# 'Needs ID' pile, and identifications

**URL:** <https://forum.inaturalist.org/t/needs-id-pile-and-identifications/26904>\
**Category:** General\
**Created:** [October 3, 2021, 11:45pm UTC](https://forum.inaturalist.org/t/needs-id-pile-and-identifications/26904 "2021-10-03T23:45:26Z")\
**Posts on this page:** 1\
**Showing post:** 610

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**Author:** ![pisum](https://avatars.discourse-cdn.com/v4/letter/p/91b2a8/32.png) [@pisum](https://forum.inaturalist.org/u/pisum)\
**Post date:** [September 7, 2022, 10:30pm UTC](https://forum.inaturalist.org/t/needs-id-pile-and-identifications/26904/610 "2022-09-07T22:30:21Z")

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i don’t think normal folks have access to get that level of information effectively. via /v1/observations in the API, we have the ability to use an `identified=true` or `=false` parameter, which can help distinguish between observations with 0 identifications and with \>0 identifications. theoretically, you could use some combination of `identifications=some_agree`, `=most_agree`, and =`most_disagree` to further separate observations with \>1 identifications.

if you just want to get a rough idea of percents in each of your categories, /v1/observations does provide an identification count per observation, and you can do a [random sample of observations](https://forum.inaturalist.org/t/community-taxon-algorithm-tweaks/28583/51).

here’s the distribution for a random sample of n=2000 that i just pulled:

| # of ids | # of obs | % of total |
| --- | --- | --- |
| 0 | 49 | 2.5% |
| 1 | 554 | 27.7% |
| 2 | 872 | 43.6% |
| 3 | 350 | 17.5% |
| 4 | 113 | 5.7% |
| 5 | 37 | 1.9% |
| 6 | 20 | 1.0% |
| 7 | 4 | 0.2% |
| 8 | 1 | 0.1% |
| **total** | **2000** | **100.0%** |

just to see if the above numbers are reasonable, here are the actual counts for `identified=true` and `=false`:

| identified | # of obs | % of total |
| --- | --- | --- |
| [false](https://api.inaturalist.org/v1/observations?per_page=0&identified=false) | 3,285,772 | 2.6% |
| [true](https://api.inaturalist.org/v1/observations?per_page=0&identified=true) | 125,247,127 | 97.4% |
| **total** | **128,532,899** | **100.0%** |

`identifications=false` at 2.6% roughly matches 0 identifications at 2.5% percent. so that seems to indicate that the figures in the first table should be reasonable.

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