graph python_visualisation_landscape {
graph [fontname = "Calibri", fontsize="16", overlap=false];
node [fontname = "Calibri", fontsize="16", style="bold", penwidth="5px"];
edge [fontname = "Calibri", fontsize="16", style="bold", penwidth="5px"];
tooltip="Python Visualisation Landscape";
// OpenGL
opengl [
label="OpenGL",
tooltip="Open Graphics Library",
color="#FF66B3",
target="_top",
href="../opengl/index.html"]
VisPy [
label="Vispy",
tooltip="Python-Bibliothek für\ninteraktive wissenschaftliche\nVisualisierungen",
color="#FF66B3",
target="_top",
href="http://vispy.org/"]
mayavi [
label="Mayavi",
tooltip="Python-Bibliothek für die\n3D-Visualisierung\nwissenschaftlicher Daten",
color="#FF66B3",
target="_top",
href="http://docs.enthought.com/mayavi/mayavi/"]
itkwidgets [
label="itkwidgets",
tooltip="Interaktive Jupyter-Widgets\nzur Visualisierung von Bildern,\nPunktmengen und Netzen\nin 2D und 3D",
color="#FF66B3",
target="_top",
href="https://itkwidgets.readthedocs.io/en/latest/"]
vedo [
label="vedo",
tooltip="Python-Modul für die\nwissenschaftliche\nAnalyse von 3D-Daten",
color="#FF66B3",
target="_top",
href="https://vedo.embl.es"]
polyscope [
label="Polyscope",
tooltip="Ein C++ und Python-Viewer\nfür 3D-Daten wie Netze\nund Punktwolken",
color="#FF66B3",
target="_top",
href="https://polyscope.run"]
glumpy [
label="Glumpy",
tooltip="Schnittstelle zwischen\nnumpy und OpenGL",
color="#FF66B3",
target="_top",
href="https://glumpy.github.io/"]
opengl -- VisPy [color="#FF66B3"]
opengl -- mayavi [color="#FF66B3"]
opengl -- itkwidgets [color="#FF66B3"]
opengl -- vedo [color="#FF66B3"]
opengl -- polyscope[color="#FF66B3"]
opengl -- glumpy [color="#FF66B3"]
// Matplotlib
mpl [
label="Matplotlib",
tooltip="Python-Bibliothek\nfür 2D-Plots",
color="#BF80FF"
target="_top",
href="../matplotlib/index.html"]
mpl_scatter_density [
label="mpl-scatter-density",
tooltip="Streudichtekarten für die\naussagekräftige Darstellungen\ngroßer Datensätze",
color="#BF80FF",
target="_top",
href="../matplotlib/mpl-scatter-density.html"]
pandas [
label="pandas",
tooltip="pandas Datenstrukturen mit\nMatplotlib visualisieren",
color="#BF80FF",
target="_top",
href="../matplotlib/pandas/index.html"]
geopandas [
label="GeoPandas",
tooltip="GeoPandas erweitert pandas um geometrische Datentypen",
color="#BF80FF",
target="_top",
href="../matplotlib/geopandas/index.html"]
geoplot [
label="Geoplot",
tooltip="High-level-Bibliothek zum Plotten von Geodaten",
color="#BF80FF",
target="_top",
href="https://residentmario.github.io/geoplot/index.html"]
prettymaps [
label="prettymaps",
tooltip="Python-Bibliothek zum Zeichnen benutzerdefinierter Karten aus OpenStreetMap-Daten",
color="#BF80FF",
target="_top",
href="https://github.com/marceloprates/prettymaps"]
seaborn [
label="seaborn",
tooltip="High-level-Datenvisualisierung\nbasierend auf Matplotlib",
color="#BF80FF",
target="_top",
href="../matplotlib/seaborn/index.html"]
plotnine [
label="plotnine",
tooltip="Python-Implementierung von ggplot2",
color="#BF80FF",
target="_top",
href="../matplotlib/plotnine/index.html"]
yellowbrick [
label="Yellowbrick",
tooltip="Tools für die visuelle Analyse und Diagnose\nvon Scikit-learn-Projekten",
color="#BF80FF",
target="_top",
href="https://www.scikit-yb.org/"]
networkx [
label="NetworkX",
tooltip="Erstellen, Ändern und Analysieren\nkomplexer Netzwerke",
color="#BF80FF",
