Moma Explorer Navio:
A visualization widget to understand and explore your data

Use it to summarize, explore and navigate your multivariate data using three simple interactions:

Sort Filter a Range Filter By Value
Click on a header to sort
Navio sort on les miserables network
Drag to select a range
Moma Explorer
Click on a value to select all instances
Navio select a value with the vispubdata

Try it!

You can test Navio right now with your own CSV or JSON data (less than 200MB), using:

Obervable Notebook Shipyard Jupyter Notebook
Navio-load Observable Shipyard loading data Navio Jupyter Notebooks

Other demos:


Why using something else for summarizing your data?. Here is how Navio compares with other alternatives:

Navio vs Parallel Coordinates

You can use this Notebook to compare Navio with Parallel Coordinates, using your own data. Please be aware that the Vegalite implementation of Parallel Coordinates will break with a few thousand rows (on the image below it broke with 500 rows and 86 attributes of the fifa19 Kaggle Dataset)

Navio versus Parallel Coordinates

Navio vs Scatterplot Matrix

Use this Notebook to compare Navio with a Scatterplot Matrix, using your own data. Please be aware that the Vegalite implementation of the Scatterplot Matrix only support quantitative attributes and will also break with a dozen attributes and a few hundred rows), therefore the image below only displayed 8 attributes (out of the 28) on the scatterplot matrix.

Navio versus Scatterplot Matrix


npm install navio

Or use it from unpkg

  <script type="text/javascript" src=""></script>
  <script src=""></script>
  <script type="text/javascript" src=""></script>

Requires [^popper.js@0.14](, [^d3@4.13]( If you want to use d3@4 use navio@0.0.67



<!DOCTYPE html>
  <!-- Placeholder for the widget -->
  <div id="navio"></div>

  <!-- NAVIO Step 0: Load the libraries -->
  <script type="text/javascript" src=""></script>
  <script src=""></script>
  <script type="text/javascript" src=""></script>

  // NAVIO  Step 1.  Create a Navio passing a d3 selection to place it and an optional height
  var nv = navio("#navio"), 600);

  d3.csv(YOUR_DATA).then(data) => {
    // NAVIO Step 2. Load your data!;

    // NAVIO Step 3. Detect your attributes (or load them manually)

    // Optional, setup a selection callback
    nv.updateCallback( selected => console.log("selected in Navio: ", selected.length));

Step by step

  1. HTML. Start with this template ```html <!DOCTYPE html>
Basic Usage // Your Navio widget goes here
2. **Import Navio**. Create and import a new JavaScript file below the scripts (d3 and Navio) or right in the html like in the example below.
<script src=""></script>
<script type="text/javascript" src=""></script>
<script type="text/javascript">
  1. Create a Navio Instance
var nv = navio("#Navio"), 600); //height 600
  1. [Optional] Configure navio to your liking
// Default parameters
nv.x0 = 0;  //Where to start drawing navio in x
nv.y0 = 100; //Where to start drawing navio in y, useful if your attrib names are too long
nv.maxNumDistictForCategorical = 10; // addAllAttribs uses this for deciding if an attribute is categorical (has less than nv.maxNumDistictForCategorical categories) or ordered
nv.maxNumDistictForOrdered = 90; // addAllAttribs uses this for deciding if an attribute is ordered (has less than nv.maxNumDistictForCategorical categories) or text. Use nv.maxNumDistictForOrdered = Infinity for never choosing Text

nv.howManyItemsShouldSearchForNotNull = 100; // How many rows should addAllAttribs search to decide guess an attribute type
nv.margin = 10; // Margin around navio

nv.levelsSeparation = 40; // Separation between the levels
nv.divisionsColor = "white"; // Border color for the divisions
nv.levelConnectionsColor = "rgba(205, 220, 163, 0.5)"; // Color for the conections between levels
nv.divisionsThreshold = 4; // What's the minimum row height needed to draw divisions
nv.fmtCounts = d3.format(",.0d"); // Format used to display the counts on the bottom
nv.legendFont = "14px sans-serif"; // The font for the header
nv.nestedFilters = true; // Should navio use nested levels?

