| | A line chart is a popular visualization type that displays value changes over time or any other continuous progression.
It uses points connected by line segments to depict trends and patterns in data. Line charts commonly track stock market trends,
weather patterns, website traffic, and other metrics that change over time.
Line charts are helpful when analyzing trends and patterns in data over a continuous period. They effectively show how data changes
over time, how trends emerge, and how they fluctuate. Line charts can also reveal sudden changes or sharp dips in the data, which may
be missed in other charts.
Line charts are beneficial when there are many data points and multiple data series to compare. They can be customized to include various
lines on the same chart, with different colors and labels for each line. This allows for easy comparison of different data sets and trends.
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 | A standard 3D categorical line chart is a visualization that represents data points connected by lines. It's a helpful tool for displaying trends and patterns in data. The chart can be customized with markers of various shapes and fill options to highlight specific data points. This makes it easier for viewers to interpret and understand the presented data. |
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A 2D line chart with different image effects such as soft shadows and gradients. To create visually appealing designs, the chart can be stylized with image effects like shadow, glow, bevel/emboss, and lighting. |  |
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 | Smooth line charts connect the distincst data points with cubic curves, making it easier to identify trends and patterns in the data. Each data point can be highlighted with markers of various shapes and fill options. |
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An XYZ line chart represents a line that connects data points with custom XYZ coordinates. With this chart, you can visualize how data points are distributed across the x, y, and z axes and detect trends and patterns that might be missed with other chart types. This charting type is commonly used in scientific charts. |  |
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 | Date-Time Step Line Chart is type of XY scatter line chart, where the X values represent dates or times when the measurement has happened. This chart is handy for visualizing trends and patterns in data collected over a period of time. The Date-Time Step Line Chart allows you to see the general direction of the movement while also showing the specific points at which changes occurred. |
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A stacked line chart is similar to a stacked bar chart and allows the user to compare the contribution of different measurements to a total over different categories or time spans. By stacking the lines on top of each other, you can easily see which categories are growing or declining and how they affect the overall trend. |  |
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 | Several categorical line series visualized a tapes in 3D. The chart can be useful when comparing data sets with similar or overlapping trends. |
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The multi series line chart allows the visualization of several trends over a common set of categories or time spans in a single chart. This allows you to easily compare and contrast the trends of each series. This approach can provide insights into complex data, enabling the user to spot different trends and patterns. |  |
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 | XYZ Line Chart representing Lorenz Attractor – a complex fractal structure corresponding to the long-term behavior of a 3-dimensional dynamical system that exhibits chaotic flow and evolving without ever crossing itself. |
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3D Step line chart with dimension scale X-axis. Step line chart series display data points connected with HV segments. Markers with various shapes and fill options can be used for each data point. |  |
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| Date | Sales Revenue | Expenses |
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| 2021-01-01 | 1000 | 500 | | 2021-02-01 | 1200 | 550 | | 2021-03-01 | 1300 | 600 |
In this example, the first column represents the date, the second column represents the sales revenue in USD,
and the third column represents the expenses in USD. Using this data, a line chart could be created to visualize the sales revenue and expenses trend.
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Selecting the proper measurement interval
Selecting the appropriate measurement interval is crucial when creating a line chart. The measurement interval, or bin size, should be sufficiently broad and short,
as this can result in hiding the helpful signal or revealing only noise. It's best to test out different intervals or rely on domain knowledge to make an informed decision.
Using multiple lines, one for a fine-grained interval and another for the overall trend can also be useful. This can involve averaging over a rolling window to obtain a clearer picture of the data trend.
Do not overload it with too many lines
To prevent clutter and make the line chart easily interpretable, limiting the number of lines plotted is crucial. It's recommended to keep the number of lines to five or fewer. Too many lines on a chart make reading and understanding the data trends difficult.
But if the lines are distinct and separated, it's possible to include more lines while maintaining the chart's readability.
Use colors and markers effectively
Using colors and markers effectively is key to creating a visually appealing and informative line chart. Colors can differentiate between multiple lines or data sets,
making it easier for viewers to identify and track specific trends. Markers can be utilized to draw attention to particular data points or trends, emphasizing their
significance in the overall pattern.
It is essential to select appropriate colors and markers that complement each other and are easily distinguishable, ensuring that the chart remains straightforward and
easy to interpret. |
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