Guide lines or ranges can be added to charts as a reference or way to highlight significant values. You can format the way the axes display numeric values by specifying the number of decimal places and whether to include a thousands separator. Click Reset to revert the axis bound to the default value. You can customize these values by typing a new axis bound value. The default minimum and maximum axis bounds are set based on the range of data values represented on the axis. If you use a log scale for a variable containing negative values or zeros, those values will not appear on the chart. Logarithmic scales cannot display negative values or zero. The axis diagram below, each increment on the axis increases by On a logarithmic scale, increments increase by magnitudes. For example, in the axis diagram below,Įach increment on the axis increases by adding 10. On a linear scale, each increment on the axis represents the Linear scales are based on addition, and logarithmic Changing the scale of the axis does not change the value of the data-only the way it is displayed. Logarithmic scales are useful when visualizing data with large positive skew when the majority of data points have a small value, with a few data points with very large values. You can display one or both axes on a logarithmic scale using the Logarithmic scale slider. Logarithmic scaleīy default, scatter plot axes are displayed on a linear scale. Both axes include configurations for scale, minimum and maximum bounds, and number formatting. The Axes configurations are used to change the specifications for the x- and y-axes. By symbolizing a layer with a different attribute than either of the scatter plot variables, you can show an additional dimension on the scatter plot visualization. By default, scatter plots use layer colors and inherit their outline and fill colors from the source layer style. Scatter plot points can be visualized using a single color or with the colors specified in the layer's style. You can change the size and color of the symbols on a scatter plot. It is important to note that x being correlated To small y-values (line sloping downward), this indicates a negative When small x-values correspond to large y-values, and large x-values correspond When small x-values correspond to small y-values, and large x-values correspond to large y-values (line sloping upward), this indicates a positive correlation. To change the color of the trend line, click the color swatch for the Trend line style parameter and choose a new color. The Show linear trend parameter is used to display and remove the trend line from the scatter plot. These statistics are only relevant for linear relationships. The trend line models the linear relationship between x and y, and the R² value quantifies how well the data fits the model. StatisticsĪ regression equation is calculated and the associated trend line and R² value can be plotted on the scatter plot. Scatter plots are composed of two number variables: X-axis number and Y-axis number. The Data configurations include the variables that are used to create a scatter plot, the statistics displayed on the chart, and symbol configurations. The scatter plot below visualizes the relationship between voter turnout in the 2016 United States election and the 2019 per capita income. When the resulting points form a nonrandom structure, a relationship exists between the two variables. For each record, a point is plotted where the two variables intersect on the chart. Scatter plots visualize the relationship between two numeric variables in which one variable is displayed on the x-axis, and the other variable is displayed on the y-axis.

Scatter plot relationships