View this page in the latest version of Appian. Year-Over-Year Report Share Share via LinkedIn Reddit Email Copy Link Print On This Page Tip: Interface patterns give you an opportunity to explore different interface designs. Be sure to check out How to Adapt a Pattern for Your Application. Goal This is a feature-rich, interactive report for sales and profits by products over select periods of time. This page explains how you can use this pattern in your interface, and walks through the design structure in detail. Design structure The main components in this pattern are boxes, styled text, rich text icons, and charts that show a break down of profits, sales, and costs per year, month, and product. The components are organized in side by side layouts nested within columns layouts. The image below displays how the pattern looks on a blank interface with callouts of the main components. You can examine the entire expression or jump down to the subsections below with referenced line numbers to see a detailed breakdown of the main components. Pattern expression This pattern introduces a 410-line expression to the interface. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 { a!localVariables( /* Data for the Profit: Year to Date KPI. The query that replaces this should be aggregated by year, * * then sorted by year in descending order, so that the first element is the current year. */ local!profitKPIDatasubset: a!dataSubset( data: { a!map(orderDate_year: 2019, profit_sum: 200000000.00, targetProfit_sum: 150000000.00), a!map(orderDate_year: 2018, profit_sum: 300000000.00, targetProfit_sum: 150000000.00) } ), /* Data for the Sales: Year to Date KPI. The query that replaces this should be aggregated by year, * * then sorted by year in descending order, so that the first element is the current year. */ local!salesKPIDatasubset: a!dataSubset( data: { a!map(orderDate_year: 2019, sales_sum: 500000000.00, targetSales_sum: 650000000.00), a!map(orderDate_year: 2018, sales_sum: 425000000.00, targetSales_sum: 650000000.00) } ), /* Data for the Cost: Year to Date KPI. The query that replaces this should be aggregated by year, * * then sorted by year in descending order, so that the first element is the current year. */ local!costKPIDatasubset: a!dataSubset( data: { a!map(orderDate_year: 2019, cost_sum: 50000000.00, targetCost_sum: 25000000.00), a!map(orderDate_year: 2018, cost_sum: 100000000.00, targetCost_sum: 25000000.00) } ), /* Variables for the Time Period filter and query */ local!timePeriodLabels: { "January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December" }, local!timePeriodValue: {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}, local!currentMonth: month(today()), local!timePeriodSelection: local!currentMonth, /* Example time range filter value */ /*local!timeRange: {*/ /*date(year(today()), local!timePeriodSelection, 1),*/ /*eomonth(date(year(today()), local!timePeriodSelection, 1), 0)*/ /*},*/ /* Sample data for card selectors in the TOP SELLING PRODUCTS BY CATEGORY & MONTH section. * * Substitute with a query on the aggregated numerical field (e.g., sales_sum), and the * * category (e.g., `productLine`) and use local!timeRange as the filter value for your date field * * (e.g., `orderDate`). * Select a batch size of 3, 5 or 10 and sort in descending order on the numerical field to get * * only the top values returned. */ local!salesByCategory: a!dataSubset( data: { a!map(productLine: "Beverages", sales_sum: 111562.51), a!map(productLine: "Cereals", sales_sum: 59862.22), a!map(productLine: "Dairy", sales_sum: 43763.59), a!map(productLine: "Culinary", sales_sum: 40160.97), a!map(productLine: "Infant Nutrition", sales_sum: 6284.0) } ), /* Default card selection */ local!selectedCategory: index(local!salesByCategory.data, "productLine")[1], /* Sample data for the bar chart in the TOP SELLING PRODUCTS BY CATEGORY & MONTH section. * * Substitute