Boolean & Fancy Indexing

Boolean indexing selects array elements by a True/False condition, while fancy indexing selects them by an array of integer positions — together they let you filter and gather data without writing a single loop.

Learn Boolean & Fancy Indexing in our free NumPy course — a beginner-friendly interactive lesson with worked examples, a practice exercise and a quick…

Part of the free Numpy course at LearnCodingFast — hands-on lessons with examples you run in your browser, plus practice exercises and a quick quiz.

In this lesson you'll build boolean masks, filter with conditions, combine tests with & and | , overwrite values that match a rule, and grab arbitrary elements with integer index arrays.

A comparison like arr > 5 doesn't return a single answer — it compares every element and returns a boolean mask : an array of True / False the same shape as the original. That mask is the foundation of filtering, where each True marks a position you want to keep.

Expected output: [False True False True False True] and (6,) .

Put the mask inside the brackets — arr[arr > 5] — and NumPy returns only the elements where the mask is True . This is the single most common way to filter data in NumPy, and the result is always a 1D copy of the matching values.

To combine two tests, use & for "and" and | for "or". Wrap each comparison in parentheses — these operators bind tighter than > or < , so without parentheses NumPy reads the expression wrong and errors out.

A mask can sit on the left of an assignment too. arr[arr < 0] = 0 finds every negative value and replaces it with zero in place — a clean way to clip or clean data.

Expected output: [0 5 0 8 0 2] then [0 5 0 6 0 2] .

Fancy indexing uses a list or array of positions to pick elements in any order: arr[[0, 2, 4]] . It also works on 2D arrays — pass an array of row indices and an array of column indices to gather specific cells.

Expected output: [10 30 50] , [50 10 20] , and [2 7] .

Replace each ___ so the program filters, combines conditions, and uses fancy indexing.

Expected output: [ 9 11] , [4 6] , [ 2 11] . (Answers: > , & , 0 .)

❌ ValueError: The truth value of an array with more than one element is ambiguous

You combined conditions with and / or instead of the bitwise operators.

✅ Fix: use & and | — for example (arr > 2) & (arr < 9) .

❌ Wrong results when combining two conditions

You left out the parentheses, so & ran before the comparisons.

✅ Fix: wrap each test: (arr > 2) & (arr < 9) , never arr > 2 & arr < 9 .

A sensor reports some impossible negative readings. Clip them to zero, then count how many readings are above 50.

Lesson 7 complete — you can filter like a pro!

You now build boolean masks, filter with conditions, combine tests with & and | (always in parentheses), overwrite matching values, and gather arbitrary elements with fancy integer indexing.

🚀 Up next: Reshaping and Flattening — change an array's shape without touching its data.

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