YCharts

YCharts is a light and extensible chart library for Jetpack Compose system. It comprises two main modules:

  • YChartslib (Chart components for Jetpack Compose)
  • app (sample app to showcase chart components)

Adding YCharts to your project:

You can add automatically the library via Maven:

Gradle:

implementation 'co.yml:ycharts:1.0.0'

Modules

The following table outlines the modules included in this library:

Artifact Description
axis Includes the horizontal and vertical axis components along with the math engines.
charts Includes the all the chart components i.e: Line, Bar, Combined, Pie & Donut etc. also the math engines
chartcontainer Provides the base container to draw any chart inside it with scroll tap feature etc out of the box.
piechart Includes all the 360′ chart components i.e Pie, Donut charts etc.

Sample app

Included in this repository is a sample app with multiple charts with different styling in each section. Studying the source code of the app will give you a deep understanding of how to use YCharts, including customizing and styling the charts. All of the charts i.e line, bar, groupedBar, pie & donut are implemented in the sample app.

Basic example

Let’s see how we can use the chart components and style them with available customization options.

  1. Line Chart:

    • Create list of points with x & y co-ordinates using Point data class.

    val pointsData: List<Point> =
     listOf(Point(0f, 40f), Point(1f, 90f), Point(2f, 0f), Point(3f, 60f), Point(4f, 10f))
    • Initialize X and Y Axis builders using the AxisData data class.

       val xAxisData = AxisData.Builder()
     .axisStepSize(100.dp)
     .steps(pointsData.size - 1)
     .labelData { i -> i.toString() }
     .labelAndAxisLinePadding(15.dp)
     .build()
   
  val yAxisData = AxisData.Builder()
     .steps(steps)
     .labelAndAxisLinePadding(20.dp)
     .labelData { i ->
         val yScale = 100 / steps
         (i * yScale).formatToSinglePrecision()
     }.build()
    • Initialize the Line chart data with axis and other line related styling using LineChartData data class.

    val lineChartData = LineChartData(
     linePlotData = LinePlotData(
         lines = listOf(
             Line(
                 dataPoints = pointsData,
                 LineStyle(),
                 IntersectionPoint(),
                 SelectionHighlightPoint(),
                 ShadowUnderLine(),
                 SelectionHighlightPopUp()
             )
         ),
     ),
     xAxisData = xAxisData,
     yAxisData = yAxisData,
     gridLines = GridLines()
 )
    • Finally use the LineChart Component to render the line chart with the above input params.

    LineChart(
     modifier = Modifier
         .fillMaxWidth()
         .height(300.dp),
     lineChartData = lineChartData
 )

    Line chart looks like this!

  2. Bar Chart:

    • Create list of barChartData using the random generator extension and BarData data class

      val barChartData = DataUtils.getBarChartData(barChartListSize, maxRange)

    • Initialize X and Y Axis builders using the AxisData data class.

         val xAxisData = AxisData.Builder()
     .axisStepSize(30.dp)
     .steps(barChartData.size - 1)
     .bottomPadding(40.dp)
     .axisLabelAngle(20f)
     .labelData { index -> barData[index].label }
     .build()
   
  val yAxisData = AxisData.Builder()
     .steps(yStepSize)
     .labelAndAxisLinePadding(20.dp)
     .axisOffset(20.dp)
     .labelData { index -> (index * (maxRange / yStepSize)).toString() }
     .build()
    • Initialize the Bar chart data with axis and other line related styling using BarChartData data class.

     val barChartData = BarChartData(
     chartData = barChartData,
     xAxisData = xAxisData,
     yAxisData = yAxisData,
     paddingBetweenBars = 20.dp,
     barWidth = 25.dp
 )
    • Last, use the BarChart Component to render the bar chart with the above input params.
    BarChart(modifier = Modifier.height(350.dp), barChartData = barChartData)

    Bar chart looks like this!

  3. Grouped Bar Chart:

    • Create list of grouped combinations of bar chart data using the random generator extension and BarPlotData data class

         val groupBarPlotData = BarPlotData(
                   groupBarList = DataUtils.getGroupBarChartData(
                       barChartListSize,
                       maxRange,
                       eachGroupBarSize
                   ),
                   barColorPaletteList = getColorPaletteList(barSize)
               )

    • Initialize X and Y Axis builders using the AxisData data class.

            val xAxisData = AxisData.Builder()
            .axisStepSize(30.dp)
            .steps(groupBarData.size - 1)
            .bottomPadding(40.dp)
            .labelData { index -> groupBarData[index].label }
            .build()
   
 val yAxisData = AxisData.Builder()
            .steps(yStepSize)
            .labelAndAxisLinePadding(20.dp)
            .axisOffset(20.dp)
            .labelData { index -> (index * (maxRange / yStepSize)).toString() }
            .build()
    • Initialize the group bar chart data with axis and other line related styling using GroupBarChartData data class.

       val groupBarChartData = GroupBarChartData(
                     barPlotData = groupBarPlotData,
                     xAxisData = xAxisData,
                     yAxisData = yAxisData
                 )
    • Use the GroupBarChart Component to render the bar chart with the above input params.
    GroupBarChart(modifier = Modifier.height(300.dp), groupBarChartData = groupBarChartData)

    Grouped Bar chart looks like this!

