18 chart functions that produce publication-ready output with a consistent visual style. No tweaking matplotlib defaults.
18 functions
Visualizations
Publication-ready charts and data visualizations.
Functions
Plot100PercentStackedBarChart
Generate a 100% horizontal stacked bar chart visualizing completion or composition.
PlotBarChart
Generate a formatted horizontal bar chart for categorical data comparison.
PlotBoxWhiskerByGroup
Create a formatted box-and-whisker plot for grouped data comparisons.
PlotBulletChart
Generate a formatted horizontal bullet chart to visualize performance against targets and ranges.
PlotCard
Create a clean, card-style visualization for a single KPI or metric.
PlotClusteredBarChart
Generate a formatted clustered bar chart for multi-category data comparison.
PlotContingencyHeatmap
Generate a formatted contingency heatmap to visualize relationships between categorical variables.
PlotCorrelationMatrix
Generate a correlation matrix or multi-variable pairplot.
PlotDensityByGroup
Generate a formatted kernel density estimate (KDE) plot grouped by a categorical variable.
PlotDotPlot
Generate a formatted horizontal dot plot (dumbbell chart) to compare two groups.
PlotHeatmap
Generate a formatted heatmap to visualize three-dimensional categorical data.
PlotOverlappingAreaChart
Generate a formatted overlapping area chart for multi-variable time series comparison.
PlotRiskTolerance
Generate a formatted histogram to visualize risk tolerance and simulated outcomes.
PlotScatterplot
Generate a scatter plot with optional regression lines and quadrant labels.
PlotSingleVariableCountPlot
Generate a formatted horizontal bar chart showing frequency counts for a single categorical variable.
PlotSingleVariableHistogram
Generate a formatted histogram to visualize the distribution of a single numeric variable.
PlotTimeSeries
Generate a formatted time series line chart with optional grouping.
RenderTableOne
Generate and display a standardized summary table (Table 1) for baseline characteristics.