Evan Marie Carr
May 15, 2024
Summary:
Embark on an exciting journey exploring Recharts, a powerful and flexible React charting library, and discover how Recharts offers a wider range of functionality and customization options, making it a valuable tool for creating stunning data visualizations.
Data Visualization
Remix
React
Recharts
Overview
Greetings, fellow data visualization enthusiasts! In my last post, I took you on a journey through React-ChartJS-2, a popular React charting library. While it provided a solid foundation for creating charts, I couldn't help but feel a bit limited in terms of functionality, mainly due to the minimal documentation. When I decided to dive deeper into React-ChartJs-2, I got a bit frustrated. I love customizing extensively. And without in-depth documentation, customization can get challenging, trying to guess at the best ways to get the desired results. That's when I decided to give Recharts a try. Recharts is a powerful and flexible React charting library that offers a wide range of chart types, customization options, and interactivity features.
Now, I'll be honest, customizing charts in Recharts can be a bit clumsy at times. It's not always as intuitive as one might hope. However, the sheer power and flexibility it provides make up for any minor inconveniences. Plus, with a little bit of tinkering and exploration, if you are like me, you'll be creating chart masterpieces in no time!
As we go, we'll dive into these various chart types, including line graphs, bar graphs, scatterplots, pie charts, radar charts, and even combination charts. Each chart type will be accompanied by examples and code snippets, allowing you to follow along and create you own visualizations easily with the foundation I will provide.
While Recharts may have a slight learning curve when it comes to customization, its extensive capabilities and flexibility make it a worthwhile investment for anyone who has the need or desire to create truly communicative data visualizations. By the end of this post, you will have a solid understanding of how to use Recharts to create visually appealing and interactive charts that bring your data to life.
So, get ready to level up your data visualization skills and explore the world of Recharts! Prepare to be impressed by the possibilities this library offers.
Helper Components
To facilitate the creation of various chart types and configurations, I created a set of helper components that encapsulate common chart elements and functionalities. These components serve as building blocks for the examples and provide a foundation for creating more customized visualizations.
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CustomizedXAxisTick: Customizes the tick labels on the X-axis of a chart, allowing control over their position, color, font size, and rotation.
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CustomizedYAxisTick: Customizes the tick labels on the Y-axis of a chart, providing options to control their position, color, font size, and formatting (e.g., displaying values as currency).
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CustomizedBiaxialAxisTick: Similar to CustomizedYAxisTick, this function customizes the tick labels on the biaxial axis of a chart, with options to control their position, color, font size, and formatting.
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CustomTooltip: Customizes the appearance and content of the tooltip that appears when hovering over data points in a chart. It allows you to display additional information, such as the month label and the name and value of each data entry, with options to format the values as currency.
Line Graphs
Line graphs are excellent for visualizing trends, changes, and patterns over time. They are particularly useful when you have continuous data points that are connected in a meaningful way. Line graphs allow you to easily spot increases, decreases, or fluctuations in your data. They are commonly used to represent stock prices, temperature changes, or website traffic over a specific period.
The above component will be used for the following four examples of line graphs. The component takes in various props to customize the appearance and behavior of the line graph, including the data, data lines, title, axis labels, data keys, colors, and more. By passing different configurations to the component, you can create a wide range of line graphs tailored to your specific needs all with one component.
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The LineChart component serves as the main container for the line graph.
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Inside the LineChart, you can define various sub-components to customize the appearance and behavior of the graph.
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The LineChartcomponent renders the grid lines in the background of the chart, providing a visual reference for the data points.
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The XAxis and YAxis components represent the horizontal and vertical axes of the graph, respectively.
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You can specify the data key for each axis using the dataKey prop.
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The appearance of the axis ticks can be customized using the tick prop.
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The Tooltip component displays additional information when hovering over the data points, providing insights into the specific values at each point.
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The Legend component is used to display a legend for the different lines in the graph, helping users identify which line represents which data series.
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The actual data lines are rendered using the Line component.
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Each Line represents a specific data series and is mapped to a unique data key using the dataKey prop.
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The appearance of the lines can be customized by specifying the stroke color, strokeDasharray for dashed lines, and activeDot to highlight the active data point.
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In the provided example, the dataLines prop is used to dynamically render multiple Line components based on the specified data keys, allowing for the creation of a line graph with multiple data series.
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The data prop passed to the LineChart component represents the actual data used to plot the graph.
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Each object in the data array corresponds to a single data point, with properties matching the data keys used in the Line components and the XAxis and YAxis components.
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Recharts provides a declarative and flexible way to create line graphs by composing various sub-components within the LineChart component. The combination of XAxis, YAxis, Tooltip, Legend, and Line components allows you to customize the appearance and behavior of the graph, while the data prop provides the underlying data to be plotted.
