# Kibana Scatter Plot Graph - Lines in the middle **URL:** \ **Category:** Kibana\ **Tags:** vega\ **Created:** [July 5, 2021, 11:22pm UTC](https://discuss.elastic.co/t/kibana-scatter-plot-graph-lines-in-the-middle/277887 "2021-07-05T23:22:54Z")\ **Posts on this page:** 4\ **Page:** 1
**Author:** ![momo1104](https://avatars.discourse-cdn.com/v4/letter/m/e5b9ba/32.png) [@momo1104](https://discuss.elastic.co/u/momo1104)\ **Post date:** [July 5, 2021, 11:22pm UTC](https://discuss.elastic.co/t/kibana-scatter-plot-graph-lines-in-the-middle/277887/1 "2021-07-05T23:22:54Z")
Hi All, I'm trying to draw 2 black lines in a cross manner right in the middle of the graph. Any suggestions? I'll post a snap and the code below. ![image](https://us1.discourse-cdn.com/elastic/original/3X/c/3/c38dd7e508ed8b3fde7afe577de4fa5d2174b3e5.png) ```auto { "$schema": "https://vega.github.io/schema/vega-lite/v5.json", "description": "A scatterplot showing...", "data": { "values": [ { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 10:55.755623", "source_ip": "1.10.252.196", "source_host": "hacker_17", "destination_ip": "172.31.65.89", "destination_host": "printer_17", "flow_bytes/s": 5006827.492, "flow_byte_mb": "5.01mb:", "class": "neptune", "severity": "high", "flow_packets": 11379.15339, "service": 0, "flag": "rej", "threat": 91, "certainty": 48 }, { "duration": 898, "protocol_type": "tcp", "timestamp": "2018-12-01 11:02:52.858157", "source_ip": "1.10.252.196", "source_host": "hacker_17", "destination_ip": "172.31.65.89", "destination_host": "printer_17", "flow_bytes/s": 2674.703056, "flow_byte_mb": "2.67kb", "class": "apache_2", "severity": "low", "flow_packets": 27.63122992, "service": "http", "flag": "rstr", "threat": 15, "certainty": 14 }, { "duration": 0, "protocol_type": "udp", "timestamp": "2018-12-01 10:51.852499.", "source_ip": "1.165.16.250", "source_host": "hacker_18", "destination_ip": "172.31.67.67", "destination_host": "smart_phone_120", "flow_bytes/s": 82274.24749, "flow_byte_mb": "82.27kb", "class": "snmpgetattack", "severity": "low", "flow_packets": 2675.585284, "service": "private", "flag": "sf", "threat": 32, "certainty": 31 }, { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 11:02.890213", "source_ip": "1.165.16.250", "source_host": "hacker_18", "destination_ip": "172.31.67.67", "destination_host": "smart_phone_120", "flow_bytes/s": 284211.726, "flow_byte_mb": "284.21kb", "class": "normal", "severity": "medium", "flow_packets": 651.2642668, "service": "http", "flag": "sf", "threat": 52, "certainty": 51 }, { "duration": 0, "protocol_type": "udp", "timestamp": "2018-12-01 