Technical Cheat Sheets
Quick reference guides for common data science and programming tasks. Built for practitioners who need answers fast.
Available Cheat Sheets
Pandas for SQL Users
Comprehensive mapping of SQL operations to pandas DataFrame methods. Perfect for SQL experts learning pandas.
- SELECT, WHERE, JOIN → DataFrame operations
- GROUP BY & aggregations
- Window functions & ranking
- NULL handling & string operations
- Performance tips & common gotchas
SAS String Functions
Trimming, substrings, concatenation, COMPRESS, SCAN, PRXCHANGE and regex patterns in SAS Base.
View Cheat SheetSQL Server String Functions
LEN, SUBSTRING, CHARINDEX, REPLACE, STUFF, CONCAT_WS, STRING_AGG, FORMAT and common patterns in T-SQL.
View Cheat SheetSQL Server Date & Datetime Functions
DATEADD, DATEDIFF, DATEPART, FORMAT, EOMONTH, DATEFROMPARTS, type overview and common patterns in T-SQL.
View Cheat SheetSAS Date & Datetime Functions
SAS date internals, INTNX, INTCK, MDY, DATEPART, TIMEPART, INPUT/PUT with date informats and common patterns.
View Cheat SheetHow to Use These Cheat Sheets
Learning Strategy:
- Side-by-side comparisons — see familiar patterns mapped to new syntax
- Copy-paste ready — all examples are runnable code
- Gotchas highlighted — learn from common mistakes
- Performance tips — write efficient code from the start
- Practice exercises — test your understanding
Best for:
- Transitioning between tools (SQL → pandas, R → Python, etc.)
- Quick lookup during coding
- Onboarding team members with different backgrounds
- Interview prep & skill refreshers
Request a Cheat Sheet
Have a topic you'd like to see covered? Common mappings or workflows that trip you up? These guides are meant to be practical and community-driven.
- Matplotlib/Seaborn quick plots
- Regex patterns for data cleaning
- Scikit-learn model selection & evaluation
- Bash one-liners for data pipelines
- Docker for ML workflows