Line
A Line chart can be used to visualise data in the Data Studio. Read more about this chart type below.
Line charts are perfect for following and visualising trends in data. For example, the total deposit amount per month.
How to use it
We recommend the following 2 variants when creating a line chart:
A: Maximum 1-3 Measures and 1 Time Dimension
Also, a regular Dimension may be used instead of a Time Dimension, however, this would not be commonly used. Instead, a bar chart would more commonly be a better choice to visualise it.
More Measures may be added, it is however not recommended for the simple fact: when there are too many Measures/lines (the Measures will be visualised as lines) it will be harder to visualise and understand what you're looking at. This would result in a chart that is hard to read and draw conclusions from, which in turn fights the purpose of looking at data/trends in the first place.
B: 1 Measure, 1 Time Dimension, and 1 regular Dimension
Let's have a look at examples for both of the above variants in the below examples.
Examples
Example A1:
Line chart with 1 Measure and 1 Dimension
Line chart with 1 Measure and 1 Dimension
In the above line chart, we are following the trend for deposit amounts on a monthly basis.
The Measure (the deposit amount trend) is represented by the pink line, with the value on the y-axis (you can also hover over the dots for more detailed information) and the Dimension (the timeline by month) can be found on the X-axis.
To get this visualisation we have added 1 Measure, [Deposit Amount], and 1 Dimension [Date] grouped by month with data collected from all time.
Example A2:
Line chart with 2 Measures and 1 Dimension
Line chart with 2 Measures and 1 Dimension
In the above line chart, we are following the trend for deposit and withdrawal amounts on a monthly basis.
The Measures (the deposit and withdrawal amount trends) are represented by the pink and blue line, with the value on the y-axis (you can also hover over the dots for more detailed information) and the Dimension (the timeline by month) can be found on the X-axis.
To get this visualisation we have added 2 Measures, [Deposit Amount] and [Withdrawal Amount], and 1 Dimension [Date] grouped by month with data collected from all time.
Example B1:
In the above line chart, we are following the trend for active players, split by country, on a monthly basis.
Here the Measure is now combined with the regular Dimension [Country] and together they're represented by all the lines found in the chart - each line represented by a different country.
You can find the value for the Measure on the y-axis (you can also hover over the dots for more detailed information). The time Dimension (split by month) can be found on the X-axis.
To get this visualisation, we have 1 Measure [Actives] and 2 Dimensions [Country] and the Time Dimension [Date] grouped by month with data collected from all time.
We also had to use the 'Pivot' functionality in order to display the countries as individual lines. We did this by moving the [Country] Dimension from the x-axis to the y-axis:
🧠 Let's reflect on the chart from the above example:
- There are too many lines to be able to focus and make sense out of the chart.
- The value ranges are too different, for each country/line which means we're not seeing any detailed trends.
- Many values are very low to none, which means they're not adding much or any value at all.
Conclusion:
The line chart should be cleaned up to be more relevant and clearer.
✨ Tip:
If you have a Dimension with many values, we recommend that you filter the important ones.
💡 Hint:
If you quickly want to clear up a chart, in order to focus on what's important, you can easily remove lines by crossing out the respective measure/dimension listed beneath the chart.
See below image
Clear up the chart by removing lines
Clear up the chart by removing lines
🙋 Please note that crossing out values, like above, won't store the setting and save it for a Widget. If you want to only include specific countries in your chart, at all times, you need to add filters. We'll show how to do just that in the next example.
Example B2:
We're adding to the previous example.
In the above line chart, we have kept the exact same Measures and Dimensions. What we've done, in addition, is to add a filter to our Measure. we are following the trend for active players, split by country, on a monthly basis.
Here the Measure is now combined with the regular Dimension [Country] and together they're represented by the pink, blue, and yellow lines - each line represented by a different country.
You can find the value for the measure on the y-axis (you can also hover over the dots for more detailed information). The Time Dimension (split by month) can be found on the X-axis.
To get this visualisation, we have 1 Measure [Actives] and 2 Dimensions [Country] and the Time Dimension [Date] grouped by month with data collected from all time.