Element-wise vector addition
Add equal-length numeric lists element-wise.
Scale a vector by scalar
Multiply every element by k.
Dot product of two vectors
Return sum of element-wise products.
Mean of a vector
Return arithmetic mean or 0.0 when empty.
Maximum element in vector
Return largest value or None when empty.
Minimum element in vector
Return smallest value or None when empty.
Clip vector to range
Clamp each value to [lo, hi].
Min-max normalize vector
Scale values to 0..1; equal values become all 0.0.
Sum each matrix row
Given rows, return each row sum.
Sum each matrix column
Return column totals for a rectangular matrix.
Showing 1–10 of 10 challenges · easy · Numpy & Vectorized Computing
Numpy & Vectorized Computing — Python coding challenges
What you will find here
This page lists numpy & vectorized computing challenges — real Python problems you solve in the browser IDE with instant test feedback. Each challenge includes a clear brief, starter code, and automated checks.
Challenges vs tutorials and quizzes
Challenges test what you can build under constraints. For guided teaching, use our Python tutorials. For quick checks, try quizzes or copy snippets from code samples.