# Can Kibana group events around a common id and perform statistics on the group, then plot it?

I usually use Kibana (as a basic user) with a flow of independent timed events. I then make some graphs on the evolution or statistics of a population in a specific timeframe.

I now face a problem I do not know how to approach: a set of timed events, but with a common identifier and a common date that groups them into clusters and I would like to make statistics on these clusters.

To take an example, consider the following set of data ("some date" is a random date)

``````[
{
"id": 1,
"age": 20,
"nice": true,
"sent": "date1"
},
{
"id": 1,
"age": 25,
"nice": false,
"sent": "date1"
},
{
"id": 2,
"age": 20,
"nice": false,
"sent": "date2"
},
{
"id": 2,
"age": 30,
"nice": false,
"sent": "date2"
}
]
``````

My goal is to have an evolution of the average of "nice" people by `id` (or by `sent`). This requires to first group the data by `id`, then to calculate the average by group, and then to plot this average over time (the group is located at `sent`).

Is Kibana able to do something like that?

My backup plan is to mak the calculations upstream and sent the results to Kibana but I would like to avoid this because I may want to show some other statistics (say, the median instead of the average - this will require all data to be updated in Kibana from the upstream backend)

In Lens you can break your chart by `id` and chart over time (`sent`) any metric (`median`, `average`, etc) and include filters to only render the data you want.

I've created an index and the associated Data View with some data following your spec:

``````DELETE discuss-345613

PUT discuss-345613
{
"mappings": {
"properties": {
"id": {"type": "keyword"},
"age": {"type": "integer"},
"nice": {"type": "boolean"},
"sent": {"type": "date"}
}
}
}

# 10-24
POST discuss-345613/_bulk
{ "index": {} }
{ "id": 1, "age": 20, "nice": true, "sent": "2023-10-24"}
{ "index": {} }
{ "id": 1, "age": 25, "nice": false, "sent": "2023-10-24"}
{ "index": {} }
{ "id": 2, "age": 20, "nice": true, "sent": "2023-10-24"}
{ "index": {} }

# 10-25
POST discuss-345613/_bulk
{ "index": {} }
{ "id": 1, "age": 20, "nice": true, "sent": "2023-10-25"}
{ "index": {} }
{ "id": 1, "age": 30, "nice": false, "sent": "2023-10-25"}
{ "index": {} }
{ "id": 2, "age": 20, "nice": true, "sent": "2023-10-25"}
{ "index": {} }
{ "id": 2, "age": 30, "nice": false, "sent": "2023-10-25"}
{ "index": {} }
{ "id": 3, "age": 30, "nice": true, "sent": "2023-10-25"}

# 10-26
POST discuss-345613/_bulk
{ "index": {} }
{ "id":1, "age": 25, "nice": true, "sent": "2023-10-26"}
{ "index": {} }
{ "id": 2, "age": 35, "nice": true, "sent": "2023-10-26"}
{ "index": {} }
{ "id":2, "age": 23, "nice": true, "sent": "2023-10-26"}
{ "index": {} }
{ "id": 3, "age": 35, "nice": true, "sent": "2023-10-26"}
{ "index": {} }
{ "id":3, "age": 20, "nice": true, "sent": "2023-10-26"}
{ "index": {} }
{ "id": 3, "age": 35, "nice": true, "sent": "2023-10-26"}

# Data view using sent as time field
POST kbn:/api/data_views/data_view
{
"data_view": {
"title": "discuss-345613",
"timeFieldName": "sent"
}
}
``````

Then, in Lens, it is straightforward to add a filter for `nice: true` and a breakdown for the top 10 values of `id` (you can also use intervals or any other filter).

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