Line charts are a type of data visualization tool that uses lines to represent data points and show trends or changes in data over time. They are particularly effective for displaying continuous data, such as data collected at regular intervals, and highlighting patterns, variations, and relationships in the data.
Some prominent features of line charts include:
- Data points: Line charts consist of a series of data points, each represented by a dot or marker. These data points are connected by lines, visually representing the data’s progression.
- Time on the x-axis: In most cases, line charts have time on the x-axis, making them well-suited for time-series data. The time intervals can be anything from seconds to years, depending on the data’s nature.
- Values on the y-axis: The data values are typically represented on the y-axis. The vertical position of each data point corresponds to its value, allowing for easy comparison and trend identification.
- Trends and patterns: Line charts help viewers identify trends, patterns, and fluctuations in the data. Rising or falling lines indicate increasing or decreasing values, while flat lines suggest stability.
- Interpolation between data points: The lines between data points often represent interpolation, providing a smooth visual transition between known data points.
Some commonly used types of line charts include:
- Basic line chart: A classic line chart represents data with a series of data points connected by lines. It is beneficial for displaying trends and changes over time.
- Step line chart: Step line charts connect data points with horizontal and vertical lines, emphasizing a “stepwise” progression. They are valuable for visualizing data with abrupt transitions or step changes.
- Area chart: Area charts are similar to basic line charts, but fill the area below the lines. They effectively illustrate part-to-whole relationships and help show the data’s cumulative effect.
List of recommended resources #
For a broad overview #
A Complete Guide to Line Charts
This data tutorial guide by Chartio gives a broad overview of line charts where to use them, their misuses and the different types of line charts used in data visualization.
Displaying Change Between Two Points in Time
This paper by Stepehn Few for Perceptual Edge gives a broad understanding of line charts and their function of representing change in data over time.
This LabWrite Resources page gives an explanation of the difference between line graphs and scatter plots used for representing data.
For in depth understanding #
The Truthful Art: Data, Charts, and Maps for Communication
This textbook by Alberto Cairo provides an introduction to the graphical representation of quantitative thinking using charts, graphs, and maps.
The Visual Display of Quantitative Information
This book by Edward R. Tufte provides an in-depth understanding of the process of graphically representing quantitative information using various resources like graphs, charts, maps etc.
Case study #
Annotating Line Charts for Addressing Deception
Co-written by Arlen Fan, Yuxin Ma, Michelle Mancenido and Ross Maciejewski, this paper presents a tool for annotating line charts. The tool reads line chart images and outputs text and visual annotations to assess the line charts for distortions and help guide the reader towards an honest understanding of the chart data.
Multi-label classification of line chart images using convolutional neural networks
This paper, written by Cem Kosemen & Derya Birant, proposes a new convolutional neural network (CNN) architecture to build a multi-label classifier that categorizes line chart images according to their characteristics.
References #
Line Chart: Definition, Types, Examples, How To Make in Excel
