Datawrapper

1. Datawrapper: A Beginner's Guide to Data Visualization for Wiki Contributors

Datawrapper is a powerful, yet surprisingly accessible, tool for creating interactive and embeddable charts, maps, and tables. For MediaWiki editors looking to enhance their articles with compelling data visualizations, Datawrapper provides a user-friendly solution without requiring advanced coding or design skills. This article will serve as a comprehensive guide for beginners, covering everything from account creation and data import to chart customization and embedding into your wiki pages. We will also discuss best practices for using Datawrapper effectively and ethically within the context of a collaborative knowledge base.

1. 1. What is Datawrapper and Why Use It?

Datawrapper is a web-based application designed specifically for data visualization. Unlike general-purpose spreadsheet programs or complex graphic design software, Datawrapper focuses on creating clear, concise, and interactive visuals optimized for online publication. Its core strengths lie in its simplicity, responsiveness (charts adapt to different screen sizes), and ease of embedding in various platforms, including, crucially, MediaWiki.

Here's why you should consider using Datawrapper for your wiki contributions:

• **Ease of Use:** Datawrapper requires no prior knowledge of data visualization principles or coding. Its intuitive interface guides you through the process step-by-step.
• **Interactive Charts:** Datawrapper charts aren't static images. Users can hover over data points for details, filter data, and sort tables, enhancing engagement and understanding.
• **Responsiveness:** Charts automatically adjust to fit different screen sizes, ensuring a consistent viewing experience on desktops, tablets, and mobile phones. This is particularly important for a wiki aiming for accessibility.
• **Embeddability:** Datawrapper provides a simple embed code that can be directly pasted into the wikitext of your wiki pages.
• **Accessibility:** Datawrapper prioritizes accessibility, generating charts with appropriate alt text and adhering to web accessibility standards.
• **Collaboration:** Datawrapper offers team accounts, allowing multiple editors to collaborate on data visualizations.
• **Free Tier:** Datawrapper offers a generous free tier suitable for most wiki projects. Paid plans are available for advanced features and higher usage limits.

1. 1. Getting Started with Datawrapper

1. 1. 1. Account Creation

1. Navigate to [1](https://datawrapper.com/). 2. Click on the "Sign up" button. 3. You can sign up using your email address, a Google account, or a GitHub account. 4. Follow the on-screen instructions to complete the registration process. You may need to verify your email address.

1. 1. 1. Understanding the Datawrapper Interface

Once logged in, you'll be greeted by the Datawrapper dashboard. The interface is relatively straightforward:

• **New Chart:** This button initiates the process of creating a new visualization.
• **My Charts:** This section lists all the charts you've created.
• **Team:** (If applicable) Manage team members and settings.
• **Account Settings:** Manage your profile, billing information, and other account preferences.
• **Help:** Access Datawrapper's documentation and support resources.

1. 1. Creating Your First Visualization

Let's walk through the process of creating a simple line chart.

1. **Start a New Chart:** Click the "New Chart" button. 2. **Choose a Chart Type:** Datawrapper offers a variety of chart types, including:

   * **Line Chart:**  Ideal for showing trends over time.  See [Trend Following](https://www.investopedia.com/terms/t/trendfollowing.asp) for strategies using line charts.
   * **Bar Chart:**  Useful for comparing values across different categories.  [Candlestick Patterns](https://www.investopedia.com/terms/c/candlestick.asp) often utilize bar charts.
   * **Pie Chart:**  Shows proportions of a whole.  Use with caution, as they can be difficult to interpret accurately.
   * **Scatter Plot:**  Displays the relationship between two variables.  Useful for [Correlation Analysis](https://www.investopedia.com/terms/c/correlationcoefficient.asp).
   * **Map:**  Visualizes data geographically.
   * **Table:**  Presents data in a tabular format.  [Technical Analysis](https://www.investopedia.com/terms/t/technicalanalysis.asp) often relies on data presented in tables.

3. **Select "Line Chart"** for this example. 4. **Data Import:** Datawrapper supports several methods for importing data:

   * **Copy & Paste:**  The simplest method for small datasets.  Paste your data directly into the Datawrapper editor.
   * **Upload CSV:**  Upload a comma-separated value (CSV) file.  This is the most common method for larger datasets.
   * **Google Sheets:**  Connect to a Google Sheet and import data directly.
   * **API:**  For advanced users, Datawrapper offers an API for programmatic data import.

5. **Paste Sample Data:** For demonstration, paste the following data into the Datawrapper editor:

``` Year,Sales 2018,100 2019,150 2020,120 2021,180 2022,200 ```

6. **Datawrapper automatically recognizes the headers** and data types. Verify that the columns are correctly identified (Year as Category, Sales as Value). 7. **Customize Your Chart:** The "Customize" tab allows you to modify the appearance of your chart. You can change:

   * **Title:** Add a descriptive title to your chart.
   * **Axis Labels:**  Label the x and y axes clearly.
   * **Colors:**  Choose colors that are visually appealing and accessible.  Consider using a [color palette generator](https://coolors.co/) for harmonious color schemes.
   * **Line Style:** Modify the thickness and style of the line.
   * **Gridlines:**  Add or remove gridlines to improve readability.
   * **Annotations:** Add annotations to highlight specific data points.  Understanding [Fibonacci Retracements](https://www.investopedia.com/terms/f/fibonacciretracement.asp) often involves annotating charts.

8. **Preview Your Chart:** The preview window shows you how your chart will look. Experiment with different customization options until you achieve the desired appearance. Refer to [Elliott Wave Theory](https://www.investopedia.com/terms/e/elliottwavetheory.asp) for examples of complex chart annotations. 9. **Publish Your Chart:** Click the "Publish" button. Datawrapper will generate an embed code that you can copy and paste into your MediaWiki page.

1. 1. Embedding Datawrapper Charts into MediaWiki

1. **Copy the Embed Code:** After publishing your chart, Datawrapper will display an embed code. It will look something like this:

