# Vega-lite, create a forecast similar as lens visualization **URL:** \ **Category:** Kibana\ **Tags:** vega\ **Created:** [January 20, 2023, 8:42am UTC](https://discuss.elastic.co/t/vega-lite-create-a-forecast-similar-as-lens-visualization/323572 "2023-01-20T08:42:01Z")\ **Posts on this page:** 9\ **Page:** 1
**Author:** ![plus](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/plus/32/97297_2.png) [@plus](https://discuss.elastic.co/u/plus)\ **Post date:** [January 20, 2023, 8:42am UTC](https://discuss.elastic.co/t/vega-lite-create-a-forecast-similar-as-lens-visualization/323572/1 "2023-01-20T08:42:01Z")
Hello everyone I have a question with vega-lite and I don't know how to follow up. I checked on lens I can see data from last 2 hours and next 4 hours on the same graphic (a forecast job has been launched previously to get that data), for example ![Lens - mixed old and forecast values](https://us1.discourse-cdn.com/elastic/original/3X/c/7/c7984b7376089e026b6612da9805f399be44d2d9.png) but on vega lite if I try to do the same, using the request that is used on Lens, I´m not able to replicate that graphic (lens for aggs use percentiles and I use terms value) **this is the Lens request** ```auto { "aggs": { "0": { "date_histogram": { "field": "timestamp", "fixed_interval": "10m", "time_zone": "Europe/Madrid", "extended_bounds": { "min": 1674194400000, "max": 1674223519676 } }, "aggs": { "1": { "percentiles": { "field": "actual", "percents": [ 50 ] } }, "2": { "percentiles": { "field": "forecast_prediction", "percents": [ 50 ] } } } } }, "size": 0, "fields": [ { "field": "bucket_influencers.timestamp", "format": "date_time" }, { "field": "earliest_record_timestamp", "format": "date_time" }, { "field": "exponential_average_calculation_context.latest_timestamp", "format": "date_time" }, { "field": "forecast_create_timestamp", "format": "date_time" }, { "field": "forecast_end_timestamp", "format": "date_time" }, { "field": "forecast_expiry_timestamp", "format": "date_time" }, { "field": "forecast_start_timestamp", "format": "date_time" }, { "field": "last_data_time", "format": "date_time" }, { "field": "latest_empty_bucket_timestamp", "format": "date_time" }, { "field": "latest_record_time_stamp", "format": "date_time" }, { "field": "latest_record_timestamp", "format": "date_time" }, { "field": "latest_result_time_stamp", "format": "date_time" }, { "field": "latest_sparse_bucket_timestamp", "format": "date_time" }, { "field": "log_time", "format": "date_time" }, { "field": "model_size_stats.log_time", "format": "date_time" }, { "field": "model_size_stats.timestamp", "format": "date_time" }, { "field": "timestamp", "format": "date_time" } ], "script_fields": {}, "stored_fields": [ "*" ], "runtime_mappings": {}, "_source": { "excludes": [] }, "query": { "bool": { "must": [], "filter": [ { "bool": { "should": [ { "match_phrase": { "partition_field_value": "hidden text" } } ], "minimum_should_match": 1 } }, { "range": { "timestamp": { "format": "strict_date_optional_time", "gte": "2023-01-20T06:00:00.000Z", "lte": "2023-01-20T14:05:19.676Z" } } } ], "should": [], "must_not": [] } } } ``` **This is my current vega lite code** (index field and partition\_field\_value have been modified due to are sensible information) - As I removed _"%context%": true and "%timefield%": "timestamp"_ under URL, time filter doesn't works and it's defined the datetime under query - bool ... ```auto { "$schema": "https://vega.github.io/schema/vega-lite/v5.json", "title": "push notifications", "data": { "url": { "index": ".ml-anomalies-cxx-xxx_xxx_xxx_movil", "body": { "_source": ["actual", "forecast_prediction", "timestamp"], "size": 0, "query": { "bool": { "must": [{"range": { "timestamp": { "gte": "2023-01-20T00:30:00.000Z", "lte": "2023-01-20T20:00:00.000Z", "format": "strict_date_optional_time"} }}] } }, "aggs": { "bydate": { "date_histogram": { "field": "timestamp", "fixed_interval": "1m", "min_doc_count": 1 }, "aggs": { "elvalue": {"terms": {"field": "actual","size": 1}}, "forecast": {"terms": {"field": "forecast_prediction","size": 1}} } } } } }, "format": {"property": "aggregations.bydate.buckets"} }, "enconding": { "x": { "axis": {"format": "hoursminutes"}, "field": "key", "title": "asdf", "type": "temporal" } }, "transform": [ {"flatten": ["elvalue.buckets"],"as": ["currentvalue"]}, {"flatten": ["forecast.buckets"],"as": ["futurvalue"]} ], "layer": [ { "mark": { "interpolate": "monotone", "opacity": 0.5, "tooltip": true, "type": "line" }, "encoding": { "color": { "type": "point", "value": "orange"}, "y": { "field": "futurvalue.key", "type": "quantitative" }, "x": { "field": "key", "format": "hoursminutes", "title": "sfasdfasdf", "type": "temporal" }, "tooltip": [ {"field":"key", "type": "temporal", "format": "%d/%m/%y %H:%M", "title": "fecha"}, {"field":"futurvalue.key", "type": "quantitative", "format": ",.2r", "title": "valor forecast"} ] } }, { "mark": { "interpolate": "monotone", "opacity": 1, "tooltip": true, "type": "line" }, "encoding": { "color": { "type": "point", "value": "black"}, "y": { "field": "currentvalue.key", "type": "quantitative", "title": "valores" }, "x": { "field": "key", "format": "%d/%m/%y %H:%M", "title": "", "type": "temporal" }, "tooltip": [ {"field":"key", "type": "temporal", "format": "%d/%m/%y %H:%M", "title": "fecha"}, {"field":"currentvalue.key", "type": "quantitative", "format": ",.2r", "title": "valor_actual"} ] } } ] } ``` ![vega lite graphic, not forecast on x-axis](https://us1.discourse-cdn.com/elastic/original/3X/d/8/d88221c16bc189e7a04ed5ba59789699315ca07a.png) What I'm doing wrong? or isn't possible to create a graphic with forecast data on vega-lite? Thank you very much. ---
**Author:** ![plus](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/plus/32/97297_2.png) [@plus](https://discuss.elastic.co/u/plus)\ **Post date:** [January 20, 2023, 1:33pm UTC](https://discuss.elastic.co/t/vega-lite-create-a-forecast-similar-as-lens-visualization/323572/2 "2023-01-20T13:33:46Z")
Hello I would to add more information, as you can see the response of query shows data 3 hours next the current time. why if response shows the forecast values, example on **"key\_as\_string": "2023-01-20T16:00:00.000Z",** , these data is not printed on the graphic? ```auto { "took": 32, "timed_out": false, "_shards": { "total": 1, "successful": 1, "skipped": 0, "failed": 0 }, "hits": { "total": 409, "max_score": 1, "hits": [ { "_index": ".ml-xxxxxxvil", "_id": "xxxxxxxx_forecast_kZF7wIUBHKUCZOXpiX77_1674216180000_60_0_-142261168984546803792043607818611473090_26", "_score": 1, "_source": { "forecast_prediction": 194.23115257143547, "forecast_id": "kZF7wIUBHKUCZOXpiX77", "timestamp": 1674216180000 } }, { "_index": ".xxxxxx_movil", "_id": "xxxxxxxxorecast_kZF7wIUBHKUCZOXpiX77_1674216240000_60_0_-142261168984546803792043607818611473090_26", "_score": 1, "_source": { "forecast_prediction": 194.30067612773456, "forecast_id": "kZF7wIUBHKUCZOXpiX77", "timestamp": 1674216240000 } }, { "_index": ".xxxxxxxxmovil", "_id": "rxxxxxxxxxorecast_kZF7wIUBHKUCZOXpiX77_1674216300000_60_0_-142261168984546803792043607818611473090_26", "_score": 1, "_source": { "forecast_prediction": 194.3705109907569, "forecast_id": "kZF7wIUBHKUCZOXpiX77", "timestamp": 1674216300000 } }, { "_index": ".xxxxxxml_rvia_movil", "_id": "rxxxxxxxforecast_kZF7wIUBHKUCZOXpiX77_1674216360000_60_0_-142261168984546803792043607818611473090_26", "_score": 1, "_source": { "forecast_prediction": 194.43923830329265, "forecast_id": "kZF7wIUBHKUCZOXpiX77", "timestamp": 1674216360000 } } ] }, "aggregations": { "bydate": { "buckets": [ { "key_as_string": "2023-01-20T12:00:00.000Z", "key": 1674216000000, "doc_count": 31, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 20 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 1223, "doc_count": 2 } ] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 164.99888903776827, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 608.3046952476328, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T12:10:00.000Z", "key": 1674216600000, "doc_count": 30, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 20 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 8, "buckets": [ { "key": 161, "doc_count": 1 } ] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 159.83954788767812, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 596.8168512280893, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T12:20:00.000Z", "key": 1674217200000, "doc_count": 30, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 20 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 7, "buckets": [ { "key": 222, "doc_count": 2 } ] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 153.18075168672294, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 580.6921859353731, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T12:30:00.000Z", "key": 1674217800000, "doc_count": 30, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 20 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 7, "buckets": [ { "key": 191, "doc_count": 2 } ] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 145.48343529131273, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 567.0365202349564, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T12:40:00.000Z", "key": 1674218400000, "doc_count": 30, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 20 