Line Graph One: A simple line graph with three data lines
Coffee Corner Financials 2023
Months of 2023
Financials
Line Graph Two: Numerous data lines with varying stroke dash patterns
Toy Sales by Week
Weeks
Toy Sales
Line Graph Three: Vertical line graph with category and number axes flipped
Product Sales by Quarter
Product Sales
Products
Line Graph Four: Biaxial line graph comparing attendance and temperature
Amphitheater Attendance-Temperature Comparison 2023
Months of 2023
Attendance
Temperature (°F)
Area Graphs
Area graphs are excellent for visualizing trends and changes in data over time, while also representing the magnitude of the values. They provide a clear and visually appealing way to showcase the cumulative data in a series. Area graphs are effective when you want to emphasize the overall pattern and progression of the data, as well as the total value at each point. The filled area under the line helps to highlight the volume or quantity being measured. Area graphs are often used to display data such as website traffic, sales volume, market share, or population growth over a specific period. They are particularly useful when you want to compare multiple data series and see how they stack up against each other. By using different colors or transparencies for each series, area graphs allow for easy comparison and identification of the relative contributions of each category to the total value.
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The AreaChart component serves as the main container for the area graph.
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Inside the AreaChart, you can define various sub-components to customize the appearance and behavior of the graph.
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The CartesianGrid component renders the grid lines in the background of the chart, providing a visual reference for the data points.
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The XAxis and YAxis components represent the horizontal and vertical axes of the graph, respectively.
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You can specify the data key for each axis using the dataKey prop.
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The appearance of the axis ticks can be customized using the tick prop.
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The Tooltip component displays additional information when hovering over the data points, providing insights into the specific values at each point.
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The Legend component is used to display a legend for the different area series, helping users identify which area represents which data series.
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The actual area series are rendered using the Area component.
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Each Area component represents a specific data series and is mapped to a unique data key using the dataKey prop.
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The appearance of the area series can be customized by specifying the stroke color for the line and the fill color for the filled area.
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The activeDot prop allows you to customize the appearance of the dots when hovering over the data points.
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In the provided example, the dataLines prop is used to dynamically render multiple Area components based on the specified data keys, allowing for the creation of an area graph with multiple data series.
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The data prop passed to the AreaChart component represents the actual data used to plot the graph.
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Each object in the data array corresponds to a single data point, with properties matching the data keys used in the Area components and the XAxis and YAxis components.
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The chart can be customized further by specifying props such as isVertical for a vertical layout, useDollar for displaying dollar values, biaxial for a biaxial chart, and useStrokeDash for dashed stroke lines.
Area Graph: A simple area graph with three data lines
Coffee Corner Financials 2023
Months of 2023
Financials
Bar Charts
Bar charts are ideal for comparing categories or discrete values. They provide a clear and intuitive way to showcase the differences between various groups or items. Bar charts are effective when you want to highlight the highest or lowest values, or when you need to compare the relative sizes of different categories. They are often used to display sales figures, survey results, or population demographics.
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The BarChart component serves as the main container for the bar graph.
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Inside the BarChart, you can define various sub-components to customize the appearance and behavior of the graph.
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The CartesianGrid component renders the grid lines in the background of the chart, providing a visual reference for the bars.
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The XAxis andYAxis components represent the horizontal and vertical axes of the graph, respectively.
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You can specify the data key for each axis using the dataKey prop.
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The appearance of the axis ticks can be customized using the tick prop.
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The Tooltip component displays additional information when hovering over the bars, providing insights into the specific values of each bar.
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The Legend component is used to display a legend for the different bar series, helping users identify which bar represents which data series.
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The actual bars are rendered using the Bar component.
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Each Bar represents a specific data series and is mapped to a unique data key using the dataKey prop.
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The appearance of the bars can be customized by specifying the fill color, stroke color, and custom shapes using the shape prop.
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The Brush component can be added to enable interactive zooming and panning of the chart.
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Bar labels can be displayed by configuring the label prop on the Bar component, specifying the position and style of the labels.
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Stacked bars can be created by assigning the same stackId to multiple Bar components.
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The activeBar prop allows you to customize the appearance of the bar when it is actively hovered or selected.
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The background prop can be used to add a background color or pattern to the bars.
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In the provided example, the dataBars prop is used to dynamically render multiple Bar components based on the specified data keys, allowing for the creation of a bar graph with multiple data series.
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The data prop passed to the BarChart component represents the actual data used to plot the graph.
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Each object in the data array corresponds to a single data point, with properties matching the data keys used in the Bar components and the XAxis and YAxis components.
