Un vocabulario visual completo de 72 tipos de visualización de datos, organizados en 10 categorías según su propósito. Elige el tipo de gráfico adecuado para tu historia de datos - desde gráficos de barras y líneas hasta treemaps y diagramas sankey.
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Selecciona la mejor visualización de datos según lo que quieras comunicar. Relaciona tu tipo de datos y objetivo con una de estas 10 categorías de gráficos.
Visualiza tendencias, patrones y cambios temporales en tus datos. Ideal para seguir el progreso, identificar estacionalidad o pronosticar valores futuros.
Compara tamaños y cantidades entre categorías. Perfecto para mostrar diferencias relativas y hacer comparaciones de valores directas.
Muestra cómo los componentes individuales contribuyen a una imagen completa. Mejor para análisis de composición, desgloses porcentuales y datos jerárquicos.
Resalta las variaciones desde un punto de referencia como cero, promedio u objetivo. Útil para mostrar rendimiento positivo/negativo y análisis de sentimiento.
Descubre patrones y conexiones entre dos o más variables. Esencial para análisis estadístico, identificación de tendencias y pruebas de hipótesis.
Muestra elementos ordenados por valor para indicar posición relativa. Excelente para tablas de clasificación, listas de mejores/peores, análisis competitivo y rankings de rendimiento.
Comprende la frecuencia y dispersión de los puntos de datos. Crítico para análisis estadístico, identificación de valores atípicos y comprensión de la forma de los datos.
Rastrea movimientos, transferencias y conexiones entre entidades. Perfecto para mostrar procesos, migraciones, recorridos de usuario y asignación de recursos.
Muestra datos con contexto geográfico en mapas. Esencial para análisis regional, insights basados en ubicación y comprensión de patrones de distribución geográfica.
Algunas historias de datos requieren tipos de gráficos únicos que no encajan en categorías tradicionales. Estos gráficos especializados sirven para necesidades analíticas y organizativas específicas.
Based on the FT Visual Vocabulary • 72 chart types across 10 categories
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.