Examples
Examples
Try the starting example
- JSON Services [ID,expected records,exported records]
- [["mail",100,98],["photos",200,200],["notes",30,0]]
- Export discrepancies [ID,expected−exported]
- [["mail",2],["photos",0],["notes",30]]
- Services below expected count
- ["mail","notes"]
- Count coverage fraction
- 0.90303
Try another scenario
- JSON Services [ID,expected records,exported records]
- [["mail",100,100],["photos",200,200],["notes",30,20]]
- Export discrepancies [ID,expected−exported]
- [["mail",0],["photos",0],["notes",10]]
- Services below expected count
- ["notes"]
- Count coverage fraction
- 0.969697
Calculation method
Calculation method
Export discrepancies [ID,expected−exported]
J([[r[0],r[1]-r[2]] for r in a])
Services below expected count
J([r[0] for r in a if r[2]<r[1]])
Count coverage fraction
sum(min(r[1],r[2]) for r in a)/sum(r[1] for r in a)
Symbols and units
- a
- JSON Services [ID,expected records,exported records]
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Calculation steps and notation
sum(list) adds all entries in the list.
Assumptions & limits
Assumptions & limits
- Count-level manifest comparison only, nonnegative integers and positive expected total. Matching counts do not establish identity or export fidelity. Supported limits: All numeric inputs must be finite. Only the explicitly described mathematical scenario is supported.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.