Bar Graph One: A simple bar graph with three data bars (compare to line graph 1)
Coffee Corner Financials 2023
Months of 2023
Financials
Bar Graph Two: A stacked bar graph, allowing for the comparison of different categories or groups within each bar while still showing the overall total
Coffee Corner Financials 2023
Months of 2023
Financials
Bar Graph Three: A mixed bar chart with two stacked and one independent bar
Coffee Corner Financials 2023
Months of 2023
Financials
Bar Graph Four: Bar graph with brush component allowing interactive zooming
Top Student Scores
Students
Scores
Bar Graph Four A: the shape of the bar set as triangle, and the label is positioned at the top of the bar
Top Student Scores
Students
Scores
Bar Graph Four B: the shape of the bar is set as circle, and the label is positioned in the center with the bar background set to true
Top Student Scores
Students
Scores
Bar Graph Four C: the shape of the bar is set as diamond, and the label is positioned in the center with the bar background set to true
Top Student Scores
Students
Scores
Bar Graph Eight: bar graph accounting for negative values as well as positive
Positive and Negative Values
Categories
Values
Bar Graph Nine: biaxial barchart, comparing attendance on the left y axis and temperature on the right (compare to line graph four)
Amphitheater Attendance-Temperature Comparison 2023
Months of 2023
Attendance
Temperature (°F)
Scatterplots
Scatterplots are powerful tools for visualizing the relationship between two variables. They display data points on a two-dimensional graph, where each point represents a single observation. Scatterplots are useful for identifying patterns, correlations, or outliers in your data. They are commonly used in scientific research, market analysis, or any situation where you want to explore the connection between two quantitative variables.
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The ScatterChart component serves as the main container for the scatterplot.One
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Inside the ScatterChart, you can define various sub-components to customize the appearance and behavior of the plot.
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The CartesianGrid component renders the grid lines in the background of the chart, providing a visual reference for the data points.
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The XAxis and YAxis components represent the horizontal and vertical axes of the plot, respectively.
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You can specify the data key for each axis using the dataKey prop.
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The appearance of the axis ticks can be customized using the tick prop.
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The Tooltip component displays additional information when hovering over the data points, providing insights into the specific values of each point.
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The Legend component is used to display a legend for the different scatter series, helping users identify which series represents which data.
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The actual scatter points are rendered using the Scatter component.
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Each Scatter component represents a specific data series and is mapped to a unique name prop.
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The appearance of the scatter points can be customized by specifying the fill color and the shape prop.
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The data prop passed to each Scatter component represents the actual data points for that series.
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Each data point is an object containing the x and y coordinates.
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In the provided example, the data prop is an array of objects, where each object represents a scatter series with a name and an array of data points.
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The scatterplot can be customized further by specifying the xAxisType and yAxisType props to determine the type of data on each axis (e.g., "number" or "category").
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Additional customization options include:
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Setting the isVertical prop to change the orientation of the plot.
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Using the useDollar prop to format the tooltip values as currency.
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Enabling a biaxial chart by setting the biaxial prop and providing a biaxialDataKey for the second y-axis.
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Customizing the colors of the scatter points using the colorList prop.
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Modifying the stroke color of the y-axis ticks using the yTickStroke and biaxialTickStroke props.
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Enabling different shapes for the scatter points using the useShapes and shapeList props.
Scatterplot One: simple scatterplot with multiple data series
Combined Metrics
Scatterplot Two: scatterplot using custom shapes
Combined Metrics
Pie Charts
Pie charts are used to represent the proportions or percentages of different categories within a whole. They are effective when you want to show the relative sizes of various segments or slices. Pie charts are visually appealing and can quickly convey the distribution of data. However, they can become less readable when there are too many categories or when the proportions are very similar. Pie charts are often used to display market share, budget allocations, or survey responses.
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The PieChart component serves as the main container for the pie chart.
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Inside the PieChart, you can define various sub-components to customize the appearance and behavior of the chart.
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The Pie component represents a pie or donut chart and is used to render the slices of the chart.
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Each Pie component is associated with a specific data set using the data prop.
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The dataKey prop specifies the key in the data object that holds the values for each slice.
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The cx and cy props define the center coordinates of the pie.
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The outerRadius prop sets the outer radius of the pie, determining its size.
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The innerRadius prop can be used to create a donut chart by specifying the inner radius.
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The Cell component is used within the Pie component to customize the appearance of each slice.
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Each Cell component is mapped to a specific data entry and can be customized individually.
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The fill prop is used to set the color of each slice.
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The Legend component is used to display a legend for the pie chart, showing the categories or labels for each slice.
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The payload prop of the Legend component is used to provide the data for the legend.
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Each legend item is defined as an object with properties like value (label), type (icon type), and color.
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The label prop can be used to display labels on each slice of the pie chart.
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The label can be a simple text or a custom render function that receives the data entry as a parameter.
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In the provided example, two separate Pie components are used to create a nested pie chart.
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The first Pie component represents the inner pie and is associated with the data01 prop.
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The second Pie component represents the outer donut and is associated with the data02 prop.
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The outerRadius and innerRadius props are adjusted to create the desired spacing between the two pies.
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The chart can be customized further by specifying the height prop to set the height of the chart container.
