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Plot a Continuous Color Palette Python

Using Built-In Continuous Color Scales¶

Many Plotly Express functions accept a color_continuous_scale argument and many trace types have a colorscale attribute in their schema. Plotly comes with a large number of built-in continuous color scales, which can be referred to in Python code when setting the above arguments, either by name in a case-insensitive string e.g. px.scatter(continuous_color_scale="Viridis") or by reference e.g. go.Scatter(marker_colorscale=plotly.colors.sequential.Viridis). They can also be reversed by adding _r at the end e.g. "Viridis_r" or plotly.colors.sequential.Viridis_r.

The plotly.colours module is also available under plotly.express.colors so you can refer to it as px.colors.

When using continuous color scales, you will often want to configure various aspects of its range and colorbar.

Discrete Color Sequences¶

Plotly also comes with some built-in discrete color sequences which are not intended to be used with the color_continuous_scale argument as they are not designed for interpolation to occur between adjacent colors.

Named Built-In Continuous Color Scales¶

You can use any of the following names as string values to set continuous_color_scale or colorscale arguments. These strings are case-insensitive and you can append _r to them to reverse the order of the scale.

In [1]:

                                    import                  plotly.express                  as                  px                  from                  textwrap                  import                  wrap                  named_colorscales                  =                  px                  .                  colors                  .                  named_colorscales                  ()                  print                  (                  "                  \n                  "                  .                  join                  (                  wrap                  (                  ""                  .                  join                  (                  '                  {:<12}                  '                  .                  format                  (                  c                  )                  for                  c                  in                  named_colorscales                  ),                  96                  )))                
aggrnyl     agsunset    blackbody   bluered     blues       blugrn      bluyl       brwnyl bugn        bupu        burg        burgyl      cividis     darkmint    electric    emrld gnbu        greens      greys       hot         inferno     jet         magenta     magma mint        orrd        oranges     oryel       peach       pinkyl      plasma      plotly3 pubu        pubugn      purd        purp        purples     purpor      rainbow     rdbu rdpu        redor       reds        sunset      sunsetdark  teal        tealgrn     turbo viridis     ylgn        ylgnbu      ylorbr      ylorrd      algae       amp         deep dense       gray        haline      ice         matter      solar       speed       tempo thermal     turbid      armyrose    brbg        earth       fall        geyser      prgn piyg        picnic      portland    puor        rdgy        rdylbu      rdylgn      spectral tealrose    temps       tropic      balance     curl        delta       oxy         edge hsv         icefire     phase       twilight    mrybm       mygbm              

Built-in color scales are stored as lists of CSS colors:

In [2]:

                                    import                  plotly.express                  as                  px                  print                  (                  px                  .                  colors                  .                  sequential                  .                  Plasma                  )                
['#0d0887', '#46039f', '#7201a8', '#9c179e', '#bd3786', '#d8576b', '#ed7953', '#fb9f3a', '#fdca26', '#f0f921']              

Continuous Color Scales in Dash¶

Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, click "Download" to get the code and run python app.py.

Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.

Sign up for Dash Club → Free cheat sheets plus updates from Chris Parmer and Adam Schroeder delivered to your inbox every two months. Includes tips and tricks, community apps, and deep dives into the Dash architecture. Join now.

Built-In Sequential Color scales¶

A collection of predefined sequential colorscales is provided in the plotly.colors.sequential module. Sequential color scales are appropriate for most continuous data, but in some cases it can be helpful to use a diverging or cyclical color scale (see below).

Here are all the built-in scales in the plotly.colors.sequential module:

In [4]:

                                import                plotly.express                as                px                fig                =                px                .                colors                .                sequential                .                swatches_continuous                ()                fig                .                show                ()              

Note: RdBu was included in the sequential module by mistake, even though it is a diverging color scale. It is intentionally left in for backwards-compatibility reasons.

Built-In Diverging Color scales¶

A collection of predefined diverging color scales is provided in the plotly.colors.diverging module. Diverging color scales are appropriate for continuous data that has a natural midpoint other otherwise informative special value, such as 0 altitude, or the boiling point of a liquid. These scales are intended to be used when explicitly setting the midpoint of the scale.

Here are all the built-in scales in the plotly.colors.diverging module:

In [5]:

                                import                plotly.express                as                px                fig                =                px                .                colors                .                diverging                .                swatches_continuous                ()                fig                .                show                ()              

Built-In Cyclical Color scales¶

A collection of predefined cyclical color scales is provided in the plotly.colors.cyclical module. Cyclical color scales are appropriate for continuous data that has a natural cyclical structure, such as temporal data (hour of day, day of week, day of year, seasons) or complex numbers or other phase or angular data.

Here are all the built-in scales in the plotly.colors.cyclical module:

In [6]:

                                import                plotly.express                as                px                fig                =                px                .                colors                .                cyclical                .                swatches_cyclical                ()                fig                .                show                ()                fig                =                px                .                colors                .                cyclical                .                swatches_continuous                ()                fig                .                show                ()              

What About Dash?¶

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

                                import                plotly.graph_objects                as                go                # or plotly.express as px                fig                =                go                .                Figure                ()                # or any Plotly Express function e.g. px.bar(...)                # fig.add_trace( ... )                # fig.update_layout( ... )                import                dash                import                dash_core_components                as                dcc                import                dash_html_components                as                html                app                =                dash                .                Dash                ()                app                .                layout                =                html                .                Div                ([                dcc                .                Graph                (                figure                =                fig                )                ])                app                .                run_server                (                debug                =                True                ,                use_reloader                =                False                )                # Turn off reloader if inside Jupyter              

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Source: https://plotly.com/python/builtin-colorscales/

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