A bar chart shows a numeric value broken down by a category. The length or height of each rectangular bar corresponds to the value it represents, allowing for easy comparison of quantities across various categories. Learn more about bar charts.
Collaborative analytics is an approach to data analysis that involves bringing team members, such as engineers, domain experts, and business managers into the data analysis process from ideation to final data product. It offers numerous benefits, including stronger analysis, faster decision-making, and fewer back-and-forths between analysts and stakeholders. Learn more about collaborative analytics.
Created in 2011 by Mike Bostock, D3 (or D3.js) is a free, open-source JavaScript library for visualizing data. D3 uses a low-level approach built on web standards, which gives you unparalleled flexibility to build dynamic, data-driven graphics. In addition to powering award-winning visualizations, D3 has become a foundational building block of higher-level chart libraries. There is a vibrant community of data practitioners around the world that use D3. To find examples of what you can create in D3, check out Observable’s D3 gallery. Learn more about D3.
Dashboard rot describes the process by which a dashboard loses its effectiveness and value for decision-making, usually through insufficient maintenance, infrequent updates, or poor planning. As a result, its intended audience will view inaccurate data, or ignore it and seek answers elsewhere.
Data loaders are programs that can be written in any language to access, wrangle, and analyze data. Observable Framework uses data loaders to deliver faster performance by performing bulky data processing on build instead of on page load. Data loaders give you the ability to create fast data apps powered by any language on the back-end, with powerful interactive visualizations created in JavaScript on the front-end. Learn more about data loaders.
A database is the main way that companies collect and store data they need to answer business questions. Most databases are relational databases, which means that the data is stored in tables that are related by key fields. This allows you to work with data by running queries, joining tables, and so on. Learn more about databases in this article.
A donut chart is a chart type that shows the proportion of a value to the whole. Donut charts are similar to pie charts, but they have an empty space in the center. Donut charts are often used to illustrate progress toward goals and resource allocation. Learn more about donut charts.
A histogram visualizes the frequency distribution of numeric variables, with bars representing the binned counts of observations over a range of values. It provides a clear and intuitive look into the shape of the data, giving viewers a quick look at important characteristics like skew, modality (e.g. unimodal or bimodal), and outliers. Learn more about histograms.
Joining tables is the process of combining records from two or more tables in order to analyze related variables that are stored separately in a database. There are a number of join types, including left, inner, and full joins, that determine what is returned when merging records.
A line chart displays trends by connecting sequential data points with a line. Typically, the horizontal x-axis shows a progression of values, while the vertical y-axis indicates the corresponding values for a chosen metric. This common chart type is effective for visualizing time-series data.
Linked brushing connects visualizations for enhanced data exploration. Brushing data in one chart dynamically updates linked charts to show the corresponding subset, enabling cross-filtering and the exploration of arbitrary data subsets for nuanced insights beyond predefined categories. Learn more about linked brushing.
Observable Canvases are a new, collaborative data canvas that can be used to explore data, conduct analysis, and build stunning charts and dashboards. Canvases have AI integrated into the platform and whiteboarding features making it easy to work together with cross-functional team members. Learn more about canvases.
Observable Framework is a free, open-source, static-site generator for data apps. Framework uses a local, file-based workflow. Data visualization developers choose Observable Framework for its polyglot workflow, data loaders, and static-site architecture which deliver superior data app performance.
Observable Notebooks are live, browser-based, computational notebooks that can be used for interactive data visualization, animation, learning, and experimentation. Developers use notebooks to combine Markdown, JavaScript, HTML, and SQL for expressive dynamic documents, charts, and apps. Developers choose Observable Notebooks because of the built-in reactivity, ease of connecting to any data source, and robust community examples. Learn more about notebooks.
Observable Plot is a free, open-source, JavaScript library that is used for creating visualizations of tabular data. Plot has a concise, expressive interface and features scales and layered marks to construct charts in the grammar of graphics style. The Observable Plot gallery offers many examples that you can learn from and copy-paste to more quickly get started. Learn more about Observable Plot.
A pie chart is a type of data visualization that shows proportions of a value as part of a whole. This chart type is sometimes considered controversial because it can easily be misused or misinterpreted. Donut charts are pie charts with a hole in the middle. Learn more about pie charts.
A radar chart, also known as a radar plot or spider chart, is a type of polar line chart. It consists of several axes radiating from a central point, with each axis representing a different data dimension. For each data item being visualized, a point is plotted on each axis corresponding to its value for that dimension. These points are then connected by lines, forming a polygon that resembles a spider web. Learn more about radar charts.
A Sankey diagram (also known as a Sankey chart) is a type of data visualization that illustrates the movement or flow of values through different stages of a system or over time. Quantities are usually represented by the width of bands at any stage.
A scatter plot, also known as a scatter chart or scatter graph, is a visualization that displays values for two distinct numerical variables. Scatter plots are used to show the relationships between variables and explore anomalies in the data. Each data point is represented by a mark (usually a dot) whose position on the horizontal and vertical axes corresponds to its respective values.
SQL stands for Structured Query Language (usually pronounced “sequel”) and is a programming language used to query relational databases.
Time series data is a sequence of data points collected over a period of time, ordered by the time they were recorded. It's used to track trends, identify patterns, and make predictions by analyzing how values change over time. Learn more about how to analyze time series data.
A treemap is a chart type that subdivides space to show the proportions of a value as part of the whole. Learn more about treemaps.