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Used for scheduling and to show the progress of multiple tasks over time; best for project management.

Visualizes cumulative effect of sequentially introduced values; best for understanding the stepwise impact of different contributing factors.

Used to compare quantity across different categories; best when categories are discrete and not too many.

Emphasizes the magnitude of change over time; best for showing volume beneath a line chart, illustrating cumulative totals.

A type of scatter plot that represents three dimensions of data; best used when the data set contains three quantitative and one to two categorical variables.

Displays the distribution of a data set based on a five-number summary; best for detecting outliers and understanding the spread of data.

Shows hierarchical data as nested rectangles; best for space-efficient display of hierarchical data and relative sizes.

A thematic map where geographic regions are colored or shaded in relation to a data variable; best for showing how a measurement varies across a geographic area.

Displays frequency using dots; best for small to moderate sets of data where precise values for each category are needed.

Displays multivariate data as a two-dimensional chart; best used to plot one or more groups or variables that have three or more variables.

Displays data points over a continuous interval or time span; best for showing trends and changes over time.

Shows the relationship between two quantitative variables; best for identifying correlations or patterns.

Represent data values using color coding; best for comparing data across multiple categories or through spatial data.

A type of stacked area chart that is displaced around a central axis, often used to show changes in data over time; best for displaying high-volume datasets with long time periods.

Visualizes the flow of data between different nodes; best for showing the distribution and conservation in a system.

Indicates how different parts contribute to a total; best when you want to show the total size along with the composition of the categories.

Combines a box plot with a kernel density plot; best for comparing the distribution of data across several groups.

Shows the proportion or percentage each category represents of the total; best for illustrating part-to-whole relationships with a few categories.

Visualizes the distribution of numerical data; best used when the data is continuous and you're interested in the frequency of values within intervals.