How Many Charts Are There in Tableau?

One of the first questions aspiring analysts ask is, "How many different charts can you make in Tableau?" While there's a simple answer, it misses the entire point of what makes Tableau such a powerful data visualization tool. This article will cover the 24 built-in chart types in Tableau’s “Show Me” panel and, more importantly, explain how you can build a nearly infinite variety of custom visuals to tell your data story.

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The Official Answer: Tableau's 24 "Show Me" Chart Types

When you first open Tableau and connect your data, you’re greeted with a blank canvas. To help you get started, Tableau includes a panel on the top right called "Show Me." This feature highlights chart suggestions based on the type of data fields (dimensions or measures) you’ve selected.

The "Show Me" panel is home to 24 distinct chart types, which serve as foundational templates for your analysis. These are your go-to visuals for most common B.I. reporting tasks. Think of them as the building blocks for your dashboards.

The 24 "Show Me" chart types are:

• Text Table (Crosstab): Best for displaying precise values in a simple table format. Ideal when you need to look up specific numbers rather than see trends.
• Heat Map: A table that uses color intensity to represent the magnitude of a value. Great for spotting concentration and outliers in large datasets.
• Highlight Table: A text table enhanced with color, making it easier to compare data across categories. Less intense than a heat map, but more visual than a plain text table.
• Symbol Map: Uses shapes or symbols to show data on a geographic map. The size or color of the symbol can represent a measure.
• Filled Map (Choropleth): Uses color shading on geographic areas (like countries, states, or zip codes) to represent data. Excellent for showing regional patterns.
• Pie Chart: Shows parts of a whole, where each slice represents a percentage. Best used with a very small number of categories (less than five).
• Horizontal Bar Chart: A classic chart for comparing values across different categories. Horizontal bars are especially good for long category labels.
• Stacked Bar Chart: Compares the total amount across categories while also showing the composition of each category.
• Side-by-Side Bar Chart: An excellent way to compare sub-categories within a main category.
• Treemap: Displays hierarchical data using nested rectangles. The size and color of the rectangles can be used to represent different measures, making it great for seeing part-to-whole relationships in a compact space.
• Circle View: Uses circles, where size and color represent measures, to show data relationships.
• Side-by-Side Circle View: A variation of the Circle View that allows for comparison across different categorical breakdowns.
• Line Chart (Continuous): The standard for showing trends over time.
• Line Chart (Discrete): A variation that shows time as distinct points rather than a continuous axis.
• Dual Line Chart: Combines two line charts on different scales, which is useful when comparing two measures with very different magnitudes (e.g., website clicks and revenue).
• Area Chart (Continuous): Similar to a line chart but with the area below the line filled in, emphasizing the volume or magnitude of change over time.
• Area Chart (Discrete): A version of the area chart that treats the time component as separate categories.
• Dual Combination Chart: Overlays two different chart types (like a bar chart and a line chart) sharing the same axis. Helpful for showing different types of measures together, like sales volume (bars) and profit margin (line).
• Scatter Plot: Shows the relationship between two continuous measures. Indispensable for correlation analysis and identifying outliers.
• Histogram: Visualizes the distribution of a single continuous variable. Helps you understand the frequency, central tendency, and spread of your data.
• Gantt Chart: Primarily used for project management to visualize project timelines, dependencies, and task duration.
• Bullet Graph: A variation of a bar chart that displays performance against a target. Fantastic for KPI dashboards.
• Packed Bubble Chart: Displays data in a cluster of circles, where size and color encode quantitative data. Useful for showing a large number of items in a limited space.
• Box-and-Whisker Plot: A standardized way to show the distribution of data based on a five-number summary (minimum, first quartile, median, third quartile, and maximum). A favorite among statisticians.

Thinking Beyond "Show Me": Why the Real Answer is Unlimited

Stopping at the "Show Me" panel is like only using the templates in PowerPoint. It gets the job done, but you miss out on the real creative power of the tool. The actual answer to "how many charts are in Tableau?" is effectively unlimited. Tableau is a visualization engine, not just a chart selector.

The core of Tableau's flexibility lies in the combination of the Marks Card and the Rows and Columns shelves.

• The Shelves: Dragging your data fields (dimensions and measures) to the Rows and Columns shelves tells Tableau how to structure the chart. A field on 'Columns' creates axes or headers across the top, while 'Rows' creates them down the side. This is what forms the fundamental structure of your visual.
• The Marks Card: This card controls the visual elements within that structure. You can drag fields here to control attributes like Color, Size, Text, Detail, and Tooltip for the "marks" (the points, bars, or shapes) on your chart. Creating a dual-axis chart or manipulating how marks are layered opens up a huge range of possibilities.

By learning to manipulate these elements creatively, you can move beyond the 24 presets and build almost any data visualization imaginable. Almost every advanced chart type is simply a clever combination of basic chart types, dual axes, and precise control over the Marks Card.

