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Before any fancy analysis, you measure text. Simple counts of characters and words already tell you a lot about a document. 📏

The len function returns how many characters a string holds, including spaces and punctuation.

Remember that whitespace like spaces and newlines are real characters, so they are included in any character count.

The split method breaks a string on whitespace and returns a list of words, your simplest path to word counting.

Apply len to the list from split and you get the word count of the whole document.

Plain split treats hello! as one word because punctuation sticks to letters. Good enough to start, but not perfect.

A quick sentence estimate is to count periods, question marks, and exclamation points. It is rough but instantly useful.

Divide total letters by word count to get average word length, a small signal about how dense the writing is.

The count method tells you how many times a substring appears, handy for tallying a single target word.

Put the word list into a set and its length is the number of unique words, a measure of vocabulary richness.

These statistics drive real decisions: spam filters flag odd lengths, and readability tools lean on word counts.

Test your grasp of basic Python text counting.

You can now count characters with len, words with split, unique words with a set, and rough sentences by punctuation. 🔢