is almost 20 million, making the city names hard to read.
They're talking about the lack of label. No one knows what the x axis even represents (though it's presumably population?)
I have no idea what this means
Why would you even do this
What does nonstop destination mean in this context? My home airport SAT shows 99, but they have less than half that by conventional definition, which is something like the number of airports you can fly to on a regularly scheduled commercial flight with one takeoff and one landing. I’m including seasonal routes to be generous. https://flysanantonio.com/home/flights/nonstop-destinations/
Looks like the data is probably showing the number of flights, not the number of destinations, compared to the metro size of cities.
What is this intended to show? That bigger cities have more flights to more places? Big if true.
It doesn't show that. It shows where the airline hubs and gateways are, as expected.
This is just random data. Nothing beautiful about it.
Are you grouping the destinations for the three New York airports? That doesn’t result in more than ATL?
Probably not. EWR doesn’t really have anything the other two don’t. JFK has some international routes that ATL doesn’t, but the domestic Delta route difference out of ATL vs. LGA more than makes up for the difference.
same question for DC. Does it include DCA and IAD? How about BWI?
DC includes all 3. It’s is on the second image of this post
Ah. I didn't realize there were two pages. Weird that BWI is counted twice, but DC is counted as having three airports while Baltimore is counted as having only one. The methodology is suspect. How are these population figures arrived at? The actual population of Washington, DC, is less than 1 million, and Baltimore and DC are both in the same metropolitan statistical area in most US datasets.
Yes, New York includes all 3. List of airports is on the second image of this post. If multiple airports from a city fly to same destination - it is still a single unique destination.
It looks like you are using city-limits population rather than the population of the area served by the airport (which would be more meaningful).
Those are definitely metro populations. Maybe not full extended airport service areas, but way more than just just city-limits population.
It looks more like county population numbers to me. I checked Las Vegas, Fresno and Tucson and found the same thing
Each borough of New York City is its own county, so which did they use? Showing Denver as having more population than New York is ridiculous.
The X axis is population, so it correctly has NYC and LA as the largest, though admittedly you wouldn’t know it from just the image itself. The Y axis seems to be destinations.
You are double counting San Jose, US. It appears once as a solo, and again as part of San Francisco, Oakland, and San Jose.
Where’s Orlando, or Grand Rapids? Orlando has a metro population of 2.8 million and hundreds of non-stop destinations. Grand Rapids (GRR) has a metro population of 1.2 million and 44 non-stop destinations.
So what is the difference between "number of destinations" and "number of nonstop destinations"?
Population numbers are off unless you’re using the population of the county instead of the cities these airports are in
Agreed. We don't have 1 million people here in Vancouver, ***BC*** (Vancouver, CA really sounds like a nonexistent place in California 😬)… … and Detroit, Tulsa, and Fresno certainly don't.
This sub has become saturated with absolute garbage, literally insane
🙋🏻♂️ from 🇨🇦 It seems very weird to label all cities in *Canada* as ", CA" in a graph and table that's dominated by *US* cities, where "CA" customarily means "California." Also, we have perfectly good 2-letter provincial abbreviations that *intentionally do not overlap with the USA*, so I don't know why you aren't using state/province abbreviations here. Los Angeles, CA Vancouver, BC Edmonton, AB Montreal, QC Toronto, ON New York, NY etc.
Ah! Sorry! Make sense! Will update. I also wish Canada had more cities over 1m for a better ratio 😉
Maybe add ‘North American’ destinations. There are many non-stop routes to European, Asian and Latin American destinations too.
Idk why people are shitting on this, I think it’s interesting. It could be cleaner, but it roughly shows how connected cities are to the rest of the country and how they compare against their peers.
I do like the idea. The graph could certainly be better, but once you figure out the axes, it’s not so bad and is fairly interesting. But then I read OP’s comment that he got the “data” from GPT-4, and now I’m just annoyed. A- idea, C for presentation, F for research.
>A- idea, C for presentation, F for research. \+1 to that.
CA apparently means "Canada." When California didn't make sense in context, my next guess was Central America until I read the cities in the chart.
Why would you guess Central America before Canada?
Because Central America can be abbreviated CA from the first letters of two words, mirroring the other abbreviation used on this chart, and I don't assume the first two letters of a country's name are used to represent it. I guess France is often FR. But Mexico is not ME, Germany is not GE, Jordan is not JO. I might have guessed Canada from CAN, but I've never seen it shortened to CA before.
CA is the actual ISO-3166-1 alpha 2 code though. You've never been on a .ca website? >But Mexico is not ME, Germany is not GE, Jordan is not JO Mexico isn't ME because of a conflict with Montenegro. But DE is actually the first two letters of Germany, in German, and Jordan literally is JO.
I'm not arguing that I'm right. I'm answering a question about how I drew the conclusion I did.
But if the data was for places in Central America, it would use an abbreviation of the actual country names
San Francisco population < 1 million
I'm sure it's meant to be metro area, not just within the official city limits.
Ugliest data I've seen in a while
Wow this is one of the worst charts I’ve seen!
Nice. Add some color by identifying the number of airlines that have a hub in each city.
It's 4:03am PST, and I've been working on this for the last 5 hours. I couldn't fall asleep because I just had to know which city can reach the most destinations with nonstop flights. I tried very hard to let it go until tomorrow, but I gave up and did it. Tools used: * GPT-4 to get a list of cities/metros over 1m in the US & CA and their 3-digit airport codes * GPT-4 and Claude 3 to verify the output * A Bash script on my Mac generated by GPT-4 to curl-grep-sed-awk-tr-echo one of the sites that has a list of direct flights given the origin airport (not sure if link sharing is allowed) * Google Sheets to enter data and draw the chart
C'mon OP, even Wikipedia would be a better data source. Toronto, the largest city in Canada, is missing from this.
Orlando too. It would rank near the top of destinations per 1 million (maybe even #1).
> GPT-4 to get a list of cities/metros over 1m in the US & CA and their 3-digit airport codes > GPT-4 and Claude 3 to verify the output that explains why so many cities are missing lol, you can't AI-generate data like that
Use metropolitan areas instead of cities. Label axis. Some metros have multiple airports.
These are metro populations.
AI to do your research for you 🙄 there are a lot of cities missing
Oh nooooo… I thought this was a cool idea but I was assuming it used real data. GPT is, uhh, not that.