/Curriculum/Intermediate•Data Cleaning

31. NumPy String OperationsIntermediate

Vectorized string manipulation with np.char: upper, lower, replace, and strip.

12 mins

Concept Overview

The `np.char` module provides vectorized string operations that execute string manipulations across arrays without Python for-loops.

Hardware Mental Model

`np.char.upper(names)` converts 100,000 text names to UPPERCASE in a single C-level loop.

Key Concepts (1)Click snippet to load in editor

`np.char` exposes standard string methods like `upper`, `lower`, `replace`, `split`, and `strip` as vectorized functions.

clean = np.char.strip(text_array)

Avoid these frequent beginner syntax and logic traps

❌ Incorrect:names.upper() # AttributeError: 'numpy.ndarray' has no attribute 'upper'

✓ Correct:np.char.upper(names)

String methods live inside the `np.char` sub-module, not directly on the ndarray instance.

Pro Tip: Always access string tools via `np.char.method(arr)`.

Core takeaway points from this topic

`np.char.upper()` / `np.char.lower()`: Vectorized case conversion.

`np.char.add(a, b)`: Element-wise string concatenation.

`np.char.replace(arr, old, new)`: Substring replacement.

`np.char.strip(arr)`: Trims surrounding whitespace.

Editor: 31. NumPy String Operations

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Execution Result

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Hands-on Mode

Solve the objective below using NumPy vectorized syntax

Create `arr = np.array(['numpy', 'python'])`, convert to uppercase with `np.char.upper(arr)`, and print.

Expected Output Target:['NUMPY' 'PYTHON']

Practice Workspace

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