10:52.941151", "source_ip": "1.170.218.162", "source_host": "hacker_18", "destination_ip": "172.31.65.8", "destination_host": "printer_14", "flow_bytes/s": 1349382.811, "flow_byte_mb": "1.35mb", "class": "normal", "severity": "critical", "flow_packets": 3066.779115, "service": "private", "flag": "sf", "threat": 85, "certainty": 67 }, { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 10:59.942030", "source_ip": "1.170.218.162", "source_host": "hacker_18", "destination_ip": "172.31.65.8", "destination_host": "printer_14", "flow_bytes/s": 2627179.365, "flow_byte_mb": "2.63mb", "class": "normal", "severity": "high", "flow_packets": 5970.862193, "service": "http", "flag": "sf", "threat": 0, "certainty": 1 }, { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 10:53.569712", "source_ip": "1.55.176.28", "source_host": "hacker_19", "destination_ip": "172.31.69.11", "destination_host": "smart_phone_144", "flow_bytes/s": 981333333.3, "flow_byte_mb": "981.33mb", "class": "neptune", "severity": "critical", "flow_packets": 666666.6667, "service": "ftp_data", "flag": "sf", "threat": 98, "certainty": 97 }, { "duration": 4, "protocol_type": "tcp", "timestamp": "2018-12-01 10:59.778963", "source_ip": "1.55.176.28", "source_host": "hacker_19", "destination_ip": "172.31.69.11", "destination_host": "smart_phone_144", "flow_bytes/s": 2588681.931, "flow_byte_mb": "2.59mb", "class": "guess_passwd", "severity": "medium", "flow_packets": 5931.901768, "service": "pop_3", "flag": "sf", "threat": 43, "certainty": 42 }, { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 10:53.986321", "source_ip": "101.96.116.77", "source_host": "hacker_1", "destination_ip": "172.31.64.79", "destination_host": "fax_1", "flow_bytes/s": 1472000000, "flow_byte_mb": "1472.00mb", "class": "guess_passwd", "severity": "critical", "flow_packets": 1000000, "service": "telnet", "flag": "sf", "threat": 98, "certainty": 99 }, { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 10:53.112587", "source_ip": "101.96.116.77", "source_host": "hacker_1", "destination_ip": "172.31.65.90", "destination_host": "fax_1", "flow_bytes/s": 2946198.4, "flow_byte_mb": "2.95mb", "class": "warezmaster", "severity": "medium", "flow_packets": 6695.905454, "service": "ftp_data", "flag": "sf", "threat": 40, "certainty": 39 }, { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 10:55.740325", "source_ip": "101.96.116.77", "source_host": "hacker_1", "destination_ip": "172.31.68.20", "destination_host": "phone_4", "flow_bytes/s": 3677699.766, "flow_byte_mb": "3.68mb", "class": "neptune", "severity": "low", "flow_packets": 8358.408559, "service": "uucp", "flag": "s0", "threat": 