General
PromptBeginner5 minmarkdown
→ df.dropna(subset=[TARGET_COL]
inplace=True)
0
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inplace=True)
│
evaluate all three branches simultaneously:
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ascending=False)
np.nan
N/A
CustomerID must be unique and non-null
Age cannot be 0 or negative
Price is the target — rows missing it are unusable
N/A
XGBoost / LinearRegression / Neural Network]
True/False)
price]
feature engineering
rules
# PROMPT() — UNIVERSAL MISSING VALUES HANDLER
accurate
sprint_todo.md
DevSecOps guidelines
`[ ] Current`
updates
jargon-free explanation of what the concept is.
ask which one to do first.