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The radius prop is used to control the overall size of the pie chart.
Pie Graph: extended pie graph showing main categories along with subcategory values
Example Pie Chart
Radar Charts
Radar charts, also known as spider charts or star charts, are used to compare multiple variables across different categories. They display data points on a circular grid, with each variable represented by an axis radiating from the center. Radar charts are useful when you want to assess the relative strengths or weaknesses of different entities across various dimensions. They are commonly used in sports analysis, product comparisons, or skill evaluations.
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The RadarChart component serves as the main container for the radar chart.
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Inside the RadarChart, you can define various sub-components to customize the appearance and behavior of the chart.
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The PolarGrid component renders the grid lines in the background of the chart, providing a visual reference for the data points.
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The PolarAngleAxis component represents the angular axis of the radar chart.
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It is used to display the categories or labels around the perimeter of the chart.
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The dataKey prop specifies the key in the data object that holds the category names.
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The appearance of the axis labels can be customized using the stroke prop.
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The PolarRadiusAxis component represents the radial axis of the radar chart.
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It is used to display the scale or values along the radial axis.
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The domain prop is used to specify the range of values for the radial axis.
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The Radar component is used to render the actual data points and the area filled by the data.
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Each Radar component represents a specific data series and is mapped to a unique dataKey prop.
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The appearance of the radar area can be customized using the stroke, fill, and fillOpacity props.
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The Tooltip component is used to display additional information when hovering over the data points.
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It can be customized using a custom render function passed to the content prop.
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In the provided example, multiple Radar components are dynamically rendered based on the keys present in the data object.
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The Object.keys() method is used to extract the keys from the data object.
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The filter() method is used to exclude specific keys that are not meant to be plotted.
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Each Radar component is assigned a unique color based on the colors array.
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The chart can be customized further by specifying the height prop to set the height of the chart container.
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The axisLabel prop is used to specify the key in the data object that holds the category names for the angular axis.
Radar Chart: simple radar graph showing the percentages of different languages spoken in a given population
Languages Spoken by Population Percentage
Combination Charts
Combination charts allow you to combine multiple chart types into a single visualization. They are useful when you want to present different types of data or highlight different aspects of your analysis. For example, you can combine a line graph and a bar chart to show the relationship between two variables while also comparing categories. Combination charts provide flexibility and can help you tell a more comprehensive story with your data.
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The ComposedChart component serves as the main container for the combination chart.
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Inside the ComposedChart, you can define various sub-components to create a chart that combines multiple chart types.
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The XAxis and YAxis components represent the horizontal and vertical axes of the chart, respectively.
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The dataKey prop specifies the key in the data object that corresponds to the axis values.
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The type prop determines the type of the axis (e.g., "number" or "category").
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The appearance of the axis ticks can be customized using the tick prop.
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The CartesianGrid component renders the grid lines in the background of the chart, providing a visual reference for the data points.
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The Tooltip component is used to display additional information when hovering over the data points.
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It can be customized using a custom render function passed to the content prop.
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The Legend component is used to display a legend for the different data series in the chart.
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The Area component is used to render an area chart within the combination chart.
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It is defined with a type prop to specify the curve type (e.g., "monotone" for a smooth curve).
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The dataKey prop specifies the key in the data object that corresponds to the area values.
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The appearance of the area can be customized using the fill and stroke props.
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The Bar component is used to render a bar chart within the combination chart.
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The dataKey prop specifies the key in the data object that corresponds to the bar values.
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The barSize prop determines the width of the bars.
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The appearance of the bars can be customized using the fill prop.
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The Line component is used to render a line chart within the combination chart.
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It is defined with a type prop to specify the curve type (e.g., "monotone" for a smooth curve).
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The dataKey prop specifies the key in the data object that corresponds to the line values.
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The appearance of the line can be customized using the stroke prop.
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The Scatter component is used to render a scatter plot within the combination chart.
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The dataKey prop specifies the key in the data object that corresponds to the scatter values.
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The appearance of the scatter points can be customized using the fill prop.
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The chart can be customized further by specifying various props such as useDollar for formatting tooltip values as currency, biaxial for enabling a biaxial chart, and colorList for specifying custom colors for the chart components.
Combination Graph: exhibiting a combination of bar, line, area, and scatter plots for different categories and values
Combination Graph
months
quantities
In Conclusion
So, now that we have explored the powerful and flexible Recharts library for creating stunning data visualizations in React and Remix, are you ready to go graphs some digits? While there may be a learning curve when it comes to customization, the extensive features and flexibility offered by Recharts make it a valuable tool for data visualization enthusiasts. By utilizing the knowledge gained from this post, you can create visually appealing and informative charts that effectively communicate your data stories. So go ahead, experiment with Recharts, and unleash the power of data visualization in your React and Remix projects!
