Definitive guide to data visualization charts: from theory to practice

Data visualization is not about making numbers look “pretty”. Its true purpose is to reduce the cognitive load of the person reading the report, allowing them to identify patterns, trends, anomalies, and relationships in a matter of seconds.

Choosing the wrong chart can ruin an excellent data analysis. If you use a line chart to compare discrete categories or a pie chart to show 15 different elements, you will be confusing your audience instead of providing value.

This comprehensive guide is a complete catalog of the most used and advanced types of charts in business analytics, data science, and research. Use it as an input and reference map every time you need to design a dashboard or report.

Table of Contents and Visualization Taxonomy

Charts are classified according to the analytical question they attempt to answer. Here are the 7 main families:

Comparison (Categories and Magnitudes): Who sells more? How do the groups differ?
Evolution and Time: How does the metric change over time? Is there seasonality?
Composition (Part of a Whole): How is the budget divided? What is our market share?
Distribution and Intervals: How are the data concentrated? Are there outliers?
Relationships, Flows, and Connectivity: Does the increase in X cause the increase in Y? How do users move?
Geospatial (Maps): Where are conversions physically concentrated?
Processes and Indicators (KPIs): How is performance against the goal? Where is the bottleneck?

1. Comparison Charts

Used to compare numerical values between different categories or discrete groups.

1.1. Simple Bar Chart (Horizontal or Vertical)

What is it?: Represents numerical values through the length of rectangular bars aligned on a common axis.
When to use it: To compare magnitudes between discrete categories and few variables.
- Vertical Bars (Columns): Ideal when category labels are short (e.g., years, months, countries with 3-letter names).
- Horizontal Bars: Mandatory when labels are long (e.g., marketing campaign names, product names, or acquisition channel types).
Applied example: Comparing the average cost per acquisition (CPA) across 4 traffic channels.
Best practices: The numerical axis must always start at zero (0) to avoid distorting physical proportions.

1.2. Grouped Bar Chart

What is it?: Shows multiple subcategories grouped within a main category on one of the axes.
When to use it: To compare data organized in two categorical levels simultaneously.
Applied example: Web traffic comparison (Mobile vs. Desktop) over the last 3 months.

1.3. Stacked Bar Chart

What is it?: Places subcategory segments on top of each other, summing the total height to show accumulated volume.
When to use it: When you want to compare the overall total of each category and see the internal contribution of each segment.
Applied example: Total monthly clothing sales divided by category (Clothing, Footwear).

1.4. Diverging Bar Chart

What is it?: Horizontal bars that extend in opposite directions from a central baseline.
When to use it: Excellent for opposing opinions or Likert-scale classifications (e.g., Good vs. Bad).
Applied example: Percentage of favorable (left/blue) and unfavorable (right/red) opinions in a survey.

1.5. Tornado or Bilateral Chart

What is it?: Shows growth and decline variations from a central zero baseline.
When to use it: To visualize magnitudes that reflect variations of positive and negative signs.
Applied example: Percentage employment growth in the software sector.

1.6. Radar or Spider Chart

What is it?: Two-dimensional chart with multiple quantitative radial axes starting from a common central point.
When to use it: To compare performance profiles across multiple attributes simultaneously.
Applied example: Technical skills of an analyst.

1.7. Slope Chart

What is it?: Shows lines connecting data points between exactly two points in time.
When to use it: To visualize the relative change and evolutionary direction of several elements.
Applied example: Traffic accident rate in two different years.

1.8. Dumbbell Plot (Cleveland Dot Plot)

What is it?: Represents two or more data points on the same line, connected by a segment, showing the distance or gap between them.
When to use it: Excellent for emphasizing the difference or “gap” between two categories or groups.
Applied example: Electrical infrastructure gap (blackouts) by manufacturing vs. retail sector.

1.9. Lollipop Chart

What is it?: A thin bar (line) capped with a circle at the end, representing the value of a discrete category.
When to use it: As a clean aesthetic alternative that reduces visual ink load on screen.
Applied example: GDP ratio by number of banks per country.