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 8, "buckets": [ { "key": 205, "doc_count": 2 } ] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 137.2202102610587, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 552.6512883019194, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T12:50:00.000Z", "key": 1674219000000, "doc_count": 30, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 20 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 7, "buckets": [ { "key": 185, "doc_count": 2 } ] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 128.8304877247488, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 539.1988044604327, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T13:00:00.000Z", "key": 1674219600000, "doc_count": 30, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 20 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 6, "buckets": [ { "key": 167, "doc_count": 3 } ] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 120.64197367192736, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 520.9446034231962, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T13:10:00.000Z", "key": 1674220200000, "doc_count": 30, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 20 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 8, "buckets": [ { "key": 164, "doc_count": 2 } ] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 112.95890595390381, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 19, "buckets": [ { "key": 507.99144403662604, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T13:20:00.000Z", "key": 1674220800000, "doc_count": 13, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 11 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 1, "buckets": [ { "key": 146, "doc_count": 1 } ] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 10, "buckets": [ { "key": 112.23011188337635, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 10, "buckets": [ { "key": 506.7234591587502, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T13:30:00.000Z", "key": 1674221400000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 128.7650045336486, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 519.314593173476, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T13:40:00.000Z", "key": 1674222000000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 123.82139518074963, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 509.9725080929261, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T13:50:00.000Z", "key": 1674222600000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 119.8501076686533, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 502.3113416765282, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T14:00:00.000Z", "key": 1674223200000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 116.72710114890398, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 496.0677985400145, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T14:10:00.000Z", "key": 1674223800000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 114.57622338643061, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 487.9892786989142, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T14:20:00.000Z", "key": 1674224400000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 113.5289721170205, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 483.6799850660867, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T14:30:00.000Z", "key": 1674225000000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 113.44854252019219, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 481.0127164962853, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T14:40:00.000Z", "key": 1674225600000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 113.79774419133545, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 480.296730108848, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T14:50:00.000Z", "key": 1674226200000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 115.18188181279268, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 480.18356329421886, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T15:00:00.000Z", "key": 1674226800000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 117.18125657118058, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 481.2100658168749, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T15:10:00.000Z", "key": 1674227400000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 119.32010108137749, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 480.94800651482535, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T15:20:00.000Z", "key": 1674228000000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 