Hey everyone,
I’ve been working on a small side project and wanted to share it here in case it’s useful for others dealing with messy data.
It’s a no-code CSV pipeline tool, but the part I’ve been focusing on recently is a “data health” layer that tries to answer a simple question: how bad is this dataset before I start working on it?
For each dataset (and each column), it surfaces things like:
- % of missing values
- outliers
- skewness
- uniqueness
- data type consistency
You can also drill into individual columns to see why something looks off, instead of manually scanning or writing quick checks.
The general idea behind the tool is:
- every transformation creates a versioned snapshot
- you can go back to any previous step
- you don’t lose the original dataset
- everything is visual / no-code
I built it mostly because I kept repeating the same initial checks in pandas and wanted a faster way to get a feel for the data before doing anything serious.
Not trying to replace code-based workflows just more like speeding up the early “what am I dealing with?” phase.
Curious how others approach this part of analysis, and whether something like this would actually fit into your workflow or just feel unnecessary.
submitted by /u/Woland96
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