Trim cleans the edges of strings without changing their interiors. Through pandas' .str accessor, .str.strip() removes surrounding whitespace, while an argument specifies characters to remove from each string's beginning and end. section 9.2 section 9.6
Clean words before counting them
After splitting review text into individual words, chain .str.strip(string.punctuation) to prevent sentence punctuation from creating separate word counts. For example, `words = s.str.lower().str.split().explode().str.strip(string.punctuation)` produces lowercase tokens without leading or trailing punctuation; value_counts().head(10) can then find the most common words. section 9.2 section 9.6
Use trim when the unwanted characters occur at string boundaries:
- Call `s.str.strip()` to remove surrounding whitespace. section 9.2
- Pass a character string such as `':;'` to remove any of those characters from both ends. section 9.2
- Use `string.punctuation` for broad punctuation cleanup, then combine trimming with lower, split, explode, filtering, and value_counts. section 9.6
(
s
.str
.lower()
.str
.strip(string.punctuation)
.value_counts()
.head(10)
)
Inspect a complete chain that normalizes case, strips punctuation, and counts the ten most common words. section 9.2