nv.showAttribTitles = true; // Show headers?
nv.attribWidth = 15; // Width of the columns
nv.attribRotation = -45; // Headers rotation
nv.attribFontSize = 13; // Headers font size
nv.attribFontSizeSelected = 32; // Headers font size when mouse over

nv.filterFontSize = 10; // Font size of the filters explanations on the bottom

nv.tooltipFontSize = 12; // Font size for the tooltip
nv.tooltipBgColor = "#b2ddf1"; // Font color for tooltip background
nv.tooltipMargin = 50; // How much to separate the tooltip from the cursor
nv.tooltipArrowSize = 10; // How big is the arrow on the tooltip

nv.digitsForText = 2; // How many digits to use for text attributes"attribName"); // Shows this id on the tooltip, should be unique

nv.addAllAttribsRecursionLevel = Infinity; // How many levels depth do we keep on adding nested attributes
nv.addAllAttribsIncludeObjects = false; // Should addAllAttribs include objects
nv.addAllAttribsIncludeArrays = false; // Should addAllAttribs include arrays

// Default colors for values
nv.nullColor = "#ffedfd"; // Color for null values
nv.defaultColorInterpolator = d3.interpolateBlues;
nv.defaultColorInterpolatorDate = d3.interpolatePurples;
nv.defaultColorInterpolatorDiverging = d3.interpolateBrBG;
nv.defaultColorInterpolatorOrdered = d3.interpolateOranges;
nv.defaultColorInterpolatorText = d3.interpolateGreys;
nv.defaultColorRangeBoolean = ["#a1d76a", "#e9a3c9", "white"]; //true false null
nv.defaultColorRangeSelected = ["white", "#b5cf6b"];
nv.defaultColorCategorical = d3.schemeCategory10;

// // Discouraged: If you want to break perceptual rules to have many more categories use
// // the following "Piñata mode 🎉"
// nv.defaultColorCategorical = d3.schemeCategory10
//   .concat(d3.schemeAccent)
//   .concat(d3.schemePastel1)
//   .concat(d3.schemeSet2)
//   .concat(d3.schemeSet3);
// nv.maxNumDistictForCategorical = nv.defaultColorCategorical.length;

  1. [Optional] Add your attributes manually. Navio supports six types of attributes: categorical, sequential (numerical), diverging (numerical with negative values), text, date and boolean. You can either add them manually or use nv.addAllAttribs() to auto detect them (must be called after seting the data with
nv.addCategoricalAttrib("attribName", [customScale]);
nv.addSequentialAttrib("attribName", [customScale]);
nv.addDivergingAttrib("attribName", [customScale]);
nv.addTextAttrib("attribName", [customScale]); // Colors by the first nv.digitsForText
nv.addOrderedAttrib("attribName", [customScale]); // Sorts and then colors by rank
nv.addDateAttrib("attribName", [customScale]);
nv.addBooleanAttrib("attribName", [customScale]);

If you ommit the [customScale] parameter it will use the defaults. You can also create your own custom made parameters using nv.addAttrib("attribName", customScale). For example, if you already have a scale for setting the colors of a cluster property on your visualization, you can tell navio to use the same matching colors. Make sure to set the domain and range of the scale, as navio will not try to do it with this function.

var color = d3.scaleOrdinal(d3.schemeSet3)
  .domain["cluster1", "cluster2", "cluster3"];

nv.addAttrib("cluster", color);

  1. Set the data

After loading your data pass it to navio. This will trigger the drawing operation. You can force redrawing using nv.update();;

If your data is a network, or you have some links in the same format of a d3.forceSimulation you can also add them to navio using nv.links([links]). This won’t trigger a redraw, so make sure to call it before setting your data

  1. Detect Attributes. navio also includes a function that detects the attributes automatically, which is slow, redraws the whole thing, and my be buggy. Use it at your own risk. But make sure to call it after setting your data;
  1. Set a callback. A function that navio will call when the user filters/sort the data
    nv.updateCallback( data => console.log("The filtered data is ", data));

Other methods

# nv.update() <>

Use it to force a redraw of navio after changing the underlying data without losing the filters. Useful in case you modify the data with some other action in your code, e.g. you recomputed clusters in a network chart.

# nv.hardUpdate([opts]) <>

Slower update that recomputes brushes and checks for parameters. Use it if you change any parameters or added new attributes after calling .data. opts can be an object that contains any of the following attributes:

# nv.getColorScales(attr ) <>

Returns the color scale for a certain attribute, make sure to pass an attribute that has been already added

# nv.getAttribs( ) <>

Returns the ordered list of attributes added to navio


Navio.js is licensed under the MIT license. (