Evan Marie Carr
May 15, 2024
Data Visualization
Remix
React
Recharts
Summary:
Embark on an exciting journey exploring Recharts, a powerful and flexible React charting library, and discover how Recharts offers a wider range of functionality and customization options, making it a valuable tool for creating stunning data visualizations.
Overview
Greetings, fellow data visualization enthusiasts! In my last post, I took you on a journey through React-ChartJS-2, a popular React charting library. While it provided a solid foundation for creating charts, I couldn't help but feel a bit limited in terms of functionality, mainly due to the minimal documentation. When I decided to dive deeper into React-ChartJs-2, I got a bit frustrated. I love customizing extensively. And without in-depth documentation, customization can get challenging, trying to guess at the best ways to get the desired results. That's when I decided to give Recharts a try. Recharts is a powerful and flexible React charting library that offers a wide range of chart types, customization options, and interactivity features.
Now, I'll be honest, customizing charts in Recharts can be a bit clumsy at times. It's not always as intuitive as one might hope. However, the sheer power and flexibility it provides make up for any minor inconveniences. Plus, with a little bit of tinkering and exploration, if you are like me, you'll be creating chart masterpieces in no time!
As we go, we'll dive into these various chart types, including line graphs, bar graphs, scatterplots, pie charts, radar charts, and even combination charts. Each chart type will be accompanied by examples and code snippets, allowing you to follow along and create you own visualizations easily with the foundation I will provide.
While Recharts may have a slight learning curve when it comes to customization, its extensive capabilities and flexibility make it a worthwhile investment for anyone who has the need or desire to create truly communicative data visualizations. By the end of this post, you will have a solid understanding of how to use Recharts to create visually appealing and interactive charts that bring your data to life.
So, get ready to level up your data visualization skills and explore the world of Recharts! Prepare to be impressed by the possibilities this library offers.
Helper Components
To facilitate the creation of various chart types and configurations, I created a set of helper components that encapsulate common chart elements and functionalities. These components serve as building blocks for the examples and provide a foundation for creating more customized visualizations.
￮
CustomizedXAxisTick: Customizes the tick labels on the X-axis of a chart, allowing control over their position, color, font size, and rotation.
￮
CustomizedYAxisTick: Customizes the tick labels on the Y-axis of a chart, providing options to control their position, color, font size, and formatting (e.g., displaying values as currency).
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CustomizedBiaxialAxisTick: Similar to CustomizedYAxisTick, this function customizes the tick labels on the biaxial axis of a chart, with options to control their position, color, font size, and formatting.
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CustomTooltip: Customizes the appearance and content of the tooltip that appears when hovering over data points in a chart. It allows you to display additional information, such as the month label and the name and value of each data entry, with options to format the values as currency.
Line Graphs
Line graphs are excellent for visualizing trends, changes, and patterns over time. They are particularly useful when you have continuous data points that are connected in a meaningful way. Line graphs allow you to easily spot increases, decreases, or fluctuations in your data. They are commonly used to represent stock prices, temperature changes, or website traffic over a specific period.
The above component will be used for the following four examples of line graphs. The component takes in various props to customize the appearance and behavior of the line graph, including the data, data lines, title, axis labels, data keys, colors, and more. By passing different configurations to the component, you can create a wide range of line graphs tailored to your specific needs all with one component.
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The LineChart component serves as the main container for the line graph.
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Inside the LineChart, you can define various sub-components to customize the appearance and behavior of the graph.
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The LineChartcomponent renders the grid lines in the background of the chart, providing a visual reference for the data points.
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The XAxis and YAxis components represent the horizontal and vertical axes of the graph, respectively.
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You can specify the data key for each axis using the dataKey prop.
⏵
The appearance of the axis ticks can be customized using the tick prop.
￮
The Tooltip component displays additional information when hovering over the data points, providing insights into the specific values at each point.
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The Legend component is used to display a legend for the different lines in the graph, helping users identify which line represents which data series.
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The actual data lines are rendered using the Line component.
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Each Line represents a specific data series and is mapped to a unique data key using the dataKey prop.
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The appearance of the lines can be customized by specifying the stroke color, strokeDasharray for dashed lines, and activeDot to highlight the active data point.
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In the provided example, the dataLines prop is used to dynamically render multiple Line components based on the specified data keys, allowing for the creation of a line graph with multiple data series.
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The data prop passed to the LineChart component represents the actual data used to plot the graph.
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Each object in the data array corresponds to a single data point, with properties matching the data keys used in the Line components and the XAxis and YAxis components.
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Recharts provides a declarative and flexible way to create line graphs by composing various sub-components within the LineChart component. The combination of XAxis, YAxis, Tooltip, Legend, and Line components allows you to customize the appearance and behavior of the graph, while the data prop provides the underlying data to be plotted.
