Use pandas’ string accessor to normalize every string in a Series to lowercase. The method returns a new Series, making differently capitalized words comparable before counting or filtering. section 9.2 section 9.6
Count words without case differences
Given a Series s containing words from a text, chain `.str.lower()` before `.value_counts()`: `s.str.lower().value_counts().head(10)`. This counts “The” and “the” together while preserving the original Series. section 9.2
Extend lowercase normalization when preparing text for comparison or frequency analysis:
- Split each normalized string into words, then use `explode()` to place one word on each row. section 9.6
- Strip leading and trailing punctuation after lowercasing so sentence boundaries do not create separate word counts. section 9.2
- Apply the same pipeline to selected wine descriptions, such as French reviews or particular grape varieties. section 9.6
s.str.lower().value_counts().head(10)
Inspect the compact frequency-counting pipeline that applies lowercase normalization before selecting the ten most common words. section 9.2
