What is the best way to display data changes over time in charts?

Best Ways to Display Data Changes Over Time

1. Table Matrix:

• The table matrix is a powerhouse for storytelling. It’s versatile and, with the right conditional formatting and granular drill-down, you can reveal detailed insights. Add in a percentage change KPI with conditional formatting, and you’ve got a complete view without needing any other chart. It’s like reading the data’s mind!

2. Cumulative Running Total Line:

• A cumulative running total line chart is great for showing progress over time, especially when you compare it against another metric. For example, tracking this year’s total versus the previous year’s total—the gap between the lines tells a compelling story of growth or decline.

3. Column Chart:

• The classic column chart is great for spotting anomalies and identifying highs and lows at a glance. Whether you're tracking monthly sales or daily transactions, columns help make trends, outliers, and patterns easy to spot.

The term "best" can be subjective, as it depends on the context, audience, and the specific goals of your data visualization. However, there are some well-established principles that can guide you in choosing the most effective way to display changes in data over time.

1. Understanding the Purpose and Audience:
   1. Purpose: Are you trying to show a trend, make a comparison, or highlight specific data points?
   2. Audience: Consider who will be viewing this data. Are they data-savvy, or do they need a simplified representation?
2. Types of Charts:
   1. Line Charts: Ideal for showing trends over time. They are particularly effective for displaying cumulative data or continuous data points. The gradual slope of the line can help viewers easily grasp upward or downward trends.
   2. Bar Charts: Suitable for comparative analysis. If you need to compare different categories or groups over time, bar charts (especially grouped or stacked) are your go-to. They allow for a clear comparison at each time interval.
   3. Expanded Bar Charts: Useful when you need to show the distribution of different components within each category over time. This helps in understanding the contribution of each part to the whole.
3. Considerations for Data Density:
   1. Clarity: When dealing with large datasets or longer time frames, it’s crucial to avoid clutter. Consider using fewer data points or summarizing data (e.g., showing monthly averages instead of daily data) to maintain clarity.
   2. Interactive Elements: For dense datasets, interactive charts can be very useful. They allow users to zoom in and out, hover over data points for more details, and focus on specific segments of the data over time.

4. . Balancing Detail with Simplicity:

   Focus on Key Insights: Avoid overwhelming your audience with too much detail. Highlight the most important trends or changes, and use additional tools (like annotations or tooltips) to provide further detail only when necessary.

5. Best Practices for Effective Time-Based Charts:

   Consistent Time Intervals: Use consistent time intervals (e.g., days, months, years) to avoid misleading trends.

   Color and Labeling: Use color thoughtfully to differentiate data without causing confusion. Labels should be clear, concise, and directly tied to the data they represent.

Bottom line:

Ultimately, the "best" way to display data changes over time is the one that most effectively communicates the insights you want to convey, while considering the needs and expectations of your audience. Start with the goal in mind, choose the appropriate chart type, and always prioritize clarity and simplicity.