You can highlight content in a widget based on selections or results in other queries. For example, color code the values of number widgets based on thresholds to draw attention to low and high numbers.
Let’s say you want to change the colors of measures in three number widgets based on whether the numbers are high (green), medium (yellow), or low (red).
In the dashboard JSON, compute the color based on the measure of each query with a case statement. Then apply the computed color to the numberColor field of each number widget.
1{
2 "label": "Sales Overview",
3 "state": {
4 "gridLayouts": [...],
5 "layouts": [],
6 "steps": {
7 "color_1": {
8 "type": "aggregateflex",
9 "visualizationParameters": {
10 "options": {}
11 },
12 "query": {
13 "pigql": "q = load \"Opportunity_Dataset\";\n
14 q = filter q by 'Region' == \"US\";\n
15 q = group q by all;\n
16 q = foreach q generate count() as 'count',
17 (case when count() \< 25000 then \\"#EE0A50\\"
18 when count() \< 50000 then \\"#F8CE00\\"
19 else \\"#0FD178\\" end) as 'color';\\n
20 q = limit q 2000;",
21 "measures": [ [
22 "count",
23 "*",
24 "count" ] ],
25 "groups": [ "color" ],
26 "measuresMap": {}
27 },
28 "isFacet": true,
29 "useGlobal": true,
30 "isGlobal": false,
31 "datasets": [{
32 "name": "Opportunity_Dataset",
33 "url": "/services/data/v38.0/wave/datasets/0Fbx000000000KLCAY",
34 "id": "0Fbx000000000KLCAY"
35 }]
36 },
37 "color_2": {
38 "type": "aggregateflex",
39 "visualizationParameters": {
40 "options": {}
41 },
42 "query": {
43 "pigql": "q = load \"Opportunity_Dataset\";\n
44 q = filter q by 'Region' == \"AP\";\n
45 q = group q by all;\n
46 q = foreach q generate count() as 'count',
47 (case when count() \< 25000 then \\"#EE0A50\\"
48 when count() \< 50000 then \\"#F8CE00\\"
49 else \\"#0FD178\\" end) as 'color';\\n
50 q = limit q 2000;",
51 "measures": [ [
52 "count",
53 "*",
54 "count"
55 ] ],
56 "groups": [ "color" ],
57 "measuresMap": {}
58 },
59 "isFacet": true,
60 "useGlobal": true,
61 "isGlobal": false,
62 "datasets": [{
63 "name": "Opportunity_Dataset",
64 "url": "/services/data/v38.0/wave/datasets/0Fbx000000000KLCAY",
65 "id": "0Fbx000000000KLCAY"
66 }]
67 },
68 "color_3": {
69 "type": "aggregateflex",
70 "visualizationParameters": {
71 "options": {}
72 },
73 "query": {
74 "pigql": "q = load \"Opportunity_Dataset\";\n
75 q = filter q by 'Region' == \"EU\";\n
76 q = group q by all;\n
77 q = foreach q generate count() as 'count',
78 (case when count() \< 25000 then \\"#EE0A50\\"
79 when count() \< 50000 then \\"#F8CE00\\"
80 else \\"#0FD178\\" end) as 'color';\\n
81 q = limit q 2000;",
82 "measures": [ [
83 "count",
84 "*",
85 "count"
86 ] ],
87 "groups": [ "color" ],
88 "measuresMap": {}
89 },
90 "isFacet": true,
91 "useGlobal": true,
92 "isGlobal": false,
93 "datasets": [{
94 "name": "Opportunity_Dataset",
95 "url": "/services/data/v38.0/wave/datasets/0Fbx000000000KLCAY",
96 "id": "0Fbx000000000KLCAY"
97 }]
98 }
99 },
100 "widgetStyle": {...},
101 "widgets": {
102 "number_5": {
103 "type": "number",
104 "parameters": {
105 "step": "color_1",
106 "measureField": "count",
107 "textAlignment": "right",
108 "compact": false,
109 "exploreLink": true,
110 "titleColor": "#335779",
111 "titleSize": 14,
112 "numberColor": "{{cell(color_1.result, 0, \\"color\\").asString()}}",
113 "numberSize": 32,
114 "title": "Opp Count (United States)"
115 }
116 },
117 "number_6": {
118 "type": "number",
119 "parameters": {
120 "step": "color_2",
121 "measureField": "count",
122 "textAlignment": "right",
123 "compact": false,
124 "exploreLink": true,
125 "titleColor": "#335779",
126 "titleSize": 14,
127 "numberColor": "{{cell(color_2.result, 0, \\"color\\").asString()}}",
128 "numberSize": 32,
129 "title": "Opp Count (Asia Pacific)"
130 }
131 },
132 "number_7": {
133 "type": "number",
134 "parameters": {
135 "step": "color_3",
136 "measureField": "count",
137 "textAlignment": "right",
138 "compact": false,
139 "exploreLink": true,
140 "titleColor": "#335779",
141 "titleSize": 14,
142 "numberColor": "{{cell(color_3.result, 0, \\"color\\").asString()}}",
143 "numberSize": 32,
144 "title": "Opp Count (Europe)"
145 }
146 }
147 }
148 },
149 "datasets": [...]
150}
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