Sometimes you don't need the data — you just need to know what's in a Parquet file: the column names, their data types, and how it's structured. The web viewer shows you the full schema the moment you open a .parquet file, without writing a line of code and without uploading anything.
See every column and type at a glance
Open your file and the viewer lists each column with its data type, color-coded by kind — integers, floats, strings, booleans, dates and timestamps, binary, and nested structs. You can see the column order, the logical types, and the overall shape of the dataset immediately.
This is the fast way to answer questions like “what columns does this file have?”, “is this column an int or a string?”, or “does the schema match what I expected?” — without loading the data into pandas first.
Why inspect the schema first?
- Confirm structure before you write a query or a pipeline against the file.
- Debug type mismatches — spot a column that's text when it should be a number.
- Understand an unfamiliar dataset someone handed you, or one you downloaded.
- Check a remote file by URL or S3 without downloading the whole thing.
Beyond the schema
Once you can see the columns, the viewer lets you go further in the same place: browse the rows, profile a column's distribution, filter and sort, run SQL, and convert to CSV, JSON, or another Parquet file. To learn more about the format itself, see what is a Parquet file.
