How to Read a Chart Vertical Line
What is a line chart?
A line nautical chart (aka line plot, line graph) uses points connected by line segments from left to right to demonstrate changes in value. The horizontal axis depicts a continuous progression, often that of fourth dimension, while the vertical axis reports values for a metric of involvement across that progression.
The line chart above shows the commutation rate between two fictional currencies over a six calendar month period. Every bit fourth dimension progresses from left to right, points connect the daily substitution rates. We can read from the full general slope of the line and its vertical positions that the rate improved from well-nigh 0.75 to 0.78 betwixt March and early April, then fell gradually to about 0.765 in late May and June.
When you should use a line chart
You volition use a line chart when you want to emphasize changes in values for one variable (plotted on the vertical axis) for continuous values of a second variable (plotted on the horizontal). This emphasis on patterns of alter is sold by line segments moving consistently from left to correct and observing the slopes of the lines moving upwardly or downwardly.
On the horizontal axis, you need a variable that depicts continuous values that have a regular interval of measurement. Very commonly, this variable is a temporal one, generating an observation every minute, 60 minutes, day, calendar week, or calendar month. The choice of interval size, or bin, is a decision that the analyst will usually demand to brand for the data, rather than it being an inherent data characteristic.
On the vertical centrality, you lot will report the value of a second numeric variable for points that autumn in each of the intervals defined by the horizontal-centrality variable. Often, this will exist a statistical summary like a total or average value across events within each bin.
Multiple lines tin can also be plotted in a single line chart to compare the trend betwixt series. A mutual utilize case for this is to notice the breakdown of the information across different subgroups. The power to plot multiple lines also provides the line chart a special use case where it might not usually be selected. Normally, we would apply a histogram to depict the frequency distribution of a single numeric variable. Notwithstanding, since it'due south tricky to plot two histograms on the same set up of axes, the line chart serves as a good mode of comparison as a substitute. Line charts used to depict frequency distributions are often called frequency polygons.
Example of data structure
| Appointment | Guests | Subscribers |
|---|---|---|
| 2019-05-01 | nineteen | 103 |
| 2019-05-02 | 22 | 105 |
| 2019-05-03 | 20 | 98 |
| 2019-05-04 | 26 | 83 |
| … | … | … |
To utilize a line nautical chart, data often needs to be aggregated into a table with two or more columns. Values in the offset column indicate positions for points on the horizontal centrality for each line to be plotted. Each following cavalcade indicates the vertical position for points of a single line.
Sure tools create line charts from a different data format where iii columns are expected regardless of how many lines to plot. In these cases, the columns specify the horizontal values, vertical values, and to which line to each row volition exist assigned.
| Appointment | User Type | Trips |
|---|---|---|
| 2019-03-01 | Guest | 23 |
| 2019-03-01 | Subscriber | 102 |
| 2019-03-02 | Guest | 24 |
| 2019-03-03 | Subscriber | 77 |
| … | … | … |
Best practices for using a line nautical chart
Choose an advisable measurement interval
An of import aspect of creating a line chart is selecting the right interval or bin size. For temporal information, a too-broad of a measurement interval may hateful that it takes besides long to come across where the information tendency is leading, hiding away the useful signal. On the flip side of the coin, a as well-short a measurement interval may only reveal noise rather than signal.
Testing out different intervals or relying on your domain knowledge about what data is being recorded can inform you of a good choice of bin size. It can also exist possible to apply multiple lines, with i line for a fine-grained interval, and and then a second line for the overall trend, averaging over a rolling window.
Don't plot too many lines
With great ability comes groovy responsibility, and so while at that place is the technical capacity to put many lines onto a single line chart, it is a good idea to exist judicious in the amount of data that you plot. A good rule of thumb is to limit yourself to five or fewer lines, lest the plot end up looking like an unreadable tangle. However, if the lines are well-separated, you can withal plot all of the values you wish to track.
If you find the need to plot more than lines than tin can be read in a single axis, so yous might consider faceting the plots into a grid of smaller line charts. It will be more difficult to see details in these plots, then information technology'due south a good idea to sort them past some important characteristic (similar average or last value) to aid draw out important points. If you are using a tool that allows for interactive plots, another alternative is to be able to highlight individual lines or grey out lines to exist out of focus as the reader desires.
Common misuses
Strictly using a zippo-value baseline
Despite the goose egg baseline for the vertical axis existence a requirement for bar charts and histograms, yous do not need to include a nada baseline for a line chart. Recall that the main goal of a line chart is to emphasize changes in value, rather than the magnitude of the values themselves. In cases where a nada line is not meaningful or useful, it's fine to zoom the vertical axis range into what volition make the changes in value most informative.
In that location is one use example where a cipher baseline is still necessary, even so. When a line chart being used to display frequency distributions, then it is being used in a capacity equivalent to bar charts and histograms. Thus, information technology volition follow the same requirement of needing to include a zero-value baseline as an anchor for the line chart'south heights.
Failing to identify uneven gaps between points
When the line chart is missing information for certain bins, gaps in the tape may be interpreted equally phantom values if the line does non include distinct dots at each observation. When at that place aren't many points to plot, try showing all of the points and non just the line. If including the points would muddy upwardly the interpretability of the plot, another alternative is to include a gap in the line to bear witness where there are missing values.
Interpolating a curve between points
In a standard line chart, each point is connected to the next with a straight line segment, from first to last. However, there may be the aesthetic temptation to effort and link all of the points smoothly, fitting a bend that goes through all of the points at in one case. Yous should absolutely resist this temptation! Equally seen in the example beneath, attempting this kind of plumbing equipment will exist assured of distorting perception of trends in the data. The direction and steepness of the line is supposed to exist indicative of change in value, and then the curve may end up implying the presence of additional data points betwixt the actual measurements that do non exist.