Line Graph One: A simple line graph with three data lines
Coffee Corner Financials 2023
Months of 2023
Financials
Line Graph Two: Numerous data lines with varying stroke dash patterns
Toy Sales by Week
Weeks
Toy Sales
Line Graph Three: Vertical line graph with category and number axes flipped
Product Sales by Quarter
Product Sales
Products
Line Graph Four: Biaxial line graph comparing attendance and temperature
Amphitheater Attendance-Temperature Comparison 2023
Months of 2023
Attendance
Temperature (°F)
Area Graphs
Area graphs are excellent for visualizing trends and changes in data over time, while also representing the magnitude of the values. They provide a clear and visually appealing way to showcase the cumulative data in a series. Area graphs are effective when you want to emphasize the overall pattern and progression of the data, as well as the total value at each point. The filled area under the line helps to highlight the volume or quantity being measured. Area graphs are often used to display data such as website traffic, sales volume, market share, or population growth over a specific period. They are particularly useful when you want to compare multiple data series and see how they stack up against each other. By using different colors or transparencies for each series, area graphs allow for easy comparison and identification of the relative contributions of each category to the total value.
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The AreaChart component serves as the main container for the area graph.
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Inside the AreaChart, you can define various sub-components to customize the appearance and behavior of the graph.
￮
The CartesianGrid component renders the grid lines in the background of the chart, providing a visual reference for the data points.
￮
The XAxis and YAxis components represent the horizontal and vertical axes of the graph, respectively.
⏵
You can specify the data key for each axis using the dataKey prop.
⏵
The appearance of the axis ticks can be customized using the tick prop.
￮
The Tooltip component displays additional information when hovering over the data points, providing insights into the specific values at each point.
￮
The Legend component is used to display a legend for the different area series, helping users identify which area represents which data series.
￮
The actual area series are rendered using the Area component.
⏵
Each Area component represents a specific data series and is mapped to a unique data key using the dataKey prop.
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The appearance of the area series can be customized by specifying the stroke color for the line and the fill color for the filled area.
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The activeDot prop allows you to customize the appearance of the dots when hovering over the data points.
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In the provided example, the dataLines prop is used to dynamically render multiple Area components based on the specified data keys, allowing for the creation of an area graph with multiple data series.
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The data prop passed to the AreaChart component represents the actual data used to plot the graph.
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Each object in the data array corresponds to a single data point, with properties matching the data keys used in the Area components and the XAxis and YAxis components.
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The chart can be customized further by specifying props such as isVertical for a vertical layout, useDollar for displaying dollar values, biaxial for a biaxial chart, and useStrokeDash for dashed stroke lines.
Area Graph: A simple area graph with three data lines
Coffee Corner Financials 2023
Months of 2023
Financials
Bar Charts
Bar charts are ideal for comparing categories or discrete values. They provide a clear and intuitive way to showcase the differences between various groups or items. Bar charts are effective when you want to highlight the highest or lowest values, or when you need to compare the relative sizes of different categories. They are often used to display sales figures, survey results, or population demographics.
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The BarChart component serves as the main container for the bar graph.
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Inside the BarChart, you can define various sub-components to customize the appearance and behavior of the graph.
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The CartesianGrid component renders the grid lines in the background of the chart, providing a visual reference for the bars.
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The XAxis andYAxis components represent the horizontal and vertical axes of the graph, respectively.
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You can specify the data key for each axis using the dataKey prop.
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The appearance of the axis ticks can be customized using the tick prop.
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The Tooltip component displays additional information when hovering over the bars, providing insights into the specific values of each bar.
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The Legend component is used to display a legend for the different bar series, helping users identify which bar represents which data series.
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The actual bars are rendered using the Bar component.
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Each Bar represents a specific data series and is mapped to a unique data key using the dataKey prop.
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The appearance of the bars can be customized by specifying the fill color, stroke color, and custom shapes using the shape prop.
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The Brush component can be added to enable interactive zooming and panning of the chart.
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Bar labels can be displayed by configuring the label prop on the Bar component, specifying the position and style of the labels.
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Stacked bars can be created by assigning the same stackId to multiple Bar components.
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The activeBar prop allows you to customize the appearance of the bar when it is actively hovered or selected.
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The background prop can be used to add a background color or pattern to the bars.
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In the provided example, the dataBars prop is used to dynamically render multiple Bar components based on the specified data keys, allowing for the creation of a bar graph with multiple data series.
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The data prop passed to the BarChart component represents the actual data used to plot the graph.
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Each object in the data array corresponds to a single data point, with properties matching the data keys used in the Bar components and the XAxis and YAxis components.