1.10. Threshold or Goal Line Chart

What is it?: Superimposes a fixed straight line (horizontal or vertical) corresponding to a regulatory limit or performance goal.
When to use it: To immediately contrast which categories exceed or fall short of a standard.
Applied example: Prison overcrowding rate and official capacity limit.

2. Trend, Time, and Evolution Charts

They allow understanding how metrics change over time.

2.1. Line Chart

What is it?: Connects individual data points along a continuous time axis using segments.
When to use it: The standard option for analyzing historical trends.
Applied example: Evolution of monthly registered users.

2.2. Area Chart

What is it?: Similar to a line chart, but with the space below filled with color.
When to use it: To emphasize the magnitude of total accumulated volume over time.
Applied example: Total volume of daily downloads.

2.3. Stacked Area Chart

What is it?: Multiple area series stacked vertically on top of each other.
When to use it: To observe the evolution of the accumulated total and its internal distribution simultaneously.
Applied example: Network traffic broken down by devices.

2.4. Candlestick Chart

What is it?: Shows four price metrics (Open, Close, High, Low) in a time interval.
When to use it: Exclusively used in financial market analysis and stock trading.
Applied example: Fluctuations in the value of a stock.

2.5. Calendar Heatmap

What is it?: A structured grid where each daily cell is colored according to its numerical value.
When to use it: To discover seasonal patterns based on specific days.
Applied example: Commits made by a development team.

2.6. Combo or Dual Axis Chart

What is it?: Unites two different types of charts (e.g., bars and lines) using two independent Y-axes.
When to use it: To analyze the correlation between two variables with completely different scales or units.
Applied example: Interest rate (%) and total volume invested.

3. Distribution and Interval Charts

They help understand the dispersion and concentration of data observations.

3.1. Histogram

What is it?: Groups continuous data into equal adjacent intervals (“bins”) and illustrates their frequency.
When to use it: To analyze the statistical distribution of a variable.
Applied example: Distribution of order values in an e-commerce.

3.2. Scatter Plot

What is it?: Places individual points on a Cartesian two-dimensional grid using the coordinates of two variables.
When to use it: To discover correlations or grouping patterns between two variables.
Applied example: Artificial Intelligence governance vs. scientific development.

3.3. Bubble Chart

What is it?: Extension of the scatter plot where each point has a size proportional to a third quantitative variable.
When to use it: To evaluate complex relationships of three continuous variables at once.
Applied example: Campaign budget, clicks, and conversions.

3.4. Box and Whisker Plot (Boxplot)

What is it?: Visual summary of five key descriptive statistics and outliers.
When to use it: To compactly compare dispersion across multiple groups.
Applied example: Server load times.

3.5. Violin Plot

What is it?: Combination of a boxplot with a smoothed density plot rotated to each side of the box.
When to use it: To simultaneously view the boxplot and the exact probability density of the distribution.
Applied example: Salary distribution in a tech company.

3.6. Quadrant Scatter Plot

What is it?: A scatter plot divided into four quadrants by two reference lines (mean values of X and Y axes).
When to use it: To segment data observations into four well-differentiated zones or analytical profiles.
Applied example: Labor participation by gender (Female vs Male).

4. Composition and Part of a Whole Charts

They show how parts contribute to forming a total consolidated metric.

4.1. Pie Chart and 4.2. Donut Chart

What is it?: Circle (or ring) divided into sectors proportional to the percentage they represent of the total.
When to use it: To compare simple static proportions (3 or 4 categories maximum).
Applied example: Proportion of mobile vs desktop traffic in visits.

4.3. Treemap

What is it?: Shows hierarchical data as nested rectangles proportional to their magnitude.
When to use it: To visualize 100% compositions across dozens of categories.
Applied example: Airline market share in air cargo.

4.4. Waffle Chart

What is it?: 10x10 grid where each colored cell represents 1%.
When to use it: A highly readable alternative to the pie chart.
Applied example: User retention rate of 72%.

