Geometric Objects (Geoms)

Geoms are the geometric objects that represent data in your plot.

Basic Geoms

class ggviews.geoms.geom_point(mapping=None, data=None, size=6, alpha=1.0, color=None, shape='circle', **kwargs)[source]

Bases: GeomLayer

Scatter plot points

Parameters:

  • mapping – Aesthetic mappings (aes object)

  • data – Data for this layer (overrides ggplot data)

  • size – Point size

  • alpha – Transparency (0-1)

  • color – Point color

  • shape – Point shape

  • **kwargs – Additional parameters

class ggviews.geoms.geom_line(mapping=None, data=None, color=None, size=2, alpha=1.0, linetype='solid', **kwargs)[source]

Bases: GeomLayer

Line plots

Parameters:

  • mapping – Aesthetic mappings

  • data – Data for this layer

  • color – Line color

  • size – Line width

  • alpha – Transparency

  • linetype – Line type (‘solid’, ‘dashed’, ‘dotted’)

  • **kwargs – Additional parameters

class ggviews.geoms.geom_bar(mapping=None, data=None, stat='count', color=None, fill=None, alpha=1.0, width=0.8, **kwargs)[source]

Bases: GeomLayer

Bar charts

Parameters:

  • mapping – Aesthetic mappings

  • data – Data for this layer

  • stat – Statistical transformation (‘count’ or ‘identity’)

  • color – Bar border color

  • fill – Bar fill color

  • alpha – Transparency

  • width – Bar width

  • **kwargs – Additional parameters

class ggviews.geoms.geom_histogram(mapping=None, data=None, bins=30, alpha=1.0, fill=None, color=None, **kwargs)[source]

Bases: GeomLayer

Histograms

Parameters:

  • mapping – Aesthetic mappings

  • data – Data for this layer

  • bins – Number of bins or bin edges

  • alpha – Transparency

  • fill – Fill color

  • color – Border color

  • **kwargs – Additional parameters

class ggviews.geoms.geom_area(mapping=None, data=None, stat='identity', position='identity', alpha=0.7, fill=None, color=None, size=1, **kwargs)[source]

Bases: GeomLayer

Area plots

Draws an area plot where the area under the curve is filled. Useful for showing cumulative values or stacked areas.

Parameters:

  • mapping – Aesthetic mappings (x, y, fill, color, group, alpha)

  • data – Data for this layer

  • stat – Statistical transformation (‘identity’ or ‘count’)

  • position – Position adjustment (‘identity’, ‘stack’, ‘fill’)

  • alpha – Transparency (0-1)

  • fill – Fill color

  • color – Outline color

  • size – Outline width

  • **kwargs – Additional parameters

Examples

geom_area(aes(x=’year’, y=’value’)) geom_area(aes(x=’year’, y=’value’, fill=’category’)) geom_area(position=’stack’) # Stacked areas

class ggviews.geoms.geom_smooth(mapping=None, data=None, method='loess', se=True, color=None, fill=None, alpha=1.0, **kwargs)[source]

Bases: GeomLayer

Smoothed conditional means

Parameters:

  • mapping – Aesthetic mappings

  • data – Data for this layer

  • method – Smoothing method (‘lm’ for linear, ‘loess’ for local regression)

  • se – Show confidence interval

  • color – Line color

  • fill – Confidence band color

  • alpha – Transparency

  • **kwargs – Additional parameters

Statistical Geoms

class ggviews.geom_boxplot.geom_boxplot(mapping=None, data=None, width=0.9, outlier_alpha=1.0, outlier_color=None, outlier_size=1.5, coef=1.5, **kwargs)[source]

Bases: GeomLayer

Box and whisker plots

Creates box-and-whisker plots showing the distribution of a continuous variable, optionally grouped by a categorical variable.