Bar Graph One: A simple bar graph with three data bars (compare to line graph 1)
Coffee Corner Financials 2023
Months of 2023
Financials
Bar Graph Two: A stacked bar graph, allowing for the comparison of different categories or groups within each bar while still showing the overall total
Coffee Corner Financials 2023
Months of 2023
Financials
Bar Graph Three: A mixed bar chart with two stacked and one independent bar
Coffee Corner Financials 2023
Months of 2023
Financials
Bar Graph Four: Bar graph with brush component allowing interactive zooming
Top Student Scores
Students
Scores
Bar Graph Four A: the shape of the bar set as triangle, and the label is positioned at the top of the bar
Top Student Scores
Students
Scores
Bar Graph Four B: the shape of the bar is set as circle, and the label is positioned in the center with the bar background set to true
Top Student Scores
Students
Scores
Bar Graph Four C: the shape of the bar is set as diamond, and the label is positioned in the center with the bar background set to true
Top Student Scores
Students
Scores
Bar Graph Eight: bar graph accounting for negative values as well as positive
Positive and Negative Values
Categories
Values
Bar Graph Nine: biaxial barchart, comparing attendance on the left y axis and temperature on the right (compare to line graph four)
Amphitheater Attendance-Temperature Comparison 2023
Months of 2023
Attendance
Temperature (°F)
Scatterplots
Scatterplots are powerful tools for visualizing the relationship between two variables. They display data points on a two-dimensional graph, where each point represents a single observation. Scatterplots are useful for identifying patterns, correlations, or outliers in your data. They are commonly used in scientific research, market analysis, or any situation where you want to explore the connection between two quantitative variables.
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The ScatterChart component serves as the main container for the scatterplot.One
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Inside the ScatterChart, you can define various sub-components to customize the appearance and behavior of the plot.
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The CartesianGrid component renders the grid lines in the background of the chart, providing a visual reference for the data points.
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The XAxis and YAxis components represent the horizontal and vertical axes of the plot, respectively.
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You can specify the data key for each axis using the dataKey prop.
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The appearance of the axis ticks can be customized using the tick prop.
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The Tooltip component displays additional information when hovering over the data points, providing insights into the specific values of each point.
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The Legend component is used to display a legend for the different scatter series, helping users identify which series represents which data.
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The actual scatter points are rendered using the Scatter component.
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Each Scatter component represents a specific data series and is mapped to a unique name prop.
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The appearance of the scatter points can be customized by specifying the fill color and the shape prop.
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The data prop passed to each Scatter component represents the actual data points for that series.
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Each data point is an object containing the x and y coordinates.
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In the provided example, the data prop is an array of objects, where each object represents a scatter series with a name and an array of data points.
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The scatterplot can be customized further by specifying the xAxisType and yAxisType props to determine the type of data on each axis (e.g., "number" or "category").
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Additional customization options include:
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Setting the isVertical prop to change the orientation of the plot.
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Using the useDollar prop to format the tooltip values as currency.
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Enabling a biaxial chart by setting the biaxial prop and providing a biaxialDataKey for the second y-axis.
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Customizing the colors of the scatter points using the colorList prop.
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Modifying the stroke color of the y-axis ticks using the yTickStroke and biaxialTickStroke props.
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Enabling different shapes for the scatter points using the useShapes and shapeList props.
Scatterplot One: simple scatterplot with multiple data series
Combined Metrics
Scatterplot Two: scatterplot using custom shapes
Combined Metrics
Pie Charts
Pie charts are used to represent the proportions or percentages of different categories within a whole. They are effective when you want to show the relative sizes of various segments or slices. Pie charts are visually appealing and can quickly convey the distribution of data. However, they can become less readable when there are too many categories or when the proportions are very similar. Pie charts are often used to display market share, budget allocations, or survey responses.
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The PieChart component serves as the main container for the pie chart.
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Inside the PieChart, you can define various sub-components to customize the appearance and behavior of the chart.
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The Pie component represents a pie or donut chart and is used to render the slices of the chart.
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Each Pie component is associated with a specific data set using the data prop.
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The dataKey prop specifies the key in the data object that holds the values for each slice.
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The cx and cy props define the center coordinates of the pie.
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The outerRadius prop sets the outer radius of the pie, determining its size.
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The innerRadius prop can be used to create a donut chart by specifying the inner radius.
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The Cell component is used within the Pie component to customize the appearance of each slice.
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Each Cell component is mapped to a specific data entry and can be customized individually.
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The fill prop is used to set the color of each slice.
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The Legend component is used to display a legend for the pie chart, showing the categories or labels for each slice.
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The payload prop of the Legend component is used to provide the data for the legend.
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Each legend item is defined as an object with properties like value (label), type (icon type), and color.
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The label prop can be used to display labels on each slice of the pie chart.
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The label can be a simple text or a custom render function that receives the data entry as a parameter.
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In the provided example, two separate Pie components are used to create a nested pie chart.
⏵
The first Pie component represents the inner pie and is associated with the data01 prop.
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The second Pie component represents the outer donut and is associated with the data02 prop.
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The outerRadius and innerRadius props are adjusted to create the desired spacing between the two pies.
