app.rawgraphs.io

What is RAWGraphs 2.0?

RAWGraphs 2.0 is a browser-based tool for turning tabular data into charts without writing code. You paste or upload a dataset, choose a chart type, and map your columns to visual dimensions such as x-axis, y-axis, size, or color. It is best understood as a data-visualization workspace rather than a full analytics platform: its strength is fast, flexible chart construction from pasted or uploaded data.

Its audience is broad. A journalist can build a quick bar or line chart for a story; a researcher can explore survey results; a designer can produce a chart to refine in a graphics editor; a student can learn how data maps to visual variables. Because it runs in the browser, it suits people who want to avoid installing desktop software or writing plotting code.

A practical way to use it: prepare a clean table with one row per observation and clear column headers, paste it in, select a chart family, then drag fields onto the available dimensions. If the result looks wrong, the usual fixes are checking data types, removing blank rows, or simplifying the field mapping.

One caveat: the page itself only reports that JavaScript must be enabled to run the app, so the interface and features depend on a working browser session. For static publishing, a code-based library may be a better fit; for quick visual exploration, RAWGraphs is the more direct route.

How do I create a chart from a spreadsheet in RAWGraphs 2.0?

RAWGraphs 2.0 is a browser-based tool for turning tabular data into charts: you paste or upload a spreadsheet, drag fields onto visual variables, then export the result. Because the page itself is a JavaScript app, the workflow happens entirely in the browser after the app loads.

A practical workflow

1. Prepare your data as a flat table: one header row, one row per record, no merged cells or totals rows. CSV or TSV exports from Excel, Google Sheets or Numbers work best.
2. Open RAWGraphs 2.0 and load the data by pasting it into the input area or dropping a file onto the page.
3. Check the parsing preview. If columns are split wrongly, change the delimiter or the number/date parsing options before continuing.
4. Pick a chart type from the gallery — for example a bar chart for category comparisons, a scatterplot for two numeric variables, or an alluvial diagram for flows between stages.
5. Drag spreadsheet columns onto the dimensions offered by that chart (such as X, Y, size, color, label). The preview updates as you map fields.
6. Adjust scales, sorting and colors, then export as SVG (best for further editing in Illustrator or Inkscape), PNG (quick sharing) or a JSON project file if you want to keep working later.

Example

Suppose a spreadsheet lists region, month, sales and channel. For a stacked bar chart, drag month to X, sales to Y and channel to color; the same table can become a scatterplot by mapping sales to one axis and another numeric column to the other.

Trade-offs to keep in mind

• RAWGraphs is strongest for unusual chart types that spreadsheet apps do not offer, and for quick visual exploration without coding.
• It is weaker for live, recurring dashboards: each update generally means reloading data and redoing the mapping.
• Very large tables can slow a browser tab, so filter or aggregate first if performance drops.

If you only need a standard bar or line chart that updates automatically, a spreadsheet's built-in chart tools may be faster. If you need a diagram type the spreadsheet cannot draw, RAWGraphs is the more direct route.

What chart types can I make with RAWGraphs 2.0?

RAWGraphs 2.0 is built around a library of chart templates rather than a free-form chart builder, so the chart types you can make are the ones in its template gallery. The app itself is a browser-based React tool, so the exact current list is always shown inside the tool after you load a dataset.

The practical way to answer this for your own data is to open RAWGraphs 2.0, paste or upload a table, and scroll the chart template picker. It groups choices by what your data can support—such as charts for one categorical field, charts for a numeric value across categories, charts for relationships between two numeric fields, and charts for hierarchies or flows.

Typical categories in the gallery

• Categorical and ranking charts — bar charts, circular or radial variants, and similar layouts for comparing values across named groups.
• Part-to-whole charts — stacked layouts, treemaps, and similar views when you want to show composition.
• Relationship and correlation charts — scatterplots and bubble-style views when you have two or more numeric fields.
• Hierarchy and network charts — tree and cluster-style layouts for parent-child data, and network diagrams for linked entities.
• Time-oriented charts — line and area-style layouts when one field is a date or ordered sequence.
• Flow and change charts — alluvial or Sankey-style diagrams for movement between states.

How to choose

The template picker tells you which fields it expects. If a chart is greyed out or asks for a field type you do not have, that chart is not available for your current table. This is the real constraint: chart type depends on your column types, not just on preference.

For example, if you have a column of countries, a column of years, and a column of values, the tool will offer time-series and categorical comparison templates. If you instead have a source column, a target column, and a weight column, it will steer you toward flow or network templates.

A useful next step: load a small sample of your data and check which templates accept your exact column types before designing a full visualization. If you need a chart outside the gallery, you would export the data and finish the chart in a general-purpose tool such as Observable or a spreadsheet, rather than expecting RAWGraphs to generate it.

How do I export a RAWGraphs 2.0 visualization for a presentation or website?