4.5. 100% Stacked Bar Chart

What is it?: Columns of the same fixed size (100%) divided proportionally according to their segments.
When to use it: To compare relative internal proportions across multiple categories.
Applied example: Mobile market share Android vs. iOS by country.

4.6. Packed Bubble Chart

What is it?: Circles whose sizes represent quantitative magnitudes grouped compactly without axes.
When to use it: For quick and attractive comparison of proportions.
Applied example: Distribution of online capital and savings.

4.7. Voronoi Diagram (Voronoi Treemap)

What is it?: Hierarchical subdivision of a surface into irregular polygons where the area of each cell represents proportionally its part of the whole.
When to use it: For complex representations that are more organic and less rigid than the treemap.
Applied example: Breakdown of air cargo transport by operator.

5. Relationship, Flow, and Connectivity Charts

They visualize how data flows between nodes or the connectivity of systems.

5.1. Sankey Diagram

What is it?: Shows directed flows between nodes where the width of the flow lines is proportional to their volume.
When to use it: To map a journey, transition, or conversion from start to finish.
Applied example: User flow across pages of an e-commerce site.

5.2. Chord Diagram

What is it?: Circular structure where internal curved links demonstrate bidirectional exchange relationships.
When to use it: To study complex transition flows between multiple entities.
Applied example: Transition of visits between sections of a portal.

5.3. Matrix Heatmap

What is it?: Two-dimensional table where individual cell values are represented by color intensity.
When to use it: To analyze activity peaks or anomalies across large cross-volumes.
Applied example: Campaign CTR broken down by day and time.

6. Geospatial Charts (Data Maps)

Used when the data contains geographic information.

6.1. Choropleth Map

What is it?: Geographic map where political boundaries are colored using a chromatic scale.
When to use it: To show spatial variations at a country or region level.
Applied example: National unemployment rate by state.

6.2. Proportional Symbol Map

What is it?: Draws circles centered on geographic coordinates proportional to the data value.
When to use it: To compare direct absolute totals without being biased by the physical size of countries.
Applied example: Total volume of gross sales by commercial city.

6.3. Cartogram

What is it?: Map where the actual size of territories is intentionally distorted proportionally to a value.
When to use it: To de-emphasize physical area in favor of the absolute value.
Applied example: Countries of the world resized according to their population.

7. Process and KPI Charts

Focused on the daily monitoring of key operational and business metrics.

7.1. Funnel Chart

What is it?: Illustrates a linear series of sequential stages that progressively decrease in size.
When to use it: To immediately identify retention and drop-off rates.
Applied example: Customer conversion in the recruitment or sales process.

7.2. Gantt Chart

What is it?: Horizontal bars arranged on a timeline detailing tasks, deadlines, and milestones.
When to use it: Essential for project management and planning.
Applied example: Development plan for a website migration.

7.3. KPI Scorecards or Summary Cards

What is it?: Large key figures accompanied by a trend or relative variation indicator.
When to use it: In executive dashboards to facilitate quick decisions without inspecting details.
Applied example: Total accumulated sales for the month.

📋 5-Step Checklist for choosing your Chart

Before creating any visualization in your analytics tool (Looker Studio, Tableau, Power BI, or custom code), answer the following questions:

What is the key business question? (Do I want to compare categories, see a trend over time, or find the distribution of a variable?).
What type of data do I have? (Categorical variables like “campaign”, continuous numerical like “price”, temporal like “days”, or geospatial?).
How many dimensions and metrics do I want to show in a single view? (If there are many, you likely need to divide the data into multiple coordinated charts instead of cluttering one).
What is the technical level of my audience? (For non-technical clients, use intuitive charts like bars, lines, or KPIs. Save boxplots or violin plots for technical or scientific teams).
Does the chart reduce or increase the mental effort to understand the data? (If it requires complex verbal explanations from you to understand what the axis or color means, then the chart has failed and you need to simplify).