with a query on the aggregated numerical field (e.g., sales_sum), the category * * (e.g., `productLine`), and items within that categry (e.g., `productCode`), and use * * local!timeRange as the filter value for for your date field (e.g., `orderDate`). * Select a batch size of -1 and sort in descending order on the numerical field to get all * * items returned. */ local!salesByCategoryAndProduct: a!dataSubset( data: { a!map(productLine: "Beverages", productCode: "Coke", sales_sum: 20535.24), a!map(productLine: "Beverages", productCode: "Pepsi", sales_sum: 13556.06), a!map(productLine: "Beverages", productCode: "Dr Pepper", sales_sum: 12300.55), a!map(productLine: "Beverages", productCode: "Sprite", sales_sum: 5168.4), a!map(productLine: "Beverages", productCode: "Other", sales_sum: 4271.5), a!map(productLine: "Beverages", productCode: "Vitamin Water", sales_sum: 4030.47) } ), /* Sample Current Year to Date data for the column chart in the SALES PERFORMANCE: YEAR TO DATE VS. PREVIOUS YEAR TO DATE * * section. Substitute with a query on the aggregated numerical field (e.g., sales_sum) and the * * time field (e.g., `orderDate`). Make sure to use `Current Year to Date` as the date preset * * in your filter using a date field. Group the data for `orderDate` using the year and * * month modifiers. * * Select a batch size of -1 and sort in descending order on the numerical field. */ local!tyMonthDataSubset: a!dataSubset( data: { a!map(orderDate_year: 2019, orderDate_month: 1, sales_sum: 339543.42), a!map(orderDate_year: 2019, orderDate_month: 2, sales_sum: 358186.18), a!map(orderDate_year: 2019, orderDate_month: 3, sales_sum: 374262.76), a!map(orderDate_year: 2019, orderDate_month: 4, sales_sum: 138915.45) } ), /* Sample Current Year to Date data for the column chart in the SALES PERFORMANCE: YEAR TO DATE VS. PREVIOUS YEAR TO DATE * * section. Substitute with a query on the aggregated numerical field (e.g., sales_sum) and the * * time field (e.g., `orderDate`). Make sure to use `Previous Year to Date` as the date preset * * in your filter using a date field. Group the data for `orderDate` using the year and * * month modifiers. * * Select a batch size of -1 and sort in descending order on the numerical field. */ local!lyMonthDataSubset: a!dataSubset( data: { a!map(orderDate_year: 2018, orderDate_month: 1, sales_sum: 316577.42), a!map(orderDate_year: 2018, orderDate_month: 2, sales_sum: 311419.53), a!map(orderDate_year: 2018, orderDate_month: 3, sales_sum: 205733.73), a!map(orderDate_year: 2018, orderDate_month: 4, sales_sum: 112537.04) } ), { a!columnsLayout( columns: { a!columnLayout( contents: { a!boxLayout( label: "Profit: Year to Date", contents: { a!sideBySideLayout( items: { a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!profitKPIDatasubset.data, "profit_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, size: "LARGE", style: "STRONG" ) } ) ), a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextIcon(icon: "bullseye", color: "SECONDARY"), " ", a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!profitKPIDatasubset.data, "targetProfit_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, color: "SECONDARY", size: "MEDIUM" ) } ), width: "MINIMIZE" ) }, alignVertical: "BOTTOM", stackWhen: { "PHONE", "TABLET_LANDSCAPE", "DESKTOP_NARROW" } ) }, marginBelow: "STANDARD" ) } ), a!columnLayout( contents: { a!boxLayout( label: "Sales: Year to Date", contents: { a!sideBySideLayout( items: { a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!salesKPIDatasubset.data, "sales_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, size: "LARGE", style: "STRONG" ) } ) ), a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextIcon(icon: "bullseye", color: "SECONDARY"), " ", a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!salesKPIDatasubset.data, "targetSales_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, color: "SECONDARY", size: "MEDIUM" ) } ), width: "MINIMIZE" ) }, alignVertical: "BOTTOM", stackWhen: { "PHONE", "TABLET_LANDSCAPE", "DESKTOP_NARROW" } ) }, marginBelow: "STANDARD" ) } ), a!columnLayout( contents: { a!boxLayout( label: "Cost: Year to Date", contents: { a!sideBySideLayout( items: { a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!costKPIDatasubset.data, "cost_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, size: "LARGE", style: "STRONG" ) } ) ), a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextIcon(icon: "bullseye", color: "SECONDARY"), " ", a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!costKPIDatasubset.data, "targetCost_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, color: "SECONDARY", size: "MEDIUM" ) } ), width: "MINIMIZE" ) }, alignVertical: "BOTTOM", stackWhen: { "PHONE", "TABLET_LANDSCAPE", "DESKTOP_NARROW" } ) }, marginBelow: "STANDARD" ) } ) }, stackWhen: { "PHONE", "TABLET_PORTRAIT" } ), a!columnsLayout( columns: { a!columnLayout( contents: { a!richTextDisplayField( value: { a!richTextHeader( text: "TOP SELLING PRODUCTS BY CATEGORY & MONTH", size: "SMALL" ) } ), a!columnsLayout( columns: { a!columnLayout( contents: { a!dropdownField( label: "Time Period", labelPosition: "ABOVE", choiceLabels: rdrop(local!timePeriodLabels, 12 - local!currentMonth), choiceValues: rdrop(local!timePeriodValue, 12 - local!currentMonth), value: local!timePeriodSelection, saveInto: {local!timePeriodSelection} ), a!textField(labelPosition: "COLLAPSED", readOnly: true), a!forEach( items: local!salesByCategory.data, expression: a!cardLayout( contents: { a!sideBySideLayout( items: { a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: a!richTextItem( text: index(index(local!salesByCategory.data, "productLine"), fv!index, ""), style: "STRONG" ) ) ), a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextItem( text: a!currency(isoCode: "USD", value: fv!item.sales_sum, decimalPlaces: 0, format: "SYMBOL"), size: "MEDIUM" ) }, align: "RIGHT" ), width: "MINIMIZE" ) }, alignVertical: "MIDDLE" ) }, link: if( local!selectedCategory = index(index(local!salesByCategory.data, "productLine"), fv!index, ""), {}, a!dynamicLink( value: index(index(local!salesByCategory.data, "productLine"), fv!index, ""), saveInto: local!selectedCategory ) ), style: if( local!selectedCategory = index(index(local!salesByCategory.data, "productLine"), fv!index, ""), "ACCENT", "NONE" ), marginBelow: "STANDARD" ) ) }, width: "NARROW_PLUS" ), a!columnLayout( contents: { { a!barChartField( categories: index(local!salesByCategoryAndProduct.data, "productCode"), series: { a!chartSeries( label: "Total Sales", data: index(local!salesByCategoryAndProduct.data, "sales_sum") ) }, stacking: "NORMAL", showLegend: false, showTooltips: true, colorScheme: "SUNSET" ) } }, width: "AUTO" ) } ) } ), a!columnLayout( contents: { a!richTextDisplayField( value: { a!richTextHeader( text: "SALES PERFORMANCE: YEAR TO DATE VS. PREVIOUS YEAR TO DATE", size: "SMALL" ) } ), a!columnChartField( categories: a!forEach( items: local!tyMonthDataSubset.data, expression: text( date( fv!item.orderDate_year, fv!item.orderDate_month, 1 ), "mmmm" ) ), series: { a!chartSeries( label: "Previous Year to Date Sales", data: index(local!lyMonthDataSubset.data, "sales_sum", null) ), a!chartSeries( label: "Current Year to Date Sales", data: index(local!tyMonthDataSubset.data, "sales_sum", null) ) }, stacking: "NONE", showLegend: true, showTooltips: true, labelPosition: "ABOVE", colorScheme: "SUNSET" ) } ) }, stackWhen: { "PHONE", "TABLET_PORTRAIT", "TABLET_LANDSCAPE" } ) } ) } [Line 1-109] Define local variables and data subsets The first section of this pattern defines all of the local variables and data that make up the report's display. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 { a!localVariables( /* Data for the Profit: Year to Date KPI. The query that replaces this should be aggregated by year, * * then sorted by year in descending order, so that the first element is the current year. */ local!profitKPIDatasubset: a!dataSubset( data: { a!map(orderDate_year: 2019, profit_sum: 200000000.00, targetProfit_sum: 150000000.00), a!map(orderDate_year: 2018, profit_sum: 300000000.00, targetProfit_sum: 150000000.00) } ), /* Data for the Sales: Year to Date KPI. The query that replaces this should be aggregated by year, * * then sorted by year in descending order, so that the first element is the current year. */ local!salesKPIDatasubset: a!dataSubset( data: { a!map(orderDate_year: 2019, sales_sum: 500000000.00, targetSales_sum: 650000000.00), a!map(orderDate_year: 2018, sales_sum: 425000000.00, targetSales_sum: 650000000.00) } ), /* Data for the Cost: Year to Date KPI. The query that replaces this should be aggregated by year, * * then sorted by year in descending order, so that the first element is the current year. */ local!costKPIDatasubset: a!dataSubset( data: { a!map(orderDate_year: 2019, cost_sum: 50000000.00, targetCost_sum: 25000000.00), a!map(orderDate_year: 2018, cost_sum: 100000000.00, targetCost_sum: 25000000.00) } ), /* Variables for the Time Period filter and query */ local!timePeriodLabels: { "January", "February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December" }, local!timePeriodValue: {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}, local!currentMonth: month(today()), local!timePeriodSelection: local!currentMonth, /* Example time range filter value */ /*local!timeRange: {*/ /*date(year(today()), local!timePeriodSelection, 1),*/ /*eomonth(date(year(today()), local!timePeriodSelection, 1), 0)*/ /*},*/ /* Sample data for card selectors in the TOP SELLING PRODUCTS BY CATEGORY & MONTH section. * * Substitute with a query on the aggregated numerical field (e.g., sales_sum), and the * * category (e.g., `productLine`) and use local!timeRange as the filter value for your date field * * (e.g., `orderDate`). * Select a batch size of 3, 5 or 10 and sort in descending order on the numerical field to get * * only the top values returned. */ local!salesByCategory: a!dataSubset( data: { a!map(productLine: "Beverages", sales_sum: 111562.51), a!map(productLine: "Cereals", sales_sum: 59862.22), a!map(productLine: "Dairy", sales_sum: 43763.59), a!map(productLine: "Culinary", sales_sum: 40160.97), a!map(productLine: "Infant Nutrition", sales_sum: 6284.0) } ), /* Default card selection */ local!selectedCategory: index(local!salesByCategory.data, "productLine")[1], /* Sample data for the bar chart in the TOP SELLING PRODUCTS BY CATEGORY & MONTH section. * * Substitute with a query on the aggregated numerical field (e.g., sales_sum), the category * * (e.g., `productLine`), and items within that categry (e.g., `productCode`), and use * * local!timeRange as the filter value for for your date field (e.g., `orderDate`). * Select a batch size of -1 and sort in descending order on the numerical field to get all * * items returned. */ local!salesByCategoryAndProduct: a!dataSubset( data: { a!map(productLine: "Beverages", productCode: "Coke", sales_sum: 20535.24), a!map(productLine: "Beverages", productCode: "Pepsi", sales_sum: 13556.06), a!map(productLine: "Beverages", productCode: "Dr Pepper", sales_sum: 12300.55), a!map(productLine: "Beverages", productCode: "Sprite", sales_sum: 5168.4), a!map(productLine: "Beverages", productCode: "Other", sales_sum: 4271.5), a!map(productLine: "Beverages", productCode: "Vitamin Water", sales_sum: 4030.47) } ), /* Sample Current Year to Date data for the column chart in the SALES PERFORMANCE: YEAR TO DATE VS. PREVIOUS YEAR TO DATE * * section. Substitute with a query on the aggregated numerical field (e.g., sales_sum) and the * * time field (e.g., `orderDate`). Make sure to use `Current Year to Date` as the date preset * * in your filter using a date field. Group the data for `orderDate` using the year