Parameters:

  • mapping – Aesthetic mappings (aes object)

  • data – Data for this layer

  • width – Box width (default: 0.9)

  • outlier_alpha – Transparency for outliers (default: 1.0)

  • outlier_color – Color for outliers (default: None)

  • outlier_size – Size for outliers (default: 1.5)

  • coef – Whisker length coefficient (default: 1.5)

  • **kwargs – Additional parameters

Examples

# Basic boxplot geom_boxplot(aes(y=’value’))

# Grouped boxplot geom_boxplot(aes(x=’group’, y=’value’))

# Customized geom_boxplot(aes(x=’group’, y=’value’, fill=’group’), width=0.5)

class ggviews.geom_density.geom_density(mapping=None, data=None, bw='scott', kernel='gaussian', n=512, adjust=1.0, trim=False, **kwargs)[source]

Bases: GeomLayer

Kernel density estimation plots

Computes and displays kernel density estimates, which are smoothed versions of histograms.

Parameters:

  • mapping – Aesthetic mappings (aes object)

  • data – Data for this layer

  • bw – Bandwidth for kernel density estimation (‘scott’, ‘silverman’, or float)

  • kernel – Kernel to use (‘gaussian’, ‘tophat’, ‘epanechnikov’, etc.)

  • n – Number of points to evaluate density at (default: 512)

  • adjust – Adjustment factor for bandwidth (default: 1.0)

  • trim – Whether to trim the density curve to data range

  • **kwargs – Additional parameters

Examples

# Basic density plot geom_density(aes(x=’value’))

# Multiple densities by group geom_density(aes(x=’value’, fill=’group’), alpha=0.5)

# Customized bandwidth geom_density(aes(x=’value’), bw=0.5, kernel=’gaussian’)

2D Visualization

class ggviews.geom_tile.geom_tile(mapping=None, data=None, width=None, height=None, **kwargs)[source]

Bases: GeomLayer

Rectangles with specified positions and dimensions

Creates heatmap-like visualizations using rectangles (tiles). Each tile represents a data point with x, y coordinates and can be colored by a third variable.

Parameters:

  • mapping – Aesthetic mappings (aes object)

  • data – Data for this layer

  • width – Tile width (default: auto-calculated)

  • height – Tile height (default: auto-calculated)

  • **kwargs – Additional parameters

Examples

# Basic heatmap geom_tile(aes(x=’x_var’, y=’y_var’, fill=’z_var’))

# Custom tile size geom_tile(aes(x=’x’, y=’y’, fill=’value’), width=1, height=1)

class ggviews.geom_tile.geom_raster(mapping=None, data=None, interpolate=False, **kwargs)[source]

Bases: geom_tile

High performance rectangular tiles for large datasets

Similar to geom_tile but optimized for large regular grids. Better performance for image-like data.

Parameters:

  • mapping – Aesthetic mappings (aes object)

  • data – Data for this layer

  • interpolate – Whether to interpolate between points

  • **kwargs – Additional parameters

Examples

# Large heatmap geom_raster(aes(x=’x’, y=’y’, fill=’value’))

# Image-like data geom_raster(aes(x=’x’, y=’y’, fill=’intensity’), interpolate=True)

Geographic Visualization

class ggviews.geom_map.geom_map(mapping=None, data=None, map_type='points', projection=None, features=['coastlines'], alpha=0.7, color=None, fill=None, size=6, **kwargs)[source]

Bases: GeomLayer

Geographic map layer

Creates geographic visualizations using points, polygons, or choropleth maps. Requires geoviews and cartopy for full functionality.

Parameters:

  • mapping – Aesthetic mappings (aes object)

  • data – Data for this layer (should contain lat/lon or geometry)

  • map_type – Type of map (‘points’, ‘polygons’, ‘choropleth’, ‘world’)

  • projection – Map projection (default: PlateCarree)

  • features – List of map features to add (‘coastlines’, ‘borders’, ‘land’, ‘ocean’)

  • alpha – Transparency (0-1)

  • color – Point/line color

  • fill – Fill color for polygons

  • size – Point size

  • **kwargs – Additional parameters

Examples

# World map with points geom_map(aes(x=’longitude’, y=’latitude’), map_type=’points’)

# Choropleth map geom_map(aes(fill=’population’), map_type=’choropleth’)

# Custom projection geom_map(map_type=’world’, projection=’Mollweide’)

Additional Geoms

Additional geometric objects for ggviews

This module implements additional geoms commonly used in ggplot2 including ribbon, violin, text, and more specialized plot types.

class ggviews.additional_geoms.geom_errorbar(mapping=None, data=None, width=0.1, color='black', size=1, alpha=1, **kwargs)[source]

Bases: GeomLayer

Error bars

Display error bars showing uncertainty or variation in data.