8, "certainty": 7 }, { "duration": 10, "protocol_type": "tcp", "timestamp": "2018-12-01 10:55.378945", "source_ip": "101.96.116.77", "source_host": "hacker_1", "destination_ip": "172.31.65.69", "destination_host": "phone_4", "flow_bytes/s": 410040.3983, "flow_byte_mb": "410.04kb", "class": "guess_passwd", "severity": "critical", "flow_packets": 931.9099961, "service": "pop_3", "flag": "sf", "threat": 75, "certainty": 74 }, { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 10:57.123456", "source_ip": "101.96.116.77", "source_host": "hacker_1", "destination_ip": "172.31.64.69", "destination_host": "printer_8", "flow_bytes/s": 484420.4509, "flow_byte_mb": "484.42kb", "class": "normal", "severity": "critical", "flow_packets": 1105.112734, "service": "http", "flag": "sf", "threat": 61, "certainty": 83 }, { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 10:57.189042", "source_ip": "101.96.116.77", "source_host": "hacker_1", "destination_ip": "172.31.66.28", "destination_host": "printer_8", "flow_bytes/s": 21111324.376, "flow_byte_mb": "2.11mb", "class": "smurf", "severity": "critical", "flow_packets": 4798.464491, "service": "http", "flag": "sf", "threat": 65, "certainty": 38 }, { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 10:56.984301", "source_ip": "101.99.59.70", "source_host": "hacker_20", "destination_ip": "172.31.64.19", "destination_host": "email_server", "flow_bytes/s": 243458.8314, "flow_byte_mb": "243.46kb", "class": "neptune", "severity": "medium", "flow_packets": 555.4048231, "service": "http", "flag": "sf", "threat": 33, "certainty": 12 }, { "duration": 0, "protocol_type": "tcp", "timestamp": "2018-12-01 10:52.874563", "source_ip": "103.46.12.151", "source_host": "hacker_2", "destination_ip": "172.31.64.119", "destination_host": "asus_access_point_1", "flow_bytes/s": 1112572.064, "flow_byte_mb": "1.11mb", "class": "satan", "severity": "high", "flow_packets": 2528.572873, "service": "rej", "flag": "rej", "threat": 99, "certainty": 32 }, { "duration": 0, "protocol_type": "icmp", "timestamp": "2018-12-01 10:53.102584", "source_ip": "103.70.130.74", "source_host": "hacker_3", "destination_ip": "172.31.65.9", "destination_host": "cisco_router_3", "flow_bytes/s": 0, "flow_byte_mb": "0", "class": "ipsweep", "severity": "critical", "flow_packets": 19607.84314, "service": "eco_i", "flag": "sf", "threat": 88, "certainty": 122 }, { "duration": 1, "protocol_type": "tcp", "timestamp": "2018-12-1 10:57.649701", "source_ip": "103.94.120.3", "source_host": "hacker_22", "destination_ip": "172.31.64.61", "destination_host": "desktop_30", "flow_bytes/s": 