시간이 지남에 따라 값이 어떻게 변하나요?
데이터의 트렌드, 패턴 및 시간적 변화를 시각화하세요
Based on the FT Visual Vocabulary • 72 chart types across 10 categories
보여주고 싶은 내용에 따라 최적의 데이터 시각화를 선택하세요
데이터의 트렌드, 패턴 및 시간적 변화를 시각화하세요
카테고리별 크기와 수량을 비교하세요. 순위 지정에 적합합니다
개별 구성 요소가 전체에 어떻게 기여하는지 보여주세요
0, 평균, 목표와 같은 기준점에서의 변동을 강조하세요
여러 데이터 세트 간의 연결과 관계를 발견하세요
크기나 값에 따라 항목을 순위별로 정렬하세요
데이터의 분산, 범위 및 분포 패턴을 이해하세요
요소 또는 시스템 간의 움직임과 연결을 추적하세요
지리적 또는 공간적 맥락에서 데이터를 시각화하세요
일부 데이터 스토리에는 고유한 차트 유형이 필요합니다
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.