ตัดเครื่องหมายวรรคตอนและสัญลักษณ์

After stopwords, the next clutter is symbols. Commas, dollar signs, and emoji can confuse a model, so we often strip punctuation away.

Without cleanup, your model sees cat, and cat as two different tokens. That trailing comma splits one word into two features.

The string module hands you every common mark in one constant called punctuation, so you never type them out by hand.

The fastest way to delete characters is str.translate with a table that maps each mark to nothing at all.

You can also strip marks token by token. Apply translate inside a comprehension, then drop any token that became empty.

Need more control than the fixed list? A regex can wipe anything that is not a letter, number, or space.

Some symbols carry meaning. Stripping every dot turns u.s.a into usa, and that may not be what you want for your task.

Digits are not punctuation, but they are often noise. Decide on purpose whether to keep or drop numbers for your data.

The ASCII punctuation set misses curly quotes and emoji. A Unicode-aware regex catches the symbols a fixed list leaves behind.

Removing marks can leave gaps and double spaces. A quick whitespace squeeze tidies the result back into clean words.

Sequence matters. Strip punctuation before you split or compare, so trailing marks never sneak into your final tokens.

Pick the cleanest way to delete punctuation from a string.

You can now strip punctuation with translate or regex, handle Unicode and numbers on purpose, and squeeze leftover spaces for clean tokens.