Parameters:

  • mapping – Aesthetic mappings (x, ymin, ymax, width, color)

  • data – Data for this layer

  • width – Width of error bar caps

  • color – Error bar color

  • size – Line width

  • alpha – Transparency

  • **kwargs – Additional parameters

Examples

geom_errorbar(aes(x=’treatment’, ymin=’lower’, ymax=’upper’)) geom_errorbar(aes(x=’x’, ymin=’y-se’, ymax=’y+se’), width=0.2)

class ggviews.additional_geoms.geom_label(mapping=None, data=None, label_padding=0.25, label_r=0.15, fill='white', color='black', **kwargs)[source]

Bases: geom_text

Text labels with background boxes

Similar to geom_text but with background rectangles for better readability.

Parameters:

  • mapping – Aesthetic mappings (x, y, label, color, fill)

  • data – Data for this layer

  • label_padding – Padding around text

  • label_r – Corner radius of label box

  • fill – Background fill color

  • color – Text color

  • **kwargs – Additional parameters inherited from geom_text

class ggviews.additional_geoms.geom_ribbon(mapping=None, data=None, alpha=0.5, fill=None, color=None, size=0, **kwargs)[source]

Bases: GeomLayer

Ribbon plots (confidence bands, error ribbons)

Creates ribbons between ymin and ymax values, commonly used for confidence intervals around trend lines.

Parameters:

  • mapping – Aesthetic mappings (x, ymin, ymax, fill, color, alpha)

  • data – Data for this layer

  • alpha – Transparency (0-1)

  • fill – Fill color

  • color – Border color

  • size – Border width

  • **kwargs – Additional parameters

Examples

geom_ribbon(aes(x=’x’, ymin=’lower’, ymax=’upper’), alpha=0.3) geom_ribbon(aes(x=’x’, ymin=’y-se’, ymax=’y+se’, fill=’group’))

class ggviews.additional_geoms.geom_text(mapping=None, data=None, nudge_x=0, nudge_y=0, size=12, color='black', alpha=1, fontface='plain', family='Arial', hjust=0.5, vjust=0.5, check_overlap=False, **kwargs)[source]

Bases: GeomLayer

Text annotations

Add text labels to plots at specified positions.

Parameters:

  • mapping – Aesthetic mappings (x, y, label, color, size, angle)

  • data – Data for this layer

  • nudge_x – Horizontal adjustment

  • nudge_y – Vertical adjustment

  • size – Text size

  • color – Text color

  • alpha – Text transparency

  • fontface – Font face (‘plain’, ‘bold’, ‘italic’)

  • family – Font family

  • hjust – Horizontal justification (0=left, 0.5=center, 1=right)

  • vjust – Vertical justification (0=bottom, 0.5=center, 1=top)

  • check_overlap – Whether to avoid overlapping text

  • **kwargs – Additional parameters

Examples

geom_text(aes(x=’x’, y=’y’, label=’name’)) geom_text(aes(x=’x’, y=’y’, label=’value’), nudge_y=0.1)

class ggviews.additional_geoms.geom_violin(mapping=None, data=None, trim=True, scale='area', alpha=0.7, fill=None, color=None, **kwargs)[source]

Bases: GeomLayer

Violin plots

Shows the distribution of data through kernel density estimation on each side, creating a violin-like shape.

Parameters:

  • mapping – Aesthetic mappings (x, y, fill, color)

  • data – Data for this layer

  • trim – Trim the violin to data range

  • scale – How to scale violins (‘area’, ‘count’, ‘width’)

  • alpha – Transparency

  • fill – Fill color

  • color – Border color

  • **kwargs – Additional parameters