```html <iframe src="https://datawrapper.de/embed/xxxxxxxx" width="600" height="400" frameborder="0"></iframe> ```

2. **Paste the Embed Code into your Wiki Page:** In the MediaWiki editor, switch to the "Edit source" mode. Paste the embed code directly into the wikitext where you want the chart to appear. 3. **Save the Page:** Save the wiki page. The chart should now be visible on the page. 4. **Adjusting Size:** The `width` and `height` attributes in the embed code control the size of the chart. You can adjust these values to fit the layout of your wiki page. Consider using percentages for responsive sizing (e.g., `width="100%"`).

1. 1. Advanced Datawrapper Features

• **Maps:** Datawrapper's map functionality allows you to visualize data geographically. You can import data based on countries, regions, or even custom geographic areas. Explore [Choropleth Maps](https://datawrapper.com/blog/how-to-make-a-choropleth-map/) for visualizing regional data.
• **Tables:** Create interactive tables with sorting and filtering capabilities. Useful for presenting detailed data that doesn't lend itself to charting. [Moving Averages](https://www.investopedia.com/terms/m/movingaverage.asp) are often presented in tabular format.
• **Filters:** Add filters to your charts and tables to allow users to explore different subsets of the data.
• **Themes:** Apply pre-defined themes to quickly change the overall appearance of your visualizations.
• **Team Collaboration:** Share your charts with other Datawrapper users and collaborate on projects.
• **Pro Plans:** Datawrapper offers paid plans with advanced features, such as custom branding, higher usage limits, and priority support. Understanding [Relative Strength Index (RSI)](https://www.investopedia.com/terms/r/rsi.asp) often requires analyzing data continuously, which may necessitate a pro plan.

1. 1. Best Practices for Using Datawrapper in Wiki Contributions

• **Data Accuracy:** Always verify the accuracy of your data before creating a visualization. Incorrect data can mislead readers and damage the credibility of your wiki.
• **Chart Clarity:** Choose the appropriate chart type for your data. Avoid using charts that are difficult to interpret or that obscure the underlying data. Understand the principles of [Gestalt Principles of Visual Perception](https://www.interaction-design.org/literature/topics/gestalt-principles) to improve clarity.
• **Accessibility:** Ensure that your charts are accessible to users with disabilities. Use clear labels, alt text, and color contrast.
• **Context:** Provide sufficient context for your visualizations. Explain what the data represents and what conclusions can be drawn from it. Consider adding a caption explaining the [Bollinger Bands](https://www.investopedia.com/terms/b/bollingerbands.asp) if you're using them in a chart.
• **Ethical Considerations:** Avoid using data visualizations to manipulate or mislead readers. Present data fairly and objectively. Be aware of potential [cognitive biases](https://thedecisionlab.com/biases) that could influence your interpretation of the data.
• **Maintainability:** Datawrapper charts are linked to the original data. If the source data changes, the chart will update automatically. However, ensure your source data remains accessible and stable.
• **Licensing:** Be mindful of the licensing terms of any data you use in your visualizations. Ensure that you have the right to use and distribute the data.
• **Keep it Simple:** Avoid overly complex charts with too much information. Focus on conveying a clear and concise message. Consider the principles of [Information Visualization](https://www.interaction-design.org/literature/topics/information-visualization).
• **Responsive Design:** Test your charts on different devices to ensure they are responsive and display correctly on all screen sizes. Using [adaptive layouts](https://www.w3schools.com/css/css_responsive.asp) within your wiki theme can further enhance responsiveness.
• **Consider Alternatives:** While Datawrapper is excellent, sometimes a simple table or even just text is more effective. Don't force a visualization if it doesn't add value. Explore [Gap Analysis](https://www.investopedia.com/terms/g/gap-analysis.asp) – sometimes a clear textual description is better than a complex visual.

1. 1. Troubleshooting Common Issues

• **Chart Not Displaying:** Ensure that the embed code is pasted correctly into the wikitext. Check your browser's developer console for errors.
• **Chart Size Incorrect:** Adjust the `width` and `height` attributes in the embed code.
• **Data Not Updating:** If you've updated the source data, republish the chart in Datawrapper.
• **Accessibility Issues:** Review Datawrapper's accessibility documentation and ensure that your charts meet accessibility standards. Consider using [WCAG guidelines](https://www.w3.org/WAI/standards-guidelines/wcag/) for web content accessibility.

1. 1. Resources

• **Datawrapper Documentation:** [2](https://datawrapper.com/docs/)
• **Datawrapper Blog:** [3](https://datawrapper.com/blog/)
• **Datawrapper Tutorials:** [4](https://datawrapper.com/tutorials/)

Data Visualization MediaWiki Extension Wiki Template Chart Types Data Import Interactive Charts Accessibility Embed Code CSV File Google Sheets