> For the complete documentation index, see [llms.txt](https://dots.gitbook.io/dots-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://dots.gitbook.io/dots-docs/reporting/more-about-widgets.md). # More about Widgets Dots offers three broad families of widgets. This section is a quick tour of what each one is for — see the widgets page above for detailed configuration of every setting. ### Different types of widgets **Chart widgets — for structured and quantitative data**\ These visualise counts, distributions, and relationships across your structured fields. * **Metric Card** — a single headline number: a document count or a statistic such as an average, median, or percentile. Ideal for top-of-report orientation stats, and the right tool when you need one specific figure (for example, the average income for a single group). * **Bar Chart** — the distribution of records across a category, shown as counts or percentages. Best for “how many fall into each group” questions. * **Pie Chart** — composition shown as a donut, or a nested sunburst of up to four layers for hierarchical breakdowns (for example, Caste → Education → Occupation). * **Heat Map Grid** — a two-axis grid where colour shows count. This is the best widget for cross-tabulation and intersectional questions, such as caste × education. * **Line Chart** — trends over time. Useful only when your data has a meaningful date field, such as a survey wave or follow-up date. * **Sankey Chart** — a flow diagram across ordered steps. Great for journeys and processes (for example, application → approval → disbursement). **AI widgets — for qualitative text**\ These are where richly-annotated, text-heavy datasets really shine. * **AI Summary** — an AI-generated summary of one qualitative field, optionally filtered. Run it as filtered pairs (same prompt, different group) for powerful side-by-side comparison. * **AI Categorization** — surfaces NLP results for a field: categories, sentiment (polarity and emotion), named entities, or annotations. A good at-a-glance pulse check. * **Ask AI** — a free-form question answered from your data. The most flexible widget: use it for direct comparisons across groups, synthesis across the whole dataset, or reason-finding. **Content widgets — for evidence and framing**\ These show the raw material and give the report its structure. * **Annotation Explorer** — a scrollable grid of annotation and highlight cards, filterable by tag or theme. Perfect for showing the receipts behind a claim. * **Responses List** — every response for one text field, paginated and filterable. A strong closing widget that lets readers browse raw content after the analysis. **Custom widgets — for bringing in more data**\ These widgets are where you can add in your own data * **Visualize Table** — a simple bar chart built from numbers you type in yourself. Handy for a one-off illustrative figure, but static: it does not update as the dataset changes. * **Text** — a static text block with no data source. Use it for section headers and short framing paragraphs that guide the reader through the report. This block supports links, embeddings, images, etc. ### Widget configuration options While every widget has its own settings, most share a common set of configuration options: * **Input (required)** — the field the widget visualizes. This is the one setting you should always configure first. * **Select option** — an extra choice on top of the input for certain widgets (for example, picking which statistic a Metric Card should show). * **Visibility options** — let you hide specific values from the visualization to keep it focused. * **Second input** — required by two-input widgets before they will render (for example, the two axes of a Heat Map Grid). * **Breakdown** — available on most widgets; splits the visualization by an additional field to add a second layer of detail. * **Widget-level filters** — present on every widget, letting you scope an individual widget to a subset of the data independently of the report's global filters.
### Step-by-step video guides Here you will find step-by-step videos to help you use the widgets in the Reports feature. Each video guides you through setup and configuration while explaining the key features of each widget. You can come back to these videos anytime you need help configuring widgets in your reports.
Pie Chart A pie chart can help you show how different parts make up a whole, with each slice representing a category’s share of the total, so it’s easy to see major proportions at a glance. Adding layers (nested rings) lets you show more than one level of detail. For example, breaking each main category into sub-group, while still keeping the idea of parts of a whole clear. {% embed url="" %}
Bar Chart A bar chart compares values across different categories using rectangular bars, where the length represents the magnitude. You can also apply breakdown the bars with other fields so you can easily see how sub-categories contribute to the overall distribution, making comparisons between groups and within each group simple and clear. {% embed url="" %} Bar charts for number fields have additional features like manual ranges and aggregates of multiple fields. {% embed url="" %}
Heat Map A heatmap grid widget shows data in a two-dimensional layout, where each cell is color-coded based on its value. This makes it easy to quickly spot patterns, trends, and high or low areas at a glance without focusing on exact numbers. {% embed url="" %}
Metric Card A metric card displays a single key value, making it easy to quickly understand an important number at a glance. It often includes a label, the current value, and sometimes a comparison like a trend or change, helping you track performance or status without extra detail. {% embed url="" %} Metric Card for number fields have additional features like manual ranges and aggregates of multiple fields. {% embed url="" %} Metric Card widget can also display the total number of published documents for a selected content type. {% embed url="" %}
Line Chart A line chart helps you track how a data field changes over time, with data points connected to show trends. It makes it easy to spot patterns like growth or decline at a glance. Adding a breakdown will create multiple lines which can be used to compare trends across different groups or demographics over the same time period. {% embed url="" %}
Sankey Chart A Sankey chart shows how quantities flow from one stage to another, with the width of each connection representing its magnitude. It’s useful for understanding how data or users move through a system. This makes it easy to identify dominant paths, drop-offs, and key transitions in a process. {% embed url="" %}
Annotations An annotations list displays tagged insights extracted from your data in a structured format. It helps you quickly filter and review key themes or noteworthy excerpts without going through the full dataset. This makes it easier to focus on what matters and navigate insights efficiently. {% embed url="" %}
Responses list A responses list shows individual responses or entries collected in your dataset. It allows you to filter and explore raw data in detail, making it useful for validating insights, spotting nuances, or diving deeper into specific responses. {% embed url="" %}
AI Categorization This categorization widget uses AI to group your data into meaningful categories based on patterns and content. It helps organize large volumes of unstructured qualitative data into structured themes, making analysis faster and more scalable. You can quickly see how responses are distributed across different categories. {% embed url="" %}
AI Summary An AI summary provides a concise overview of your data by highlighting key themes, patterns, and insights. It reduces the need to manually review large datasets by surfacing the most important takeaways. This helps you quickly understand the overall narrative and direction of the data. {% embed url="" %}
Ask AI Ask AI allows you to interact with your data using natural language questions. Instead of manually analyzing, you can simply ask questions and receive relevant insights or summaries instantly. This makes exploration more intuitive and flexible, especially for complex datasets. Ask AI has capability to filter the dataset which you want AI to consider while answering your questions. {% embed url="" %}
Text A static text widget displays fixed content such as explanations, instructions, or contextual information. It helps provide clarity and guidance alongside your data visualizations, ensuring users understand what they are looking at or how to interpret it. You can attach images, links, PDFs in this widget. {% embed url="" %}
Visualize Table The Visualize Table widget allows you to manually input data and instantly visualize its distribution using a bar chart. This is especially helpful when certain data isn’t available on the platform but you still need a quick visual comparison. {% embed url="" %}