Word-Start Case Normalization with Space Preservation

Easy

A publishing workflow stores user-submitted text snippets with inconsistent capitalization. Table: UserContent(content_id, content_text) Task: For each row, transform content_text using these rules: Uppercase the first letter of each word. Lowercase all other letters in that word. Preserve spaces exactly as-is, including repeated, leading, and trailing spaces. A word is any maximal sequence of non-space characters. Text rows contain only English letters and spaces. Return columns in this exact order: content_id original_text converted_text Final ordering: content_id ascending Supported submission environments: SQL (SQLite 3.27.2) Pandas (Python)

Example 1

Input

UserContent:
| content_id | content_text                      |
|------------|-----------------------------------|
| 1          | hello world of SQL                |
| 2          | the QUICK brown fox               |
| 3          | TOP rated programming BOOKS       |

Output

[
  {"content_id":1,"original_text":"hello world of SQL","converted_text":"Hello World Of Sql"},
  {"content_id":2,"original_text":"the QUICK brown fox","converted_text":"The Quick Brown Fox"},
  {"content_id":3,"original_text":"TOP rated programming BOOKS","converted_text":"Top Rated Programming Books"}
]

Explanation

Each word is normalized to title-style casing while word boundaries remain based on spaces.

Example 2

Input

UserContent:
| content_id | content_text                     |
|------------|----------------------------------|
| 10         |   leadIng   SPACES and Trailing   |
| 11         | single                           |
| 12         | MIXED   case   TEXT              |

Output

[
  {"content_id":10,"original_text":"  leadIng   SPACES and Trailing   ","converted_text":"  Leading   Spaces And Trailing   "},
  {"content_id":11,"original_text":"single","converted_text":"Single"},
  {"content_id":12,"original_text":"MIXED   case   TEXT","converted_text":"Mixed   Case   Text"}
]

Explanation

All spaces are preserved exactly, including leading, trailing, and repeated separators.

Example 3

Input

UserContent:
| content_id | content_text    |
|------------|-----------------|
| 21         |                 |
| 22         | a b c           |
| 23         |    x   y        |

Output

[
  {"content_id":21,"original_text":"","converted_text":""},
  {"content_id":22,"original_text":"a b c","converted_text":"A B C"},
  {"content_id":23,"original_text":"   x   y   ","converted_text":"   X   Y   "}
]

Explanation

Empty strings stay empty, and single-letter words are capitalized correctly.

Constraints

1 <= number of rows in UserContent <= 4000
content_id is unique
1 <= content_id <= 1000000000
0 <= length(content_text) <= 180
content_text contains only English letters and spaces
Words are separated by one or more spaces
Preserve all spaces exactly in the output
Return output columns exactly as specified
Final output must be sorted by content_id ascending
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with required columns

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Word-Start Case Normalization with Space Preservation

Easy

A publishing workflow stores user-submitted text snippets with inconsistent capitalization. Table: UserContent(content_id, content_text) Task: For each row, transform content_text using these rules: Uppercase the first letter of each word. Lowercase all other letters in that word. Preserve spaces exactly as-is, including repeated, leading, and trailing spaces. A word is any maximal sequence of non-space characters. Text rows contain only English letters and spaces. Return columns in this exact order: content_id original_text converted_text Final ordering: content_id ascending Supported submission environments: SQL (SQLite 3.27.2) Pandas (Python)

Example 1

Input

UserContent:
| content_id | content_text                      |
|------------|-----------------------------------|
| 1          | hello world of SQL                |
| 2          | the QUICK brown fox               |
| 3          | TOP rated programming BOOKS       |

Output

[
  {"content_id":1,"original_text":"hello world of SQL","converted_text":"Hello World Of Sql"},
  {"content_id":2,"original_text":"the QUICK brown fox","converted_text":"The Quick Brown Fox"},
  {"content_id":3,"original_text":"TOP rated programming BOOKS","converted_text":"Top Rated Programming Books"}
]

Explanation

Each word is normalized to title-style casing while word boundaries remain based on spaces.

Example 2

Input

UserContent:
| content_id | content_text                     |
|------------|----------------------------------|
| 10         |   leadIng   SPACES and Trailing   |
| 11         | single                           |
| 12         | MIXED   case   TEXT              |

Output

[
  {"content_id":10,"original_text":"  leadIng   SPACES and Trailing   ","converted_text":"  Leading   Spaces And Trailing   "},
  {"content_id":11,"original_text":"single","converted_text":"Single"},
  {"content_id":12,"original_text":"MIXED   case   TEXT","converted_text":"Mixed   Case   Text"}
]

Explanation

All spaces are preserved exactly, including leading, trailing, and repeated separators.

Example 3

Input

UserContent:
| content_id | content_text    |
|------------|-----------------|
| 21         |                 |
| 22         | a b c           |
| 23         |    x   y        |

Output

[
  {"content_id":21,"original_text":"","converted_text":""},
  {"content_id":22,"original_text":"a b c","converted_text":"A B C"},
  {"content_id":23,"original_text":"   x   y   ","converted_text":"   X   Y   "}
]

Explanation

Empty strings stay empty, and single-letter words are capitalized correctly.

Constraints

1 <= number of rows in UserContent <= 4000
content_id is unique
1 <= content_id <= 1000000000
0 <= length(content_text) <= 180
content_text contains only English letters and spaces
Words are separated by one or more spaces
Preserve all spaces exactly in the output
Return output columns exactly as specified
Final output must be sorted by content_id ascending
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with required columns