Nah, I'll do it with SQL
Same here.
But have you tried duckdb?
You can do sql in the pandas dfs and it is fast af.
Pandas vs. Julia – cheat sheet and comparison
31–40 of 138 posts
Re: Pandas vs. Julia – cheat sheet and comparison
#32Earlier quoted context omitted.
Same here, I don't get the point of this other that "don't want to learn SQL".
You're saying all Pandas usage (an incredibly popular library) is because people don't want to use SQL?
It's a broken argument with some truth too it. IE you can run a SQL query put the result in a dataframe to dump it to an interchange format. But in the same breathe... If you learn to use SQL a great deal of workloads often used via dataframes APIs kind of disappear, and in doing so learning a new language to use a new dataframes API isn't really worth it.
Re: Pandas vs. Julia – cheat sheet and comparison
#33Yeah this is basically why I keep trying and bouncing off Julia. I understand the real performance reasons why you'd choose to use Julia but the syntax is the perfect distance from python to make it extremely difficult to me. It's just close enough to get constantly confused. So if I really wanted to do much work in it I'd have swear off python - and I can't do that because for trivial stuff python is more convenient…
Pretty sure dataframes jl isn't the fastest dataframes library out there. Think it's Polars, which has bindings in Rust and python. If I remember correctly the runner up is data.table. Similarly SQL/SQLite can often beat all of these So switching to Julia for speed in this context may not even make sense anyways...
Re: Pandas vs. Julia – cheat sheet and comparison
#34Yeah this is basically why I keep trying and bouncing off Julia. I understand the real performance reasons why you'd choose to use Julia but the syntax is the perfect distance from python to make it extremely difficult to me. It's just close enough to get constantly confused. So if I really wanted to do much work in it I'd have swear off python - and I can't do that because for trivial stuff python is more convenient…
I have done both complex and trivial stuff in both languages and Julia isn't more inconvenient for trivial things.
Just make sure you find the appropriate documentation because the package changes it's syntax an awful lot over the past four years or so and there are lots of tutorials, videos, and blogs that don't apply anymore.
Similarly make sure you research the ecosystem because everything in Julia is very fragmented, IE pandas.loadcsv will require two or more packages in it's Julia equivalent.
Re: Pandas vs. Julia – cheat sheet and comparison
#35Earlier quoted context omitted.
For what it's worth this is literally how the Julia community deals with feedback.
Ah, it's a post mentioning Julia, and there you are.
What can I say I am a reliable person trying to make sure less people get sucked into Julia without learning of it's downsides. To be fair, the same could be said to you ;).
Re: Pandas vs. Julia – cheat sheet and comparison
#36Re: Pandas vs. Julia – cheat sheet and comparison
#37The cheatsheet goes wrong already for the first example of declaring a df:
- you could do a range in python (range(11, 14))
- columns are called col_1 & col_2 vs a & b (both sets are horrible names)
- pandas defines index of 0, 1, 3, while Julia would most likely have 0, 1, 2?
Re: Pandas vs. Julia – cheat sheet and comparison
#38This seems very poor - the comparison is between pandas and DataFrames.jl, not Julia; syntax comparison is very surface-level; cheatsheats are low resolution; the learning curve section says nothing about the learning curve; and the conclusion is "do whatever you like".
Well Pandas is a framework, not a language, so it only makes sense to compare it to DataFrames.jl and not to Julia as a lanugage.
But I agree this should have been reflected in the title of the article.
Re: Pandas vs. Julia – cheat sheet and comparison
#39Earlier quoted context omitted.
Same here, I don't get the point of this other that "don't want to learn SQL".
You're saying all Pandas usage (an incredibly popular library) is because people don't want to use SQL?
As far as I am aware, plenty of use cases can also be done via OLAP.
Re: Pandas vs. Julia – cheat sheet and comparison
#40DataFrames.jl was for me on of the primary reasons to use Julia. I personally the syntax way easier than pandas, especially for more complex operations.
I find this cheat sheet doesn't do in justice.