121.12551323481631, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 481.00487322395907, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T15:30:00.000Z", "key": 1674228600000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 122.46981650637355, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 481.0449446205719, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T15:40:00.000Z", "key": 1674229200000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 123.89502309183081, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 481.1469703144203, "doc_count": 1 } ] } }, { "key_as_string": "2023-01-20T15:50:00.000Z", "key": 1674229800000, "doc_count": 10, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 10 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 126.01997790680613, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 9, "buckets": [ { "key": 485.7819880609802, "doc_count": 1 } ] } }, { **"key_as_string": "2023-01-20T16:00:00.000Z",** "key": 1674230400000, "doc_count": 5, "elfuturelower": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 0, "doc_count": 5 } ] }, "elretardervalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [] }, "elfuturvalue": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 4, "buckets": [ { "key": 129.4634341686073, "doc_count": 1 } ] }, "elfutureupper": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 4, "buckets": [ { "key": 487.79840132163906, "doc_count": 1 } ] } } ] } } } ``` ![Screenshot 2023-01-20 at 14.22.05](https://us1.discourse-cdn.com/elastic/original/3X/6/b/6b5c569eee0b642ba593d913a70b47df018ed803.png) Thanks for your help ---
**Author:** ![plus](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/plus/32/97297_2.png) [@plus](https://discuss.elastic.co/u/plus)\ **Post date:** [January 24, 2023, 1:42pm UTC](https://discuss.elastic.co/t/vega-lite-create-a-forecast-similar-as-lens-visualization/323572/3 "2023-01-24T13:42:54Z")
Hello, anyone could help me? Thanks ---
**Author:** ![Marco\_Liberati](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/marco_liberati/32/82953_2.png) [@Marco\_Liberati](https://discuss.elastic.co/u/Marco_Liberati)\ **Post date:** [January 25, 2023, 10:34am UTC](https://discuss.elastic.co/t/vega-lite-create-a-forecast-similar-as-lens-visualization/323572/4 "2023-01-25T10:34:11Z")
Hi @plus welcome to the Kibana community. in Lens when a time shift is enabled, there's a response manipulation on top of the raw ES response, what is probably why it's not that easy to reproduce in Vega lite. ---
**Author:** ![plus](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/plus/32/97297_2.png) [@plus](https://discuss.elastic.co/u/plus)\ **Post date:** [January 25, 2023, 11:18am UTC](https://discuss.elastic.co/t/vega-lite-create-a-forecast-similar-as-lens-visualization/323572/5 "2023-01-25T11:18:43Z")
> [@Marco\_Liberati](#): > > in Lens when a time shift is enabled, there's a response manipulation on top of the raw ES response, what is probably why it's not that easy to reproduce in Vega lite. But could there a way to reproduce in vega lite? Do you know someone whom could help me to deploy it? Thanks ---
**Author:** ![plus](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/plus/32/97297_2.png) [@plus](https://discuss.elastic.co/u/plus)\ **Post date:** [January 31, 2023, 12:11pm UTC](https://discuss.elastic.co/t/vega-lite-create-a-forecast-similar-as-lens-visualization/323572/6 "2023-01-31T12:11:47Z")
Good morning @Marco_Liberati do you have any update if is possible to do this forecast visualization with VegaLite? Thanks. ---
**Author:** ![plus](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/plus/32/97297_2.png) [@plus](https://discuss.elastic.co/u/plus)\ **Post date:** [February 15, 2023, 9:53am UTC](https://discuss.elastic.co/t/vega-lite-create-a-forecast-similar-as-lens-visualization/323572/7 "2023-02-15T09:53:46Z")
any update? thanks ---
**Author:** ![Marco\_Liberati](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/marco_liberati/32/82953_2.png) [@Marco\_Liberati](https://discuss.elastic.co/u/Marco_Liberati)\ **Post date:** [February 15, 2023, 10:05am UTC](https://discuss.elastic.co/t/vega-lite-create-a-forecast-similar-as-lens-visualization/323572/8 "2023-02-15T10:05:12Z")
Hi @plus will have a look at this next week as it's not trivial and requires some time to re-align the shifted data in Vega via transforms. ---
**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\ **Post date:** [March 15, 2023, 10:05am UTC](https://discuss.elastic.co/t/vega-lite-create-a-forecast-similar-as-lens-visualization/323572/9 "2023-03-15T10:05:53Z")
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