  4. Pie Chart:

    • Create list of slices using the PieChartData data class.

       val pieChartData = PieChartData(
    slices = listOf(
        PieChartData.Slice("SciFi", 65f, Color(0xFF333333)),
        PieChartData.Slice("Comedy", 35f, Color(0xFF666a86)),
        PieChartData.Slice("Drama", 10f, Color(0xFF95B8D1)),
        PieChartData.Slice("Romance", 40f, Color(0xFFF53844))
    )
  )
    • Initialize the pie chart config with PieChartConfig data class inorder to achieve styling and configurations related to pie chart

      val pieChartConfig = PieChartConfig(
    percentVisible = true,
    isAnimationEnable = true,
    showSliceLabels = false,
    animationDuration = 1500
)
    • Finally, use the PieChart component to render the chart.

    PieChart(modifier = Modifier
         .width(400.dp)
         .height(400.dp),
     pieChartData,
     pieChartConfig
 )

    Pie chart looks like this!

  5. Donut Chart:

    • Similar to pie chart here we need create list of slices using the PieChartData data class.

        val donutChartData = PieChartData(
    slices = listOf(
        PieChartData.Slice("HP", 15f, Color(0xFF5F0A87)),
        PieChartData.Slice("Dell", 30f, Color(0xFF20BF55)),
        PieChartData.Slice("Lenovo", 40f,  Color(0xFFEC9F05)),
        PieChartData.Slice("Asus", 10f, Color(0xFFF53844))
    )
  )
    • Initialize the pie chart config with PieChartConfig data class inorder to achieve styling and configurations related to pie chart

    val donutChartConfig = PieChartConfig(
    percentVisible = true,
    percentageFontSize = 42.sp,
    strokeWidth = 120f,
    percentColor = Color.Black,
    activeSliceAlpha = .9f,
    isAnimationEnable = true
)
    • Finally, use the DonutPieChart component to render the chart.

    DonutPieChart( modifier = Modifier
         .fillMaxWidth()
         .height(500.dp),
     donutChartData,
     donutChartConfig
 )

    Donut chart looks like this!

  6. Combined Chart:

    • Similar to line and bar chart we can combine both entities in one chart, just need to initialize the line and bar plot data using the random generator extension and add styling related to individual component.

      val linePlotData = LinePlotData(
      lines = listOf(
        Line(
            DataUtils.getLineChartData(listSize, maxRange = 100),
            lineStyle = LineStyle(color = Color.Blue),
            intersectionPoint = IntersectionPoint(),
            selectionHighlightPoint = SelectionHighlightPoint(),
            selectionHighlightPopUp = SelectionHighlightPopUp()
        ),
        Line(
            DataUtils.getLineChartData(listSize, maxRange),
            lineStyle = LineStyle(color = Color.Black),
            intersectionPoint = IntersectionPoint(),
            selectionHighlightPoint = SelectionHighlightPoint(),
            selectionHighlightPopUp = SelectionHighlightPopUp()
        )
    )
)

val barPlotData = BarPlotData(
    groupBarList = DataUtils.getGroupBarChartData(listSize, maxValueRange, barSize),
    barStyle = BarStyle(barWidth = 35.dp),
    barColorPaletteList = colorPaletteList
 )

  • Initialize X and Y Axis builders using the AxisData data class.

    val xAxisData = AxisData.Builder()
  .axisStepSize(30.dp)
  .steps(maxOf(barChartData.size - 1, lineChartData.size - 1))
  .bottomPadding(40.dp)
  .labelData { index -> index.toString() }
  .build()
val yAxisData = AxisData.Builder()
  .steps(yStepSize)
  .labelAndAxisLinePadding(20.dp)
  .axisOffset(20.dp)
  .labelData { index -> (index * (maxRange / yStepSize)).toString() }
  .build()
    • Initialize the combined chart config data with CombinedChartData data class inorder to achieve styling and configurations related to same.

val combinedChartData = CombinedChartData( combinedPlotDataList = listOf(barPlotData, linePlotData), xAxisData = xAxisData, yAxisData = yAxisData ) “`

  • Finally, use the CombinedChart component to render the chart. 

    CombinedChart(
      modifier = Modifier.height(400.dp),
      combinedCharthData = combinedChartData
  )

_Note_ : To show legends infomartion related to bar, `Legends` component can be used.

Combined bar with line chart looks like this!

Accessibility Support

To interact with your device with touch and spoken feedback, you can turn on the TalkBack screen reader. TalkBack describes the graphs/charts when tapped on the graph container. Compose views by deafult supports accessibility services, but for views drawn using canvas has no straight forward approach as of now, hence all our graph components supports an accessibility popup out of the box that will be shown over the graph with tapped on the container, with all the values described in an order to support accessibility services. User will be able to scroll the popup and find all the points, bars, slices or combined values in a descriptive manner, where user can tap and talkback would read it out loud.

fig (a)

fig (b)

Here fig(a) represents the line graph with the container being highlighted & fig(b) represents the accessibility sheet with all values laid out in detail so that talkback can describe the graph values. *Note*: All the descriptions that are visible in the accessibility popup can be customized to the required string.

License

    Copyright 2022 YCharts

    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.
    You may obtain a copy of the License at

        http://www.apache.org/licenses/LICENSE-2.0

    Unless required by applicable law or agreed to in writing, software
    distributed under the License is distributed on an "AS IS" BASIS,
    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    See the License for the specific language governing permissions and
    limitations under the License.

GitHub

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