Question 1

How do I convert CSV to a Python dictionary?

Accepted Answer

Paste your CSV (with a header row) into the input, choose 'list of dicts' as the output style and click Convert. Each data row becomes a dict using the header names as keys. Numbers, booleans and None are auto-detected.

Question 2

What output styles are supported?

Accepted Answer

Four styles: a plain Python list of dicts, a @dataclass definition plus instances, a typing.NamedTuple definition, and a pandas DataFrame constructor (pd.DataFrame([...])). All include inferred type hints.

Question 3

How are types inferred from CSV cells?

Accepted Answer

Every non-empty value in a column is tested: integers and decimals become int or float, true/false/yes/no become bool, empty strings become None, ISO dates stay str, and anything else stays str. A column is only typed as int/float/bool if every sampled value matches.

Question 4

Is my CSV data uploaded anywhere?

Accepted Answer

No. Parsing and code generation run entirely in your browser. Your CSV never leaves your device.