Copy & paste your data
Select your data (including header row/column) in Excel or LibreOffice and paste it in the text field. You can also upload a CSV or Excel file from your computer.
If you just want to try Datawrapper, here‘s a list of some example datasets you can use:
Upload your dataset, clean it in a spreadsheet-like editor, and generate publication-ready charts in just a few steps.
Paste values, upload a CSV/XLSX file, or connect to a Google Sheet to bring in your dataset.
Pick from bar, line, pie, doughnut, radar, polar, scatter, or bubble charts and preview instantly.
Customize colours, toggle dark mode, and download the visual as a PNG snapshot for presentations.
Common use cases: (1) Present survey results with grouped bar charts; (2) Showcase time-series metrics using line charts; (3) Highlight composition with pie or doughnut charts; (4) Explore correlations using scatter/bubble charts; (5) Prepare quick visuals for stakeholder updates.
Width = D × cos(θ) Height = D × sin(θ) (applied internally to calculate coordinates)
Table of values entered or uploaded by the user
Visualization style applied to the dataset
Colour palette applied to series and backgrounds
1. Paste monthly sales figures (Jan–Dec) 2. Choose “Bar Chart” and preview 3. Switch to the “Warm Reds” palette 4. Download the chart as PNG for a slide deck
You can visualize various types of data, including numerical, categorical, and time series data. This flexibility allows you to explore different patterns and trends in your data. The tool supports multiple formats, making it easy to upload and visualize your data.
The choice of chart type depends on the nature of your data and the story you want to tell. For example, use a bar chart to compare categorical data, a line chart for time series data, or a scatter plot to explore relationships between variables. Consider what you want to highlight in your data and choose a chart type that effectively communicates your message.
Yes, you can customize the appearance of your charts and graphs to suit your needs. You can modify colors, fonts, labels, and other visual elements to create a presentation-ready visualization. This flexibility allows you to tailor your visualizations to your specific use case, whether it's for a report, presentation, or exploratory analysis.
Interpreting the results of your data visualization involves understanding the patterns, trends, and relationships in your data. Look for notable features, such as outliers, correlations, or anomalies, and consider the context in which your data was collected. By carefully examining your visualization, you can gain insights that inform decision-making, identify areas for further investigation, or support your findings with compelling visual evidence.
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