数值如何随时间演变?
可视化数据中的趋势、模式和时间变化。非常适合跟踪进度、识别季节性或预测未来值。
Based on the FT Visual Vocabulary • 72 chart types across 10 categories
根据您想要传达的内容选择最佳数据可视化。将您的数据类型和目标与这 10 个图表类别进行匹配。
可视化数据中的趋势、模式和时间变化。非常适合跟踪进度、识别季节性或预测未来值。
比较不同类别的大小和数量。非常适合显示相对差异和进行直接的数值比较。
展示各个组成部分如何构成完整的图景。最适合成分分析、百分比分解和层次数据。
突出显示与零、平均值或目标等参考点的变化。适用于显示正/负表现和情感分析。
发现两个或多个变量之间的模式和联系。对于统计分析、趋势识别和假设检验至关重要。
按值排序显示项目以展示相对位置。非常适合排行榜、前/后列表、竞争分析和绩效排名。
了解数据点的频率和分布。对于统计分析、识别异常值和理解数据形态至关重要。
跟踪实体之间的移动、转移和连接。非常适合展示流程、迁移、用户旅程和资源分配。
在地图上显示具有地理背景的数据。对于区域分析、基于位置的洞察和理解地理分布模式至关重要。
有些数据故事需要不符合传统类别的独特图表类型。这些专业图表服务于特定的分析和组织需求。
Common questions about data visualization types and how to choose the right chart
The Atlas of Charts is a comprehensive visual reference guide featuring 72 data visualization types organized into 10 categories. It was created to help data analysts, business professionals, and designers quickly identify the most appropriate chart type for their specific data story. Think of it as a periodic table for data visualization.
Charts are organized into 10 functional categories based on the analytical question they answer: Change over Time (13 charts), Magnitude (10), Part-to-whole (10), Deviation (4), Correlation (5), Ranking (6), Distribution (9), Flow (4), Spatial (8), and Other (3). This organization helps you start with your data question and find the right visualization.
ChartGen currently supports 9 chart types with full AI-powered generation: Line Chart, Bar Chart, Pie Chart, Area Chart, Scatter Plot, Heatmap, Combo Chart, Waterfall Chart, and Funnel Chart. These charts are marked with a green 'LIVE' badge in the atlas. We're continuously adding support for more chart types.
Charts marked with a green 'LIVE' badge are fully supported by ChartGen AI | you can click on them to see a preview and then create your own with your data. Charts with a 'Coming Soon' label are part of our development roadmap and will be added in future updates. You can still learn about these chart types in the atlas.
Both show trends over time, but they serve different purposes. Use a Line Chart when you want to emphasize the rate of change and compare multiple series clearly. Use an Area Chart when you want to emphasize the cumulative magnitude or show part-to-whole relationships over time. Area charts work best with fewer data series to avoid visual clutter.
Use a Bar Chart when comparing values across categories, especially when you have many categories or need precise comparisons. Use a Pie Chart only when showing parts of a whole with 2-5 categories and when the proportions are meaningfully different. If your pie slices would be similar in size, a bar chart is usually more effective.
A Waterfall Chart (also called a bridge chart) shows how an initial value is affected by a series of positive and negative changes to reach a final value. It's commonly used in financial analysis to show how revenue becomes profit, explain budget variances, or break down the components of change between two time periods.
Use a Scatter Plot when you want to show the relationship between two continuous variables and identify individual data points, outliers, or clusters. Use a Heatmap when you have categorical data on both axes and want to show the intensity or frequency of combinations. Heatmaps are great for showing patterns across time periods or categories.
Spatial charts (Choropleth, Cartogram, Flow Map, etc.) are used when geographic location is a key dimension of your data. They help answer questions like 'Where are sales highest?', 'How do values vary by region?', or 'What are the movement patterns between locations?'. ChartGen is working on adding map-based visualizations in future updates.
We're always expanding ChartGen's capabilities based on user needs. You can share your chart type requests with us through the Ada.im platform. Popular requests are prioritized in our development roadmap. Currently, we're working on adding Donut, Treemap, Radar, and more statistical chart types.