Storytelling with Charts Mini Guide Part 1 of 2
  • 17 Nov 2023
  • 5 Minutes to read
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Storytelling with Charts Mini Guide Part 1 of 2

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Article Summary

In the age of overwhelming data collection, curating the right chart or graph to represent your data is a crucial step in ensuring that the story you want to share to your audience is clear and impactful. In Part 1 of this mini guide series, we will explore a systematic approach to choosing the right chart to tell your data story effectively.

Understanding Your Data

Understanding your data is a great first step to figuring out what story you can convey. Here are some questions to consider:

  1. What is the nature of your data?
    • Is it quantitative (numbers) or qualitative (categories)?
    • Are there time-based data, categorical data, or a combination of both?
    • How many data points are you working with?
  2. What kind of dimensions are you dealing with?
    • Does your data contain two dimensions, three, or more?
    • Do these dimensions change over time or are they static?
    • Do any of the dimensions correlate to one another?
  3. Are there any extreme / outlier data points you're working with?
    • How many data points are there?
    • Will any outlier data points make it difficult to see in one place with the rest of the data?

By being curious about your data, you can learn about trends that are present in the data, do some rudimentary testing of hypotheses, and formulate the start of a story about what the data shows.

Clearly Define Your Intent

Once you have done an initial assessment of the data, the next step is to figure out what is the intent of any visualizations you want to create. Sometimes you want to show a new perspective to the data you've collected as part of a presentation or announcement. Other times, the data you're collecting will be used for anomaly detection when monitoring key metrics. By narrowing down the intent of the visualization, you can focus in how how the visualization can meet the intent of your story.

  1. What are your key insights or messages?
    • Are you comparing values, showing trends over time, or highlighting distribution?
    • Are there any relationships or correlations you want to illustrate?
    • What do you want your audience to learn or understand from the data?
  2. Is it more important to be precise or to be simple?
  3. What are the next steps after understanding the data?
    • What actions would you want your audience to take because of the insights you showed?
    • Are there additional questions that need to be answered from the story?

Consider Your Audience

Take the time to understand whom you’re building the dashboard for. Your audience may be executives or other data analysts, customers or vendors. These play a role in how you want to show the data. Tailoring your chart's complexity and content to match your users' knowledge and needs can help the audience quickly understand your message.

  • Are they familiar with the data collected?
  • Do they need quick overviews or in-depth analysis?
  • Will the visualization be too complex or overwhelming for a non-technical audience?

Picking the Right Chart

Preset's blog How to Choose the Right Data Chart Types already provides a good overview of the right chart types depending on the structure of the data collected. Picking the right chart is just as important as making sure that your data is shaped correctly to match the chart you want to show. This final step hones in on the message you want to convey, so it's important to choose a chart that highlights that message effectively.

At a high level, different chart types answer 4 major question:

QuestionChart Family
How do the values compare to each other or change over time?Bar charts, Time-series charts, Table charts
How do the values relate to each other?Scatter plot, Heat map
How is the data distributed?Histogram, Scatter plot
What is the composition of whole?Stacked charts, Pie charts, Area charts

Common Chart Types

Once you have a clear understanding of your data, you can explore different chart types to find the one that best suits your needs. In addition to making sure the chart is conveying your key insight effectively, you may also consider how you can make your chartvisually appealing and adheres to best practices for color, labeling, and layout.

Here are some common chart types and when to use them.

Chart TypeUse CaseExamplesData Shape
Table ChartsYou want to see aggregated values of different categories
  • Average volume of books sold by month
  • Top 10 regions for signups
Category:A column of categorical or time-series values
Value:A column of numerical values
Bar ChartsYou want to compare discrete categories or show the frequency of different items
  • Comparing sales performance by region
  • Displaying the number of customers in different age groups
X-axis: A column of numerical, categorical, or time-series values

Y-axis: A column of numerical values

optional: A column of categorical values for additional segmentation

Line/Area ChartsYou want to visualize trends or changes over time
  • Showing stock price fluctuations over a year
  • Demonstrating the growth of website traffic over months
X-axis: A column of numerical, categorical, or time-series values

Y-axis: A column of numerical values

optional: A column of categorical values for additional segmentation

Pie ChartsYou want to display the composition of a whole in relation to its parts
  • Representing the market share of different product categories
  • Showing the distribution of expenses in a budget
Slice: A column of categorical values
Composition: A column of numerical values
Scatter PlotsYou want to explore relationships or correlations between two variables
  • Analyzing the relationship between temperature and ice cream sales
  • Studying the correlation between study hours and exam scores
X-axis: A column of numerical, or time-series values

Y-axis: A column of numerical values

optional: A column of categorical values for additional segmentation

HistogramsYou want to visualize the distribution of a single variable
  • Displaying the distribution of ages in a survey
  • Showing the frequency of rainfall amounts in a region
X-axis: A column of categorical values

Y-axis: A column of numerical values

HeatmapsYou want to represent data in a matrix format, often used for showing correlations or patterns
  • Visualizing the performance of different products across various regions
  • Representing the correlation matrix of financial variables
X-axis: A column of numerical or categorical values

Y-axis: A column of numerical values or categorical values

optional: A column of numerical values

Sankey DiagramsYou want to visualize the intersection of values from one dimension to another
  • Understanding the correlation users based on their country and age
  • Predicting how effective one version of product is versus another
Source-axis: A column of categorical values
Target-axis: A column of numerical values or categorical values
Metric: A column of numerical values
Geospatial ChartsYou want to see data on a geographical map
  • Charting the crime rates of different neighborhoods
  • Plotting the travel patterns for flights
Location: A column of coordinates or location names
Metric: A column of numerical values

Additional Resources

Preset has published this terrific blog that highlights some of top charts with more details:


Selecting the right chart to tell your data story is a critical step in data visualization. By understanding your data and considering factors like audience, message, and data type, you can create charts and graphs that effectively convey your insights and captivate your audience. Remember that data visualization is as much art as it is science, and practice and experimentation will help you refine your skills over time.

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