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The chart can be customized further by specifying the height prop to set the height of the chart container.
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The radius prop is used to control the overall size of the pie chart.
Pie Graph: extended pie graph showing main categories along with subcategory values
Example Pie Chart
Radar Charts
Radar charts, also known as spider charts or star charts, are used to compare multiple variables across different categories. They display data points on a circular grid, with each variable represented by an axis radiating from the center. Radar charts are useful when you want to assess the relative strengths or weaknesses of different entities across various dimensions. They are commonly used in sports analysis, product comparisons, or skill evaluations.
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The RadarChart component serves as the main container for the radar chart.
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Inside the RadarChart, you can define various sub-components to customize the appearance and behavior of the chart.
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The PolarGrid component renders the grid lines in the background of the chart, providing a visual reference for the data points.
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The PolarAngleAxis component represents the angular axis of the radar chart.
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It is used to display the categories or labels around the perimeter of the chart.
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The dataKey prop specifies the key in the data object that holds the category names.
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The appearance of the axis labels can be customized using the stroke prop.
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The PolarRadiusAxis component represents the radial axis of the radar chart.
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It is used to display the scale or values along the radial axis.
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The domain prop is used to specify the range of values for the radial axis.
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The Radar component is used to render the actual data points and the area filled by the data.
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Each Radar component represents a specific data series and is mapped to a unique dataKey prop.
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The appearance of the radar area can be customized using the stroke, fill, and fillOpacity props.
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The Tooltip component is used to display additional information when hovering over the data points.
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It can be customized using a custom render function passed to the content prop.
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In the provided example, multiple Radar components are dynamically rendered based on the keys present in the data object.
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The Object.keys() method is used to extract the keys from the data object.
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The filter() method is used to exclude specific keys that are not meant to be plotted.
⏵
Each Radar component is assigned a unique color based on the colors array.
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The chart can be customized further by specifying the height prop to set the height of the chart container.
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The axisLabel prop is used to specify the key in the data object that holds the category names for the angular axis.
Radar Chart: simple radar graph showing the percentages of different languages spoken in a given population
Languages Spoken by Population Percentage
Combination Charts
Combination charts allow you to combine multiple chart types into a single visualization. They are useful when you want to present different types of data or highlight different aspects of your analysis. For example, you can combine a line graph and a bar chart to show the relationship between two variables while also comparing categories. Combination charts provide flexibility and can help you tell a more comprehensive story with your data.
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The ComposedChart component serves as the main container for the combination chart.
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Inside the ComposedChart, you can define various sub-components to create a chart that combines multiple chart types.
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The XAxis and YAxis components represent the horizontal and vertical axes of the chart, respectively.
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The dataKey prop specifies the key in the data object that corresponds to the axis values.
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The type prop determines the type of the axis (e.g., "number" or "category").
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The appearance of the axis ticks can be customized using the tick prop.
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The CartesianGrid component renders the grid lines in the background of the chart, providing a visual reference for the data points.
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The Tooltip component is used to display additional information when hovering over the data points.
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It can be customized using a custom render function passed to the content prop.
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The Legend component is used to display a legend for the different data series in the chart.
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The Area component is used to render an area chart within the combination chart.
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It is defined with a type prop to specify the curve type (e.g., "monotone" for a smooth curve).
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The dataKey prop specifies the key in the data object that corresponds to the area values.
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The appearance of the area can be customized using the fill and stroke props.
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The Bar component is used to render a bar chart within the combination chart.
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The dataKey prop specifies the key in the data object that corresponds to the bar values.
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The barSize prop determines the width of the bars.
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The appearance of the bars can be customized using the fill prop.
￮
The Line component is used to render a line chart within the combination chart.
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It is defined with a type prop to specify the curve type (e.g., "monotone" for a smooth curve).
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The dataKey prop specifies the key in the data object that corresponds to the line values.
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The appearance of the line can be customized using the stroke prop.
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The Scatter component is used to render a scatter plot within the combination chart.
⏵
The dataKey prop specifies the key in the data object that corresponds to the scatter values.
⏵
The appearance of the scatter points can be customized using the fill prop.
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The chart can be customized further by specifying various props such as useDollar for formatting tooltip values as currency, biaxial for enabling a biaxial chart, and colorList for specifying custom colors for the chart components.
Combination Graph: exhibiting a combination of bar, line, area, and scatter plots for different categories and values
Combination Graph
months
quantities
In Conclusion
So, now that we have explored the powerful and flexible Recharts library for creating stunning data visualizations in React and Remix, are you ready to go graphs some digits? While there may be a learning curve when it comes to customization, the extensive features and flexibility offered by Recharts make it a valuable tool for data visualization enthusiasts. By utilizing the knowledge gained from this post, you can create visually appealing and informative charts that effectively communicate your data stories. So go ahead, experiment with Recharts, and unleash the power of data visualization in your React and Remix projects!
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