43820.2953, "flow_byte_mb": "483.82kb", "class": "mailbomb", "severity": "high", "flow_packets": 628.3380459, "service": "smtp", "flag": "sf", "threat": 70, "certainty": 82 }, { "duration": 805, "protocol_type": "tcp", "timestamp": "2018-12-01 11:02.978546", "source_ip": "104.16.24.92", "source_host": "hacker_4", "destination_ip": "192.168.10.25", "destination_host": "palo_alto_firewall", "flow_bytes/s": 2414536.323, "flow_byte_mb": "2.41mb", "class": "apache2", "severity": "low", "flow_packets": 5510.410491, "service": "http", "flag": "rstr", "threat": 22, "certainty": 62 }, { "duration": 7695, "protocol_type": "tcp", "timestamp": "2018-12-01 10:57.369636", "source_ip": "104.20.117.11", "source_host": "hacker_29", "destination_ip": "172.31.68.23", "destination_host": "smart_phone_137", "flow_bytes/s": 3318796.405, "flow_byte_mb": "3.32mb", "class": "processtable", "severity": "high", "flow_packets": 7581.086362, "service": "high", "flag": "sf", "threat": 58, "certainty": 24 } ] }, "width": 1000, "height": 600, "layer": [ { "mark": { "type": "circle", "opacity": 1, "tooltip": { "content": "data" }, "size": 100 }, "encoding": { "x": { "field": "certainty", "type": "quantitative", "scale": {"domain": [0, 100]}, "axis": {"tickCount": 10, "title": "certainty"} }, "y": { "field": "threat", "type": "quantitative", "scale": {"domain": [0, 100]}, "axis": {"tickCount": 10, "title": "threat"} }, "color": { "field": "severity", "title": "severity" } } }, { "mark": "rule", "encoding": { "x": { "field": "certainty", "type": "quantitative", "aggregate": "mean" }, "y": { "field": "threat", "type": "quantitative", "aggregate": "mean" } } } ] } ``` ---
**Author:** ![nickofthyme](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/nickofthyme/32/60032_2.png) [@nickofthyme](https://discuss.elastic.co/u/nickofthyme)\ **Post date:** [July 12, 2021, 4:24pm UTC](https://discuss.elastic.co/t/kibana-scatter-plot-graph-lines-in-the-middle/277887/2 "2021-07-12T16:24:03Z")
Hey @momo1104 You could separate the `rule` marks into their own `layer`. The difficulty with this is determining a pixel length/height for each line to get say a 20px x 20 px cross with the origin at the mean/mean coordinate. See example [here](https://vega.github.io/editor/#/url/vega-lite/N4KABGBEAkDODGALApgWwIaQFxUQFzwAdYsB6UgN2QHN0A6agSz0QFcAjOxge1IRQyUa6ALQAbZskoBWOgCtY3AHaQANOCgATZAgBOjQnh4qckAIJgE6Asl2Ex3PJcTcA7oyXU63tRsibrTBxQCAhICnQxVh1sMABtDVCwEKTQ-1Zda2NYgAZ1VLTCXUdueG4xAH08AE9CZFjIPHhCXwKwo1QdPHRUFtMAJhyARgAOESH+kWGwIZysaVkAdgWANn6AZla2yEUM+GQKgwahulm6ful+04BOFa2Cne49g5dYPAbEdHgAa1sKocW91S-i6HiyykOfSgAKu6xOK1kI2uQKSILeYKMENe71MRQ8eD+AJRaQAZg5XBV2NUCbA+LFpDkcisRv1FnQACzXfr5bZktyU6kHVDsBqyYbCrDEsLwMToWCwBpKZCGVhKqVQWDIKj6GofRjURDqyB8imEL6-PAKnBDIbrRbXU7Sdbra48h6a3QURj7XJu4Fk9DUBq6ZByI0sEPWWLXIZ+1H7XTdfHVWLskaJUIAXzjyQzqM0GXBJjASJGObCRRKZUqNTqDSaLXLUA6XR6UMgg1G40m0xtWBy-XmVxG0hGQ2kgKbj2ekOOpxy50uNzuU92un2FWxH3NhMnebS2nRSiLs9MMLocLoCLoSKNh6Mx8xSk33DeDTxSgJun+e7aUBNAo0nSOD9CsizsnQiw5OsOTSCsU4AVSBIVMKDRXGB3wilOMpylaUDoGaSAHP0RqatqzApqY5JGgBhEWnhrJXnC-T9NcXKrrYXo+qY+BEDRspBqYuhvLo4aIJGOIzNI2G2Emn6UTM7L7tm+4pA8BaZE+vr7hWxR4KU5RVLU9SmKwmiNjpzaMJ0bxtmhwxjBMUxDDMczSCcI79JyDqkU864HEcZ6nNeQwrIuOS+TOW48Tu36jHeoKPsYp7QossLwmyYEJUeJ7RRqGCJhUhAuEq-yDPx-JITowElix4HnOy4GupZxrkoBQoiqYLLnIsmFGjh8oNLASi9NQyDdAQ5qkVqtgUQ01EIW1dHjQxYGyKOlwjOyHGet6JlQHiEQEvxgZDSSYkSbE6zci1CZybqOBwspOZqcCGlFtpf6QJW+nVkZdamA24bWa2vT2V2Tm9kM-bDtcA62pF-kpZAJyhbIoXhYjG55ZAnw-ISIzZQ+J6Bal6VXplv7bPeGLJTjsAFXgRUlQcEwRYtlWCrSDFbf0NqQaBHMUlVKGdVA-RbecQx9dhsqDaYSjcLoGBiNN5EPVAnSaIwrCoBVpo7pasQIicoHsqBzI7Vx+24wQFlfQGgkaudU4RsgUY4JcMmJugyb0kMz2qS171aTgeQtT9Bk1sZDRmfb2wtrZYMDA53bOa5Q50Nc7I2u5WMBe2qNQVLIzBSRq5+djr6SbjsX-ITU400lEKkyjaUXvCiJE7TWLV+++ifoS7L6+13OxLanLrN1Y6xi1iGCqLc7rNIqGy7hipKyrauzRrkDwDq3qRCPy1G49TJhYs9q51be394wR31Itp2mLALstW7HsltJt2yb78nG4sQOBRXr5kLKHMA4cvqRz+rWG2QNXYgyTu2TsjkewuVmPMB02dBgwXzsjIuC4+al1CuXFqa4q5vhivjOKDdg6JRJoXdul5ry0K+k3XKfdcQDy-P8YeQtR41VAqyAEDp1gIn4SLVCAwmKr1unLPCkBFbKyPhxdWClcb6kNPwk+eFpDXGLiMNYQxrjrBvtxXAdsTpOx2G-L6H9JKQO2HdP+GsA4FBUsA4OYDshhynNAwysD6zNGBjZboydxap0hugty6w6BwX0RMPBrcTgLFOIsMKEs8E4zxr8OKyJG70KfPgph8IHQ2m7s3Z89NGbM2UKzdkfC55tSqmPHA1wxzOk6bE0xTTObISkVAdpJxnSyK+gNBRSoVRqlUTvdR+9mCH1Vtow2eEVhrPWVeNZiwzE2xJEQCoARuhWLOhdd2kl2ne3ugpfRQDUggIPN45QqY-F6Sjv9OBwSEGhLsinCGaCM56MgosJEKxNgVxnMkuJ6N0nnFYdschLxOG4DrsYipDDjglKvGUoYaKinVPQIVYqdTeGNIds0rmgjRyGLHFnOEEiF4DI7HE64oynHyIaNQaI8oiq4VcJobeOp1Fax1nrZZ+NT5gD0ZeOGAJLZkM4rfXE3BCAVDBU05+ztTmf3ZD0sZv8-Y4HNrcpI9ywghx8RAl5VYAkx0Bp89+iCwnIMif8jBTos6GOuji8FSNknDCzmFG0F8qbukroiyhyLqH-FxclZJmKVgQXtDG3uEbjToAAB7RvpUBPCQxGqDEZIW7NHVjj5roIyVlDxxkcq5bAHl8o+UCrmqYeZRh4AqN6QbcVubC1FvlbtcxjRkBiCVO8J+1jX5avOWWH+PsDVgDYsa0IpqtCPOLI4h4-jo4A2bPauxjqfkRL+enN1sSbQXBGCG4ECL8H+tuKcDGl8slItrlG71dCcpFLjeTa8cNk1VJfSSDNWbO0CIYtnFYxjS7bVA5IsWTLrgrywnI9ephXAEuQAALwwG8WwTbd7Ct1sfFZxsViIazrBdk0gYNfQ9NbBoeyVWHMwOOk5rtxJnNTBu4Ezj50uiXRAFd6RNIWu46iLd7ygnxweInJ14NUEnrcksdk0ELhJMLnewNj6r2ohvdklF-7ik-tLuVApn66YvqJaVUlvJyU5qumBdJbFIJrOLYvUwsTmSVp4+yhWyo8CqkfvKtR803DEe7bEEYy9oM5BHHonZsdWB7tsxqnY7N34cc-jOvVc7-44EAe4l6XiRNPOtGJworyYG2t3dJ4EsnD0dhdYp+Ysg7RIio+p44mmH3BufamnJhJDPfo7leWQZHDM4yswcGzDx572cNbMHIKmLztN1bZvpJbTA5wXEtmWKH5ZQE5ToOtZoG38pmYKhorbFnhfotGaVOQ2K3FnrRhVg7CDKtVccl+tiE6ZckssS5LiFLgQE7mNha7PrbAk4Eu1tXUT1fCY149vY3JsgmOsKjK4yFhtvSce9QagV9ZrgNuKQ3GE-oguNszxM8WWe4X8OFs27PVTwmmBpgwOQMmamSjb7moDs45P0PbYzfNQCUVvC7zaoDXfbUs0DOjx6zHRhMRYmOEs8Usaxn7U7jYvacfqvLJZ1hg6E+a0rlqI6VZtTuxoyWZMHqRygtOqP5jo6REt0htHcd+vx1p3rPqKEk4MzTnuz5hvMIyUzt6hSLOpo-Dw6PqI5us9iHzG0tovIXnSW5xlVwbTefjGLnYqAMi-fdDNS7LaD5y9uytVM9poMJs5PrivA6ba8Xh6SASbGMuXRwOI2dVyrrpkK0HCHJX11Wt+jbj5Xf2iO+dSj6J8wwrtJ1cMTrZ470OkBVBYn24o2mY-bT2NFORsJpuBNl9aBfaVDo3h4trSwBeUx6OG8cIaPreFgy+Dr+OQrAi5sqobi7+aBb4ZCrIDaxEZip3aeypIqZpgbCt7XpvYd5a7qoTrl51b-ZXRrZVqG6uL9Cm7FYfS+JW7Wrbpz4hKgxL4Kau5LiXpY5qre4QoaaxLsiBr555yB7hrB5H7k4YqU4Pr5In5h4vippyisB1pfD7Dcofb4gga84-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-4cgGHIa9EHaQAERfAoBe7wqV7S6QALQK4kbwFnDbYt5LG2wsmYHBgiSbEv43Q5Z7FgBrD8lvSClObfzhGUGSZw6XFya-L0G3EXhkagqKnwrpFdYQSc42jo7AmfFIz6ZH7lEgnmYtzn7MImYfEx59lgk1wMwEpMxTb-B2gjzOl4TOijD2hhQqZFmtFwYNDdL9DEky7F6VhyG2TsBiBBavYhY8RWGwH175ajgnCxZ1mZlhkuHnkUmskbHsmfyjhA7zpeTKQZgAC6GgHiUA7gmgLA48faYQKAmikkKwjIPIkZ6A1QeGOACQJq+4kABU3wsQQm5xe8tpMoJ52wyqXw0uKBCO3A5QRgUIK60oygBIn4DQzGkAlkQF7ojAmG+0i2YOkAyASgZQ2sng2FLU6aQlf4YQNpw6-KLaPJ6o7Q1WkAAAjqwOgJ+MwFkFQLJRqHLvtMAP4ESX-LEHEHkK5DkH+axdsBmrUdhY0N6N8AAMJPAMVlaqBWR4DHlXYyWZgsVTgKQ0X-iMCSX1i4FNhyW25KUqVGATT3yEW0baXWWaD6UeCGXGWLZmUhX4TppWXBA2U-AOWqiSSzAuU2VuVwK4FeV-jmXxjlBKyiViXGgBViBSUajhm6jpXFXuUvwtUpgsW-lJDmX3IYUEpYVCSsDuU5g8V8XcACVOxCa+WWTiUNVNWNDBXzXNjyXhWqVRUaVtWBjUAhi0DHSmCdAqXMUVW9VZh+gDWYXBijUxVpC8X8UeAzXCW1UOyLUeUBEphtW4UbWRXqV3UPC7X7XWA2zHUqA9XuIZjlVgAAWZhAA) as shown below. ![visualization](https://us1.discourse-cdn.com/elastic/original/3X/7/0/70b2a0dcd04cf56d5f84c923a432206358956677.png) Another approach would be to use a [`point`](https://vega.github.io/vega-lite/docs/point.html) mark instead, with a simple svg cross path scaled to whatever pixel value you want. The `layer` would look something like this... ```json { "mark": { "type": "point", "shape": "M -1 0 L 1 0 M 0 1 L 0 -1", "strokeWidth": 1, "size": 10000, "color": "red" }, "encoding": { "x": { "field": "certainty", "type": "quantitative", "aggregate": "mean" }, "y": { "field": "threat", "type": "quantitative", "aggregate": "mean" } } } ``` And the chart would look like this... ![visualization (1)](https://us1.discourse-cdn.com/elastic/original/3X/2/5/25eaffa1d1ff26a6af2c9b6b81e6deb3843238e7.png) See the full example [here](https://vega.github.io/editor/#/url/vega-lite/N4KABGBEAkDODGALApgWwIaQFxUQFzwAdYsB6UgN2QHN0A6agSz0QFcAjOxge1IRQyUa6ALQAbZskoBWOgCtY3AHaQANOCgATZAgBOjQnh4qckAIJgE6Asl2Ex3PJcTcA7oyXU63tRsibrTBxQCAhICnQxVh1sMABtDVCwEKTQ-1Zda2NYgAZ1VLTCXUdueG4xAH08AE9CZFjIPHhCXwKwo1QdPHRUFtMAJhyARgAOESH+kWGwIZysaVkAdgWANn6AZla2yEUM+GQKgwahulm6ful+04BOFa2Cne49g5dYPAbEdHgAa1sKocW91S-i6HiyykOfSgAKu6xOK1kI2uQKSILeYKMENe71MRQ8eD+AJRaQAZg5XBV2NUCbA+LFpDkcisRv1FnQACzXfr5bZktyU6kHVDsBqyYbCrDEsLwMToWCwBpKZCGVhKqVQWDIKj6GofRjURDqyB8imEL6-PAKnBDIbrRbXU7Sdbra48h6a3QURj7XJu4Fk9DUBq6ZByI0sEPWWLXIZ+1H7XTdfHVWLskaJUIAXzjyQzqM0GXBJjASJGObCRRKZUqNTqDSaLXLUA6XR6UMgg1G40m0xtWBy-XmVxG0hGQ2kgKbj2ekOOpxy50uNzuU92un2FWxH3NhMnebS2nRSiLs9MMLocLoCLoSKNh6Mx8xSk33DeDTxSgJun+e7aUBNAo0nSOD9CsizsnQiw5OsOTSCsU4AVSBIVMKDRXGB3wilOMpylaUDoGaSAHP0RqatqzApqY5JGgBhEWnhrJXnC-T9NcXKrrYXo+qY+BEDRspBqYuhvLo4aIJGOIzNI2G2Emn6UTM7L7tm+4pA8BaZE+vr7hWxR4KU5RVLU9SmKwmiNjpzaMJ0bxtmhwxjBMUxDDMczSCcI79JyDqkU864HEcZ6nNeQwrIuOS+TOW48Tu36jHeoKPsYp7QossLwmyYEJUeJ7RRqGCJhUhAuEq-yDPx-JITowElix4HnOy4GupZxrkoBQoiqYLLnIsmFGjh8oNLASi9NQyDdAQ5qkVqtgUQ01EIW1dHjQxYGyKOlwjOyHGet6JlQHiEQEvxgZDSSYkSbE6zci1CZybqOBwspOZqcCGlFtpf6QJW+nVkZdamA24bWa2vT2V2Tm9kM-bDtcA62pF-kpZAJyhbIoXhYjG55ZAnw-ISIzZQ+J6Bal6VXplv7bPeGLJTjsAFXgRUlQcEwRYtlWCrSDFbf0NqQaBHMUlVKGdVA-RbecQx9dhsqDaYSjcLoGBiNN5EPVAnSaIwrCoBVpo7pasQIicoHsqBzI7Vx+24wQFlfQGgkaudU4RsgUY4JcMmJugyb0kMz2qS171aTgeQtT9Bk1sZDRmfb2wtrZYMDA53bOa5Q50Nc7I2u5WMBe2qNQVLIzBSRq5+djr6SbjsX-ITU400lEKkyjaUXvCiJE7TWLV+++ifoS7L6+13OxLanLrN1Y6xi1iGCqLc7rNIqGy7hipKyrauzRrkDwDq3qRCPy1G49TJhYs9q51be394wR31Itp2mLALstW7HsltJt2yb78nG4sQOBRXr5kLKHMA4cvqRz+rWG2QNXYgyTu2TsjkewuVmPMB02dBgwXzsjIuC4+al1CuXFqa4q5vhivjOKDdg6JRJoXdul5ry0K+k3XKfdcQDy-P8YeQtR41VAqyAEDp1gIn4SLVCAwmKr1unLPCkBFbKyPhxdWClcb6kNPwk+eFpDXGLiMNYQxrjrBvtxXAdsTpOx2G-L6H9JKQO2HdP+GsA4FBUsA4OYDshhynNAwysD6zNGBjZboydxap0hugty6w6BwX0RMPBrcTgLFOIsMKEs8E4zxr8OKyJG70KfPgph8IHQ2m7s3Z89NGbM2UKzdkfC55tSqmPHA1wxzOk6bE0xTTObISkVAdpJxnSyK+gNBRSoVRqlUTvdR+9mCH1Vtow2eEVhrPWVeNZiwzE2xJEQCoARuhWLOhdd2kl2ne3ugpfRQDUggIPN45QqY-F6Sjv9OBwSEGhLsinCGaCM56MgosJEKxNgVxnMkuJ6N0nnFYdschLxOG4DrsYipDDjglKvGUoYaKinVPQIVYqdTeGNIds0rmgjRyGLHFnOEEiF4DI7HE64oynHyIaNQaI8oiq4VcJobeOp1Fax1nrZZ+NT5gD0ZeOGAJLZkM4rfXE3BCAVDBU05+ztTmf3ZD0sZv8-Y4HNrcpI9ywghx8RAl5VYAkx0Bp89+iCwnIMif8jBTos6GOuji8FSNknDCzmFG0F8qbukroiyhyLqH-FxclZJmKVgQXtDG3uEbjToAAB7RvpUBPCQxGqDEZIW7NHVjj5roIyVlDxxkcq5bAHl8o+UCrmqYeZRh4AqN6QbcVubC1FvlbtcxjRkBiCVO8J+1jX5avOWWH+PsDVgDYsa0IpqtCPOLI4h4-jo4A2bPauxjqfkRL+enN1sSbQXBGCG4ECL8H+tuKcDGl8slItrlG71dCcpFLjeTa8cNk1VJfSSDNWbO0CIYtnFYxjS7bVA5IsWTLrgrywnI9ephXAEuQAALwwG8WwTbd7Ct1sfFZxsViIazrBdk0gYNfQ9NbBoeyVWHMwOOk5rtxJnNTBu4Ezj50uiXRAFd6RNIWu46iLd7ygnxweInJ14NUEnrcksdk0ELhJMLnewNj6r2ohvdklF-7ik-tLuVApn66YvqJaVUlvJyU5qumBdJbFIJrOLYvUwsTmSVp4+yhWyo8CqkfvKtR803DEe7bEEYy9oM5BHHonZsdWB7tsxqnY7N34cc-jOvVc7-44EAe4l6XiRNPOtGJworyYG2t3dJ4EsnD0dhdYp+Ysg7RIio+p44mmH3BufamnJhJDPfo7leWQZHDM4yswcGzDx572cNbMHIKmLztN1bZvpJbTA5wXEtmWKH5ZQE5ToOtZoG38pmYKhorbFnhfotGaVOQ2K3FnrRhVg7CDKtVccl+tiE6ZckssS5LiFLgQE7mNha7PrbAk4Eu1tXUT1fCY149vY3JsgmOsKjK4yFhtvSce9QagV9ZrgNuKQ3GE-oguNszxM8WWe4X8OFs27PVTwmmBpgwOQMmamSjb7moDs45P0PbYzfNQCUVvC7zaoDXfbUs0DOjx6zHRhMRYmOEs8Usaxn7U7jYvacfqvLJZ1hg6E+a0rlqI6VZtTuxoyWZMHqRygtOqP5jo6REt0htHcd+vx1p3rPqKEk4MzTnuz5hvMIyUzt6hSLOpo-Dw6PqI5us9iHzG0tovIXnSW5xlVwbTefjGLnYqAMi-fdDNS7LaD5y9uytVM9poMJs5PrivA6ba8Xh6SASbGMuXRwOI2dVyrrpkK0HCHJX11Wt+jbj5Xf2iO+dSj6J8wwrtJ1cMTrZ470OkBVBYn24o2mY-bT2NFORsJpuBNl9aBfaVDo3h4trSwBeUx6OG8cIaPreFgy+Dr+OQrAi5sqobi7+aBb4ZCrIDaxEZip3aeypIqZpgbCt7XpvYd5a7qoTrl51b-ZXRrZVqG6uL9Cm7FYfS+JW7Wrbpz4hKgxL4Kau5LiXpY5qre4QoaaxLsiBr555yB7hrB5H7k4YqU4Pr5In5h4vippyisB1pfD7Dcofb4gga84-7zYzDnoThXBMhf7M586MqoxDCF5pDVovyBAqBS67yICaJ14SoXASxxJpSXr4GoHt7BihjfZQAhhhjsb94Lo84G65YazXQkET5kGW5QLW5UENDehgxfK0HyYu4r7uqzAXozbXo+7sGQQLi2gLjgQH5UK5Jfah6VJGYX6yCiFsKx4po1zwCMAIDcAVDFCsA8IsHf5gZQ46EqGbZQDpai4gGQAGCwCuDIDKgQFXY14drKE8oRbWi3A5BshbSf4a5QDIBlCHDuE2K644AjDZb+HD7WgsTBHUyQ7WjT5vKw41Y0FILxFOSJGZSchQTvqsG+oZHZynCc4tGhpRQvqk4VAsSCFnjxpU6PHUyVEAapqHjfD6Qqq4JP41Q6osiEKIZOHJ4s786QBpixIshAFVrF4YCMBiDsDcCGFhBkSzJ6gGjWGrJ2HOgjBLbxb9r0YvyoB8Ta6areGcb5blbSiEEKQsiHHqTHEliwSnFVa27wIOrfJO5NZQwwxZzArUbY5PEbh+oQQYxZ5ch5GRoFGpH5ign4JcjBTEKELSDX7x6RD1GRD6QVAkiMAhjoZiDy6TEtKCI5xUZiIXgbC55-4cgGHIa9EHaQAERfAoBe7wqV7S6QALQK4kbwFnDbYt5LG2wsmYHBgiSbEv43Q5Z7FgBrD8lvSClObfzhGUGSZw6XFya-L0G3EXhkagqKnwrpFdYQSc42jo7AmfFIz6ZH7lEgnmYtzn7MImYfEx59lgk1wMwEpMxTb-B2gjzOl4TOijD2hhQqZFmtFwYNDdL9DEky7F6VhyG2TsBiBBavYhY8RWGwH175ajgnCxZ1mZlhkuHnkUmskbHsmfyjhA7zpeTKQZgAC6GgHiUA7gmgLA48faYQKAmikkKwjIPIkZ6A1QeGOACQJq+4kABU3wsQQm5xe8tpMoJ52wyqXw0uKBCO3A5QRgUIK60oygBIn4DQzGkAlkQF7ojAmG+0i2YOkAyASgZQ2sng2FLU6aQlf4YQNpw6-KLaPJ6o7Q1WkAAAjqwOgJ+MwFkFQLJRqHLvtMAP4ESX-LEHEHkK5DkH+axdsBmrUdhY0N6N8AAMJPAMVlaqBWR4DHlXYyWZgsVTgKQ0X-iMCSX1i4FNhyW25KUqVGATT3yEW0baXWWaD6UeCGXGWLZmUhX4TppWXBA2U-AOWqiSSzAuU2VuVwK4FeV-jmXxjlBKyiViXGgBViBSUajhm6jpXFXuUvwtUpgsW-lJDmX3IYUEpYXBDvzyUKEMWrifC24ACyYA4wECYAAAMjMAtbNTkCtcteteMKRHgMUL8AAOqMCgWGgnFkLsWcW9rYTVWiRCRQHMVj4PC8X8UeBOxCYiUjViX+WBXSUBEphtW4XhWqVRUaVtWBjUAhi0DHSmCdAqX3VtCVVpC+WWTiUNVNWNDBXI3NjyWA2RXqUxUWXUDg3CBQ2azuwqA9XuIZjlVgAAWZhAA). ---
**Author:** ![momo1104](https://avatars.discourse-cdn.com/v4/letter/m/e5b9ba/32.png) [@momo1104](https://discuss.elastic.co/u/momo1104)\ **Post date:** [July 14, 2021, 10:58pm UTC](https://discuss.elastic.co/t/kibana-scatter-plot-graph-lines-in-the-middle/277887/3 "2021-07-14T22:58:19Z")
hooray! Thanks @nickofthyme ---
**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\ **Post date:** [August 11, 2021, 10:58pm UTC](https://discuss.elastic.co/t/kibana-scatter-plot-graph-lines-in-the-middle/277887/4 "2021-08-11T22:58:43Z")
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