and * * month modifiers. * * Select a batch size of -1 and sort in descending order on the numerical field. */ local!tyMonthDataSubset: a!dataSubset( data: { a!map(orderDate_year: 2019, orderDate_month: 1, sales_sum: 339543.42), a!map(orderDate_year: 2019, orderDate_month: 2, sales_sum: 358186.18), a!map(orderDate_year: 2019, orderDate_month: 3, sales_sum: 374262.76), a!map(orderDate_year: 2019, orderDate_month: 4, sales_sum: 138915.45) } ), /* Sample Current Year to Date data for the column chart in the SALES PERFORMANCE: YEAR TO DATE VS. PREVIOUS YEAR TO DATE * * section. Substitute with a query on the aggregated numerical field (e.g., sales_sum) and the * * time field (e.g., `orderDate`). Make sure to use `Previous Year to Date` as the date preset * * in your filter using a date field. Group the data for `orderDate` using the year and * * month modifiers. * * Select a batch size of -1 and sort in descending order on the numerical field. */ local!lyMonthDataSubset: a!dataSubset( data: { a!map(orderDate_year: 2018, orderDate_month: 1, sales_sum: 316577.42), a!map(orderDate_year: 2018, orderDate_month: 2, sales_sum: 311419.53), a!map(orderDate_year: 2018, orderDate_month: 3, sales_sum: 205733.73), a!map(orderDate_year: 2018, orderDate_month: 4, sales_sum: 112537.04) } ), [Line 110-260] Display profit, sales, and cost boxes This section is the first of two columns layouts which make up the display for the report. This first section contains three boxes that display profit, sales, and cost for the year to date. Inside the boxes are styled text and rich text icons that show the current amount met and the target amount for each category. 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 { a!columnsLayout( columns: { a!columnLayout( contents: { a!boxLayout( label: "Profit: Year to Date", contents: { a!sideBySideLayout( items: { a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!profitKPIDatasubset.data, "profit_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, size: "LARGE", style: "STRONG" ) } ) ), a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextIcon(icon: "bullseye", color: "SECONDARY"), " ", a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!profitKPIDatasubset.data, "targetProfit_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, color: "SECONDARY", size: "MEDIUM" ) } ), width: "MINIMIZE" ) }, alignVertical: "BOTTOM", stackWhen: { "PHONE", "TABLET_LANDSCAPE", "DESKTOP_NARROW" } ) }, marginBelow: "STANDARD" ) } ), a!columnLayout( contents: { a!boxLayout( label: "Sales: Year to Date", contents: { a!sideBySideLayout( items: { a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!salesKPIDatasubset.data, "sales_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, size: "LARGE", style: "STRONG" ) } ) ), a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextIcon(icon: "bullseye", color: "SECONDARY"), " ", a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!salesKPIDatasubset.data, "targetSales_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, color: "SECONDARY", size: "MEDIUM" ) } ), width: "MINIMIZE" ) }, alignVertical: "BOTTOM", stackWhen: { "PHONE", "TABLET_LANDSCAPE", "DESKTOP_NARROW" } ) }, marginBelow: "STANDARD" ) } ), a!columnLayout( contents: { a!boxLayout( label: "Cost: Year to Date", contents: { a!sideBySideLayout( items: { a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!costKPIDatasubset.data, "cost_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, size: "LARGE", style: "STRONG" ) } ) ), a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextIcon(icon: "bullseye", color: "SECONDARY"), " ", a!richTextItem( text: {a!currency(isoCode: "USD", value: index(local!costKPIDatasubset.data, "targetCost_sum")[1], decimalPlaces: 0, format: "SYMBOL")}, color: "SECONDARY", size: "MEDIUM" ) } ), width: "MINIMIZE" ) }, alignVertical: "BOTTOM", stackWhen: { "PHONE", "TABLET_LANDSCAPE", "DESKTOP_NARROW" } ) }, marginBelow: "STANDARD" ) } ) }, stackWhen: { "PHONE", "TABLET_PORTRAIT" } ), [Line 261-410] Display time period filter, product options, and charts The second columns layout contains the time period dropdown, product cards, and sales charts. The components in this section should be used as examples of how you can create an interactive report. For the components to conditionally change displays and values based on user selection, substitute your own queries and data. The time period dropdown shows one way to create a filter in your report using local variables to define filter values. With a function filter, the card and chart values would change based on the time period selected. The product cards are configured using the a!forEach() function with styled text and dynamic link components. In a completed report, these cards with dynamic links would change the chart series values based on your selected product. Lastly, the bar and column charts are configured using local variables to define their categories and series. Notice that both charts use the same color scheme to create a consistent style for the interface. 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 a!columnsLayout( columns: { a!columnLayout( contents: { a!richTextDisplayField( value: { a!richTextHeader( text: "TOP SELLING PRODUCTS BY CATEGORY & MONTH", size: "SMALL" ) } ), a!columnsLayout( columns: { a!columnLayout( contents: { a!dropdownField( label: "Time Period", labelPosition: "ABOVE", choiceLabels: rdrop(local!timePeriodLabels, 12 - local!currentMonth), choiceValues: rdrop(local!timePeriodValue, 12 - local!currentMonth), value: local!timePeriodSelection, saveInto: {local!timePeriodSelection} ), a!textField(labelPosition: "COLLAPSED", readOnly: true), a!forEach( items: local!salesByCategory.data, expression: a!cardLayout( contents: { a!sideBySideLayout( items: { a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: a!richTextItem( text: index(index(local!salesByCategory.data, "productLine"), fv!index, ""), style: "STRONG" ) ) ), a!sideBySideItem( item: a!richTextDisplayField( labelPosition: "COLLAPSED", value: { a!richTextItem( text: a!currency(isoCode: "USD", value: fv!item.sales_sum, decimalPlaces: 0, format: "SYMBOL"), size: "MEDIUM" ) }, align: "RIGHT" ), width: "MINIMIZE" ) }, alignVertical: "MIDDLE" ) }, link: if( local!selectedCategory = index(index(local!salesByCategory.data, "productLine"), fv!index, ""), {}, a!dynamicLink( value: index(index(local!salesByCategory.data, "productLine"), fv!index, ""), saveInto: local!selectedCategory ) ), style: if( local!selectedCategory = index(index(local!salesByCategory.data, "productLine"), fv!index, ""), "ACCENT", "NONE" ), marginBelow: "STANDARD" ) ) }, width: "NARROW_PLUS" ), a!columnLayout( contents: { { a!barChartField( categories: index(local!salesByCategoryAndProduct.data, "productCode"), series: { a!chartSeries( label: "Total Sales", data: index(local!salesByCategoryAndProduct.data, "sales_sum") ) }, stacking: "NORMAL", showLegend: false, showTooltips: true, colorScheme: "SUNSET" ) } }, width: "AUTO" ) } ) } ), a!columnLayout( contents: { a!richTextDisplayField( value: { a!richTextHeader( text: "SALES PERFORMANCE: YEAR TO DATE VS. PREVIOUS YEAR TO DATE", size: "SMALL" ) } ), a!columnChartField( categories: a!forEach( items: local!tyMonthDataSubset.data, expression: text( date( fv!item.orderDate_year, fv!item.orderDate_month, 1 ), "mmmm" ) ), series: { a!chartSeries( label: "Previous Year to Date Sales", data: index(local!lyMonthDataSubset.data, "sales_sum", null) ), a!chartSeries( label: "Current Year to Date Sales", data: index(local!tyMonthDataSubset.data, "sales_sum", null) ) }, stacking: "NONE", showLegend: true, showTooltips: true, labelPosition: "ABOVE", colorScheme: "SUNSET" ) } ) }, stackWhen: { "PHONE", "TABLET_PORTRAIT", "TABLET_LANDSCAPE" } ) } ) } Feedback Was this page helpful? SHARE FEEDBACK Loading...