target="_top",
href="../matplotlib/networkx.html"]
graphviz [
label="Graphviz",
tooltip="Mächtige Visualisierungssoftware\nfür Graphen",
color="#cccccc",
target="_top",
href="../matplotlib/graphviz.html"]
graph_tool [
label="graph-tool",
tooltip="Effizientes Python-Modul zur\nManipulation und statistischen Analyse\n von Graphen",
color="#cccccc",
target="_top",
href="../matplotlib/graph-tool.html"]
cartopy [
label="Cartopy",
tooltip="Erstellen von Karten und\nAnalyse von Geodaten",
color="#BF80FF",
target="_top",
href="../matplotlib/cartopy/index.html"]
iris [
label="Iris",
tooltip="Visualisierung auf Basis der Climate\nand Forecast (CF) Conventions",
color="#BF80FF",
target="_top",
href="../matplotlib/iris.html"]
yt [
label="yt",
tooltip="Python-Bibliothek zur Analyse\nund Visualisierung von Volumendaten",
color="#BF80FF",
target="_top",
href="../matplotlib/yt.html"]
mpl -- pandas [color="#BF80FF"]
mpl -- mpl_scatter_density [color="#BF80FF"]
pandas -- geopandas [color="#BF80FF"]
mpl -- geoplot [color="#BF80FF"]
mpl -- prettymaps [color="#BF80FF"]
mpl -- seaborn [color="#BF80FF"]
mpl -- plotnine [color="#BF80FF"]
mpl -- yellowbrick [color="#BF80FF"]
networkx -- graphviz [color="#BF80FF;0.5:#cccccc", style="dashed"]
graphviz -- graph_tool [color="#cccccc;0.5:#cccccc", style="dashed"]
mpl -- networkx [color="#BF80FF"]
mpl -- cartopy [color="#BF80FF"]
iris -- mpl [color="#BF80FF"]
iris -- cartopy [color="#BF80FF"]
yt -- mpl [color="#BF80FF"]
yt -- opengl [color="#BF80FF;0.5:#FF66B3", style="dashed"]
mpl -- ipympl [color="#BF80FF;0.5:#00FFFF"]
mpl -- mpl_altair [color="#BF80FF;0.5:#00FF80"]
// Bokeh
bokeh [
label="Bokeh",
tooltip="Interaktive Python-Bibliothek\nzur Datenvisualisierung\nin modernen Webbrowsern",
color="#9999FF",
target="_top",
href="../bokeh/index.html"]
vaex [
label="Vaex",
tooltip="Python-Bibliothek zur Datenanalyse\nund -visualisierung",
color="#9999FF",
target="_top",
href="https://github.com/vaexio/vaex"]
holoviews [
label="HoloViews",
tooltip="Python-Bibliothek zur Datenanalyse\nund -visualisierung",
color="#9999FF",
target="_top",
href="http://holoviews.org/"]
hvplot [
label="hvPlot",
tooltip="High-level-Plot-API\nauf Basis von HoloViews",
color="#9999FF",
target="_top",
href="../bokeh/integration/holoviews/hvplot/index.html"]
datashader [
label="Datashader",
tooltip="Grafik-Pipeline-System für\naussagekräftige Darstellungen\ngroßer Datensätze",
color="#9999FF",
target="_top",
href="../bokeh/integration/datashader.html"]
geoviews [
label="GeoViews",
tooltip="Analysieren und Visualisieren von\ngeographischen, meterologischen\nund ozeanischen Daten",
color="#9999FF",
target="_top",
href="../bokeh/integration/holoviews/geoviews.html"]
geoviews -- cartopy [color="#9999FF;0.5:#BF80FF"]
geoviews -- holoviews [color="#9999FF"]
geoviews -- geopandas [color="#9999FF;0.5:#BF80FF", style="dashed"]
vaex -- bokeh [color="#9999FF"]
holoviews -- bokeh [color="#9999FF"]
holoviews -- hvplot [color="#9999FF"]
hvplot -- pandas [color="#9999FF;0.5:#BF80FF"]
hvplot -- geopandas [color="#9999FF;0.5:#BF80FF"]
hvplot -- networkx [color="#9999FF;0.5:#BF80FF"]
datashader -- bokeh [color="#9999FF"]
networkx -- bokeh [color="#BF80FF;0.5:#9999FF"]
datashader -- holoviews [color="#9999FF"]
vaex -- mpl [color="#9999FF;0.5:#BF80FF"]
vaex -- bqplot [color="#9999FF;0.5:#4da6ff"]
vaex -- opengl [color="#9999FF;0.5:#FF66B3"]
