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PERCENTRANK.INC in Google Sheets: Inclusive Ranks and Interior Estimation

Statistical Intermediate Google Sheets

Calculate inclusive Google Sheets percentage ranks, inspect an interior estimated value and keep precision and out-of-range questions explicitly scoped.

Verification status: See the evidence and test scope described in this guide. How formula examples are checked

Quick answer: PERCENTRANK.INC(data,value,[significant_digits]) returns an inclusive percentage rank. Its reference describes estimation for a target not observed in the data; the worked estimation below stays strictly between two numeric observations.

Availability and version history

  • Introduced: first introduction date is not established by the reviewed official history; no desktop release number is inferred.
  • Availability: documented in the rolling Google Sheets service; this guide uses the web worksheet workflow.
  • Checked: October 14, 2026; official PERCENTRANK.INC reference. Documentation and independent calculations, with no native Sheets execution or wider client certification.

Syntax and scope

=PERCENTRANK.INC(data,value,[significant_digits])

Data and value are required. The optional significant-digits argument defaults to 3. Google describes a rank from 0 to 1 inclusive. Its estimation note is broad, but this guide does not use it to promise extrapolation beyond the smallest or largest input.

The independent model for distinct ordered numeric data assigns rank (position-1)/(n-1) and interpolates an interior position between adjacent values. The compact reference does not print that equation or a full precision algorithm; all displayed ranks below are exact terminating decimals.

PERCENTRANK has a separate reference that explicitly documents #N/A for absent values. Keep the function names and their sourced behavior distinct.

Example 1: inclusive endpoint and observed-value controls

Enter 10,20,40,80,160 in A2:A6:

Formula Independently expected rank
=PERCENTRANK.INC(A2:A6,10) 0
=PERCENTRANK.INC(A2:A6,20) 0.25
=PERCENTRANK.INC(A2:A6,40) 0.5
=PERCENTRANK.INC(A2:A6,80) 0.75
=PERCENTRANK.INC(A2:A6,160) 1

The smallest and largest observations use the inclusive endpoints in this model. These fractions can be displayed as 0%,25%,50%,75%,100% without multiplying the underlying numeric results.

The rank of 80 is not 80/160=0.5. A percentage rank describes position within the distribution rather than a fraction of the maximum magnitude.

Example 2: estimate the rank of an interior target

=PERCENTRANK.INC(A2:A6,30)

Expected result: 0.375, or 37.5%. The target is halfway between 20 and 40, whose modeled ranks are 0.25 and 0.5. Halfway between those ranks is 0.25+0.5*(0.5-0.25)=0.375.

The empirical fraction of observations strictly below 30 is instead 2/5=0.4. That is a different definition. Do not replace an interpolated percentage rank with a count divided by the total unless the reporting requirement asks for that count-based measure.

For target 60, halfway between 40 and 80, the same model gives 0.625. The value gaps are unequal, so interpolation depends on adjacent magnitudes as well as their positions.

Advanced example: a cutoff comparison with visible arithmetic

Put target values 20,30,40,60,80 in C2:C6. Use:

=PERCENTRANK.INC($A$2:$A$6,C2)

Fill down. The independently expected ranks are 0.25,0.375,0.5,0.625,0.75. A rule selecting ranks at least 0.6 includes 60 and 80 among these targets.

The targets in C are evaluation values; adding them to the reference population A would change the question. Keep the benchmark range separate from the records being scored.

Advanced example: changing the comparison group

Append 320 to the original dataset and rank 80 against A2:A7. Its position remains fourth, but the denominator changes from four to five. Expected rank becomes 0.6.

Duplicating or extending a benchmark should therefore be treated as a data change, not a presentation change. Record which range and reporting period supplied the reference population.

For the original five-value fixture, =PERCENTILE(A2:A6,0.375) has independently expected value 30 under the inclusive interpolation model. This is a useful matched-fixture check, not proof of an exact inverse for all ties, shortened ranks or floating-point values.

Precision, errors and limits

The optional four-digit control =PERCENTRANK.INC(A2:A6,30,4) still gives expected 0.375 in this exact-decimal fixture. The source does not establish a complete rounding-versus-truncation rule, so no boundary-sensitive precision comparison is certified.

Do not import PERCENTRANK’s documented nonpositive-precision fallback into PERCENTRANK.INC without separate evidence. Native behavior for targets beyond the data endpoints, duplicate ranks, singletons, empty ranges, mixed types and error inputs remains unverified. A scoped example is more useful than assigning unsupported error labels to every case.

References and verification

Examples use fictional data, English function names and comma argument separators. Expected results are independent calculations or explicitly documented rules, not native Sheets captures. Check spreadsheet locale when reproducing punctuation-sensitive formulas.