RAWGraphs 2.0 runs as a browser app, so exporting is a matter of choosing the right output for where the chart will live. For a slide deck or a printed handout, export a static image; for a live website or dashboard, export the vector or code-friendly format so the graphic stays sharp at any size.

Export formats and where they fit

• SVG — best for websites and any scalable use. It stays crisp when resized or zoomed, and you can open it in a vector editor to adjust colors, labels or spacing before publishing.
• PNG — best for presentations, documents and email. It is a flat raster image, so pick a high resolution if you plan to enlarge it on a slide.
• Other raster or vector options — the export menu may offer additional image types; choose the one your slide software or CMS accepts without conversion.

A practical workflow

1. Build the chart in RAWGraphs and check labels, legend and color choices at the size you will actually use.
2. Use the export button and pick SVG if the destination is a website, PNG if it is a slide or document.
3. Open the exported file in a vector editor (for SVG) or image editor (for PNG) to trim whitespace, enlarge fonts or add a title.
4. Insert the file into your presentation or upload it to your site, then preview it at the real display size.

Choosing between them

A quick reader scenario

Suppose you are preparing a conference talk. Export a high-resolution PNG for the slides, but also keep an SVG in case a colleague wants to reuse the chart in a web article. If the chart will be embedded in a page you maintain, SVG is usually the better long-term choice because it survives redesigns and retina displays.

The app itself is hosted at RAWGraphs 2.0, and the project's documentation and examples live at RAWGraphs. If you need a vector editor for final tweaks, Inkscape is a free option.

Can I use RAWGraphs 2.0 without installing anything or uploading my data to a server?

Yes. RAWGraphs 2.0 runs in your browser as a web app, so there is nothing to install. It is designed around a local, client-side workflow: you load your data, map it to a chart, and export the result, all within the page.

The one practical caveat is that it is a JavaScript application, so JavaScript must be enabled for the app to run at all. If your browser blocks or disables JavaScript, you will see only a blank page rather than the editor.

How the workflow usually goes

1. Open the app and paste or drag in a dataset (for example, a CSV export from a spreadsheet).
2. Choose a chart type and drag fields onto the visual variables (such as x, y, size, color).
3. Adjust the layout and export the chart as a vector or image file for use in a report or slide deck.

Privacy and practical considerations

• Because processing happens in the browser, your data does not need to be sent to a remote server just to draw the chart. That makes it a reasonable choice for internal or sensitive tabular data, subject to your own organization's rules.
• Work is tied to the browser session. If you reload or close the tab without saving, your mappings may be lost, so export or save your project as you go.
• Very large datasets can be limited by your machine's memory and the browser, not by a server quota.
• If you need a reproducible pipeline or automated updates, a browser tool is a weaker fit than a scripted library.

Choosing between this and alternatives

A useful next step: try it with a small anonymized sample of your real dataset first, confirm the chart types you need are available, and check the export formats match your final destination (for example, editable vector output for print). For general background on the project, see RAWGraphs.

How does RAWGraphs 2.0 compare to using Excel or Google Sheets for data visualization?

RAWGraphs 2.0 is a browser-based chart builder aimed at people who want unusual, publication-ready graphics without writing chart code. It sits in a different category from Excel and Google Sheets: those are spreadsheets that happen to include charting, while RAWGraphs is a dedicated visualization tool that expects you to paste or upload data, then map columns onto visual variables.

Where RAWGraphs fits best

Its strength is chart types that spreadsheets do not offer, or offer only in a fixed form. You paste tabular data in, choose a layout, and drag fields onto axes, size, color and labels. The output is an SVG file you can open in a vector editor such as Illustrator or Inkscape and restyle. That workflow appeals to designers, data journalists and researchers who care about typography, spacing and custom annotation.

The trade-off is that RAWGraphs is not a live data tool. There is no formula engine, no shared workbook, no automatic refresh when a source updates. Each chart is a snapshot of the data you loaded, so repeated reporting means repeating the import-and-export cycle.

Where Excel and Sheets win

For everyday business questions — monthly totals, year-over-year comparisons, quick pivot charts — a spreadsheet is faster because the data, calculations and chart live together. Google Sheets adds real-time collaboration and easy sharing, which RAWGraphs does not attempt. Excel adds PivotCharts, slicers and a large library of built-in chart types.

If your audience needs to filter, drill down or update numbers themselves, staying in the spreadsheet is usually the right call.

A quick comparison

A practical decision rule

Ask one question: does the chart need to be updated or filtered by someone else? If yes, use Excel or Google Sheets. If the chart is a one-off graphic that must look a specific way, use RAWGraphs.

A concrete example: a marketing analyst preparing a quarterly board deck might build the underlying numbers in Google Sheets, then paste the final table into RAWGraphs to produce a clean alluvial diagram of customer flows. The spreadsheet remains the source of truth; RAWGraphs produces the artifact.

To try it, open RAWGraphs 2.0 and load a small sample dataset first — a handful of rows is enough to learn how the column-mapping works before committing a real project to it.