holoviews -- mpl [color="#9999FF;0.5:#BF80FF"]
datashader -- mpl [color="#9999FF;0.5:#BF80FF"]
// Vega
vega [
label="Vega",
tooltip="Deklarative Sprache für\ninteraktive Visualisierungen",
color="#00FF80",
target="_top",
href="../vega/index.html"]
vega_light [
label="Vega-Lite",
tooltip="High-level-Grammatik für\nkomplexe Vega-Anwendungen",
color="#00FF80",
target="_top",
href="https://github.com/vega/vega-lite"]
pdvega [
label="PdVega",
tooltip="Interaktive Vega-Light-Plots\naus pandas Dataframes",
color="#00FF80",
target="_top",
href="../vega/pdvega/index.html"]
altair [
label="Altair",
tooltip="Deklarative Visualisierung\nin Python",
color="#00FF80",
target="_top",
href="https://altair-viz.github.io/"]
mpl_altair [
label="Matplotlib Altair",
tooltip="Matplotlib-Renderer\nfür Altair",
color="#00FF80",
target="_top",
href="https://matplotlib.org/mpl-altair/"]
vega -- vega_light [color="#00FF80"]
vega_light -- altair [color="#00FF80"]
vega_light -- pdvega [color="#00FF80"]
pdvega -- pandas [color="#00FF80;0.5:#BF80FF"]
altair -- mpl_altair [color="#00FF80"]
// D3.js
d3js [
label="D3.js",
tooltip="Javascript-Bibliothek mit mächtigen\nVisualisierungskomponenten",
color="#4da6ff",
target="_top",
href="../d3js/index.html"]
bqplot [
label="bqplot",
tooltip="Interaktive Plots\nmit D3.js und ipywidgets",
color="#4da6ff",
target="_top",
href="../d3js/bqplot/index.html"]
d3po [
label="d3po",
tooltip="Javascript-Bibliothekt zum\nErstellen von D3.js-Charts",
color="#4da6ff",
target="_top",
href="https://github.com/adamlabadorf/d3po"]
plotly [
label="plotly",
tooltip="Interaktive Graphikbibliothek\nfür Python",
color="#4da6ff",
target="_top",
href="https://github.com/plotly/plotly.py"]
d3js -- bqplot [color="#4da6ff"]
d3js -- plotly [color="#4da6ff"]
d3js -- d3po [color="#4da6ff"]
d3js -- vega [color="#4da6ff;0.5:#00FF80"]
d3js -- javascript [color="#4da6ff;0.5:#00FFFF"]
// Javascript
javascript [
label="Javascript",
tooltip="Skriptsprache, die ursprünglich für\ndynamisches HTML in Webbrowsern\nentwickelt wurde",
color="#00FFFF",
target="_top",
href="../js/index.html"]
pythreejs [
label="pythreejs",
tooltip="Notebook-Extension\nfür WebGL-fähige Webbrowser",
color="#00FFFF",
target="_top",
href="../js/pythreejs.html"]
ipyvolume [
label="IPyvolume",
tooltip="Python-Bibliothek zur\nVisualisierung von\nVolumen und -Glyphen",
color="#00FFFF",
target="_top",
href="../js/ipyvolume.html"]
toyplot [
label="Toyplot",
tooltip="Leichtgewichtige Bibliothek\nfür ästhetische Plots",
color="#00FFFF",
target="_top",
href="https://toyplot.readthedocs.io/"]
ipyleaflet [
label="ipyleaflet",
tooltip="Interaktive Karten für\nJupyter Notebooks",
color="#00FFFF",
target="_top",
href="../js/ipyleaflet.html"]
xarray_leaflet [
label="xarray-leaflet",
tooltip="xarray extension für Kartendarstellungen",
color="#00FFFF",
target="_top",
href="../js/xarray-leaflet.html"]
ipympl [
label="ipympl",
tooltip="Matplotlib\nJupyter Extension",
color="#00FFFF",
target="_top",
href="https://jupyter-tutorial.readthedocs.io/de/latest/ipywidgets/libs/ipympl.html"]
javascript -- ipyvolume [color="#00FFFF"]
javascript -- ipyleaflet [color="#00FFFF"]
ipyleaflet -- xarray_leaflet [color="#00FFFF"]
javascript -- ipympl [color="#00FFFF"]
javascript -- toyplot [color="#00FFFF"]
javascript -- bokeh [color="#00FFFF;0.5:#9999FF"]
javascript -- pythreejs [color="#00FFFF"]
}