Once the data is clean and neatly in standard format this becomes a matter of preference.
Work experience says that 90% of work is gathering, cleaning and transforming data from different sources. In this capacity Python has more options available.
It is a car. Most people will spend a good chunk of time and research before they buy a car including researching things like maintenance cost, reliability and resale value.
100% - most people will buy the brand they had before or buy the car because they like how it looks or buy the car because of the price/special financing... probably like 1% of the people will do some serious research, the rest is like "imma pay $850/month, what cool-looking thing can I get for that"
I, on the contrary, see mostly very rational decisions around me. And the sample is pretty large: coworkers, friends, family.
First, people buy the same brand they had if they were happy with it and the price is sane. That's totally reasonable in my book; and not just for cars.
Those who lease do not care about long term reliability, since they replace cars in 3 years while all major components are under warranty. So they are more likely to try new things. Again, reasonable.
I am sure there are exceptions, but I know of no one who picked a fairly expensive car (and $850 per month is a lot for a car) and started with the budget. My 2c.
> First, people buy the same brand they had if they were happy with it and the price is sane. That's totally reasonable in my book; and not just for cars.
This is pretty much what the person you replied to said, just in a different way.
In my surroundings(EU), I see the opposite. Everybody buys their car only after doing serious research. Most people easily swap brands.
For most people, driving comfort (we have more/less kids or aging grandparents, so need a bigger/smaller car) is a primary filter. Next is cost, where people are very aware there is not only the price but also the fuel economy and the maintenance. People know very well the parking spots in the city are limited and polluting cars are not allowed in more and more cities, so also look at small size or good enough eco scores.
There are exceptions: People getting a car from work spend whatever money they can get, and rich people optimizing for status get a BMW or maybe a Tesla.
median income in the US is still an unimpressive 58k and a reasonably well-maintained used-car would still represent a significant chunk of their income over several years. it's a car culture, and people care about that stuff -- they'll shop around.
as to if they can shop and resist marketing -- different discussion.
Work experience says that 90% of work is gathering, cleaning and transforming data from different sources. In this capacity Python has more options available.
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