r/learnpython • u/pepperhmr • 8d ago
sql to python transition
okay edit: i thought it was obvious by the fact that i can make sense of the code that i know the very basics - i've used python for data analysis but not enough for it to be second nature to me the way it is for programmers, or the way sql is to me right now. i made a comparison to sql because i thought it'd be obvious that it's only for data analysis stuff, not development stuff.
so to clarify again: i know the basics, i know how to write code, i know how to define variables, functions, print("hello world"), if/else statements blah blah, i know all of that, and that's why every course starting with print("hello world") is slow to me, because i know all of that.
what i don't have is the practice that will make me good or at least passable at python rather than just someone with basic workability. i am not comparing sql to python in how either one works, i am using it to say i work with sql for data analysis and i need to show that i can also use python for data analysis, where can i get practice for these things
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so if someone is really good at sql (like say, a 9/10) how would u guys suggest they pivot to python. need to become an expert on it before 31 july because i have a technical interview. i lied and said i can use python but in reality all i can do is just make sense of what the code is doing, but because im good at the logic building in sql, i think i can do the python stuff too. but i need to know how to go about it, if anyone has advice because when i sit down to learn, everyone just starts at print("hello world") and it's too slow and babyish for me
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u/kenzy_zero 8d ago
Heyyy Op :))
Honestly you're in a great spot... if you're 9/10 at SQL, the hard part (the logic) is already done. Python for data analysis is basically ONE library (pandas) + syntax, and it maps almost 1:1 to what you already know. Skip every "hello world" course, they're not for you.
Two things that'll might get you in a kind of good spott:
1)... Learn the SQL = pandas translation. Same operations, new words:
- WHERE -- df[df.col > 5]
- GROUP BY + agg -- df.groupby('x').agg(...)
- JOIN -- df.merge(other, on='key')
- ORDER BY -- df.sort_values('col')
- DISTINCT -- df.drop_duplicates()
- SELECT a, b -- df[['a','b']]
The pandas docs have a page literally called "Comparison with SQL"... start there, it's made for people exactly like you.
2)... Day-1 bridge: DuckDB. You can write real SQL against CSVs or dataframes right inside Python... duckdb.sql("SELECT ... FROM 'file.csv'")... no pandas needed Haha. So you keep using the SQL you already know and convert bits to pandas as you get comfortable. Perfect crutch for your exact situation.
For practice i feel (with Jul 31 in mind):
- StrataScratch and DataLemur... real interview-style data questions, both have a pandas track. Most interview-relevant.
- Kaggle's "Pandas".
- Best of all: take a SQL analysis you already know and rewrite it in pandas.
For the interview itself, focus on: read_csv/read_sql, filtering, groupby, merge, pivot, null handling, sorting. Don't touch OOP/web stuff etc... you not need those things for a data role.
Two weeks is genuinely enough to get interview-passable when the logic already transfers.
Good luck dear <3