Using a misleading dual axis
Examples of line charts with multiple lines take thus far had each line be part of the same domain, and thus plottable on the same axis. There'southward zippo that limits each line to draw values on the same units, however. When a line plot includes two series, each depicting a summary of a different variable, then nosotros end up with a dual axis plot.
The problem with a dual-axis plot is that it tin can easily be manipulated to exist misleading. Depending on how each axis is scaled, the perceived relationship between the ii lines tin can be inverse. In the 2 plots beneath, the number of weekly trials and subscriptions are plotted in dual-centrality plots. The data is exactly the same for each, but due to the selection of vertical scaling for each variable, the inferred human relationship between the variables will alter.
While many visualization tools are capable of creating dual-axis charts, mutual recommendations advise against this, regardless of if the ii axes are in the aforementioned or split domains. Instead, faceting the ii lines into separate plots still allows for the general patterns of change to exist observed for both variables, while reducing the temptations to compare them in misleading means.
Mutual line chart options
Include additional lines to show dubiousness
When we accept a line that depicts a statistical summary like an average or median, nosotros can also have an pick to add to the plot to brandish uncertainty or variability in the data at each plotted point. 1 way of doing this is through the addition of error confined at each signal to prove standard difference or some other doubtfulness measure. Another alternative is to add supporting lines above or below the line to testify certain bounds on the data. These lines might be rendered as shading to show the most common data values, equally in the instance below.
Sparkline
A special use case for the line chart is the sparkline. A sparkline is substantially a small line chart, built to be put in line with text or alongside many values in a table. Considering of its small size, it volition not include any labeling. Statistics can exist placed next to the sparkline to indicate starting and ending values, or perhaps minimum or maximum values. The main point of a sparkline is to testify change over a period of time, and is often seen in financial contexts.
Ridgeline plot
One variant nautical chart type for a line nautical chart with multiple lines is the ridgeline plot. In a ridgeline plot, each line is plotted on a unlike axis, slightly starting time from each other vertically. This slight offset can save on space compared to a consummate faceting of plots. Like the sparkline, vertical axis markings are typically eschewed: it would be difficult to read those values on the unlike axes. Ridgeline plots are mainly used to compare lots of groups on their frequency distributions. This is about useful when a clear pattern is visible when the lines are ordered in some way.
Bar chart
If the variable we desire to testify on the horizontal axis is non numeric or ordered, but instead chiselled, then we need to apply a bar chart instead of a line nautical chart. The confined in a bar chart are usually separated by modest gaps, which help to emphasize the discrete nature of the categories plotted. Notation, even so, when our horizontal axis is numeric or ordered, we aren't restricted against using a bar chart, equally seen in the example beneath.
Dot plot
Another chart type we tin use when the horizontal centrality variable is categorical is the dot plot, or Cleveland dot plot. The dot plot is like a line plot, except that there are no line segments connecting consecutive points. This lack of line segments frees the points from their sequential progression, and then the order of labels and points can exist freely adjusted like a bar nautical chart. The major advantage of using a dot plot over a bar chart is that a dot plot, like a line chart, is not appreciative to include a zero-baseline. If we have values over levels of a categorical variable, only associated values do non have a meaningful zero-baseline, so the dot plot can be a practiced chart type pick.
Histogram
When the vertical axis of a line chart depicts information almost a frequency distribution, we take an pick to visualize the data every bit a histogram instead. Ane of the main benefits of the histogram is that the bars are a more than consequent display of frequency within each bin. Frequency judgments can exist misleading in a line chart, especially in the peaks and troughs of a distribution. However, a line chart does have one advantage for visualizing frequency distributions: if nosotros need to compare 2 unlike groups, this is very difficult for a histogram. As seen in an before department when using a line chart, nosotros tin can just plot the two groups' lines on the same axes with little outcome.
Density bend
Another culling for frequency-based line charts is the density curve, or kernel density estimate (KDE). While a line chart aggregates frequency counts by bins into single points, the KDE aggregates the contribution of each point in a continuous way. In a KDE, each point contributes a minor lump of volume centered around its true value (the titular kernel); the sum of all volumes gives the concluding density bend. Since in that location are so many options for the shape of the kernel, kernel density estimation is usually reserved for programmatic approaches to information visualization.
Area nautical chart
An extension to the line nautical chart involves the addition of shading between the line and a cypher-baseline, called an expanse chart. The surface area nautical chart can be considered a hybrid of the line chart with the bar chart, since values can be read from not just their vertical positions, but besides the size of the shaded area between each point and the baseline.
Connected besprinkle plot
If you take ii serial of values that yous want to plot using a line chart, an alternative nautical chart type you could use is the continued scatter plot. In a standard scatter plot, the two axes stand for 2 variables of interest, and points plotted on the axes indicate values on those variables. If nosotros continued points in an society specified by a third variable like time, we get a connected scatter plot. A connected besprinkle plot is good for looking at not only the relationship between two variables, but also how they alter across fourth dimension or values of a third variable.
The line chart is a versatile and useful nautical chart type, so should exist available in pretty much any data visualization tool you choose. Basic line charts where i or more lines are plotted on a single centrality should be common, but avant-garde options like dual axes may not be present or require additional data piece of work to set up. The ridgeline variant is not a common born, and ordinarily requires custom programming or a custom parcel to create. Sparklines too are not common on their own, and are more than often seen equally built in as part of other reporting tools.
The line nautical chart is 1 of many unlike nautical chart types that tin can exist used for visualizing data. Larn more than from our articles on essential chart types, how to choose a type of data visualization, or by browsing the full drove of articles in the charts category.
Source: https://chartio.com/learn/charts/line-chart-complete-guide/
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