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Common Custom Charts You Can Build in Tableau

To prove that the real capabilities extend far beyond the "Show Me" list, here are a few popular and highly effective chart types that you can build yourself in Tableau with a little practice.

Waterfall Chart

A waterfall chart is perfect for showing how an initial value is affected by a series of intermediate positive and negative values. Think of it as telling the story of your finances. You can start with your revenue, then subtract the cost of goods sold, subtract operating expenses, add other income, and finally arrive at your net profit. Each step is clearly visualized, making it exceptionally useful for financial analysis and inventory tracking.

Sankey Diagram

Sankey diagrams are amazing for visualizing flow or relationships between nodes. The width of the connecting lines shows the magnitude of the flow. You could use a Sankey diagram to visualize a customer's journey through your website (from homepage to product page to checkout), analyze user clicks in a marketing campaign, or track energy flows in a supply chain.

Donut Chart

While pie charts get a lot of criticism from data visualization purists, their cousin, the donut chart, is often a more palatable alternative. It's essentially a pie chart with a hole in the middle. This small change makes it slightly less focused on comparing slice angles and more focused on the length of each arc, which humans can interpret more accurately. You can also use the empty space in the middle to display a headline number, like the total value.

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Sunburst Chart

A sunburst chart is a way to display hierarchical data through a series of concentric rings. The innermost ring is the root of the hierarchy, and each subsequent ring represents a deeper level. It functions like a radial treemap and is a visually striking way to show how different sub-categories contribute to a whole within a complex hierarchy.

Marimekko Chart

A Marimekko Chart (or Mekko Chart) is like a two-dimensional stacked bar chart. While a standard stacked bar has a constant width for all bars, a Marimekko chart varies the width of the bars as well. This allows you to encode two variables simultaneously: one through the bar height (like a normal bar chart) and a second through the bar width. It's an information-dense chart used to analyze categorical data across two different measures, like market share analysis by segment and region.

How to Choose the Right Chart in Tableau

With so many options, the key isn't to memorize every chart type. Instead, learn to ask the right questions about your data and your goal. A simple framework can help you narrow down the best visual for the job.

1. What question are you trying to answer?

The purpose of your chart should drive your choice. Data visualization expert Andrew Abela's chart chooser framework boils this down to four main goals:

• Comparison: How do different categories stack up against each other? Best charts: Bar chart, Bullet graph, Line chart.
• Relationship: Is there a correlation between two or more variables? Best charts: Scatter plot, Bubble chart.
• Distribution: How is my data spread out? Where are the outliers? Best charts: Histogram, Box-and-whisker plot, Scatter plot.
• Composition: How do individual parts make up a whole? This can be static or change over time. Best charts: Stacked bar chart, Treemap, Pie/Donut Chart, Waterfall chart.

2. What does your data look like?

The type of data you have will automatically rule certain charts out. Consider:

• Do you have a time variable? Line charts and area charts are your best friends.
• Are you working with categorical data (e.g., product names, countries) or continuous data (e.g., sales, temperature)? Scatters, histograms, and box plots need continuous data.
• Do you have geographic data? Symbol maps and filled maps are obvious choices.

3. Who is your audience?

A dashboard for a C-level executive should be very different from one for a data analyst. An executive likely needs high-level, at-a-glance visuals like bar charts and bullet graphs to see KPI performance quickly. An analyst, on the other hand, might need a dense scatter plot or box plot to perform a deeper investigation.

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The Tableau Learning Curve: From "Show Me" to Custom Visualizations

Reaching the point where you can build custom charts is incredibly rewarding, but it doesn't happen overnight. The learning curve for BI tools like Tableau and Power BI can be surprisingly steep. Moving beyond the "Show Me" panel involves learning concepts like calculated fields, level of detail (LOD) expressions, parameters, and table calculations.

While there are endless online courses and tutorials to guide you, becoming truly proficient takes hours of dedicated practice. Many teams spend years developing their internal reporting capabilities or rely on dedicated data analysts to translate their business questions into functional dashboards. The process is potent, but the time investment is significant.

Final Thoughts

While Tableau technically has 24 "out-of-the-box" chart types, its true potential is in your ability to combine foundational elements to create nearly anything you can imagine. The most effective data visualizers don't fixate on the number of available charts but instead focus on choosing or building the single best visualization to answer a specific business question clearly and accurately.

Mastering tools like Tableau takes a significant investment of time and energy, which is a luxury not every team has. We built Graphed to short-circuit this entire process. Instead of navigating menus and learning complex features, you simply connect your data sources - like Google Analytics, Shopify, and Salesforce - and ask for what you want in plain English. You can say, "Show me a line chart of my Shopify revenue by month for this year," and our AI data analyst builds a live, interactive dashboard for you in seconds, saving you the hundreds of hours it takes to become a BI expert.