Messy data, cleaned on upload
Enable cleaning on a project and GoPie standardises every upload as it lands: trimming whitespace, fixing column names, standardising values and adding code dictionaries. So analysis starts from clean ground.
| St_Name | BEDS/1K(2024 ) |
|---|---|
| " Florida " | 2.6 |
| NewJersey | NA |
| Georgia | 2.4 |
Auto-applied · you review & tweak any step
| state_name | state_code | beds_per_1k_2024 |
|---|---|---|
| Florida | FL | 2.6 |
| New Jersey | NJ | null |
| Georgia | GA | 2.4 |
STATE_CODE ADDED FROM STANDARD DICTIONARY
01 · What you get
Built to do the work for you
Cleaned automatically
Whitespace, column names and value formats fixed before anyone asks a question.
Predefined codebooks
Standardise against codebooks like state codes, and add the code as its own column.
Data plus reports
Add official reports as context so answers cite the source behind the numbers.
02 · How it works
Three steps, no setup
- 01
Upload as is
Bring messy public data straight from the source. No manual prep first.
- 02
GoPie standardises it
It trims, renames, types and maps values to standard codes on the way in.
- 03
Analyse with confidence
Clean, joined data that answers questions across files without reconciliation.
Every step is auto-applied but visible, so you can review and tweak each one before the data lands.