Missing values in a CSV are not always empty cells. They hide as 'N/A', 'null', '-', '0' or a single space. If you only count blanks, you underestimate the problem and your averages, joins and charts quietly go wrong.
Plumb is built on a simple idea: the data your business runs on should be trustworthy before anyone draws conclusions from it. Cleaning, checking and reshaping data should not need macros, scripts or a weekend. Plumb keeps your files private, shows every change it proposes, and lets you approve fixes instead of hunting for problems by hand.
How Plumb helps: Data quality audit
Plumb's data quality audit profiles every column: how many values are empty, how many are placeholder values like 'N/A' or 'unknown', and which rows are affected. You get a completeness score per column and can decide to fill, flag or drop.
How It Works
Count true blanks first, then hunt for disguised ones.
- In Excel: select the data, press F5 > Special > Blanks to highlight every empty cell.
- Count blanks per column with =COUNTBLANK(A2:A1000).
- Find disguised blanks with =COUNTIF(A2:A1000, "N/A") and similar checks for 'null', '-' and spaces.
- In Python: pd.read_csv('file.csv', na_values=['N/A','null','-','']).isna().sum() gives missing counts per column.
- Decide per column: fill with a default, fill from another source, mark as unknown, or drop the row.
- In Plumb: upload the CSV, open the audit, and see missing and placeholder values per column with one-click actions.
Where This Helps
Lead lists
Find contacts missing an email or phone before a campaign goes out.
Sales data
Spot orders with no amount or region that would skew totals.
Research data
Measure completeness before deciding whether a dataset is usable.
Try Plumb in early access
Plumb is in early access. Join the waitlist on tryplumb.pro to get an invite. Early access covers Excel (.xlsx), CSV and JSON files, and we are adding more sources as people ask for them. Your files are processed privately and are never used to train models.
Know what is missing before it matters
Now you have a repeatable way to do it, by hand or with Plumb. Join the waitlist and tell us what your data looks like; we read every reply.
Join the waitlist