Bar

'Bar' is a Chart Type that can be used to visualise data in the Data Studio. Read more about this Chart Type below.

Bar charts are great for following and visualising trends in data. Also, for comparing different values that have a similar value range. For example, the total deposit amount in comparison to total withdrawal amount per month.

How to use it

When it comes to bar charts it's always a safe bet to use 1 Measure and 1 Dimension. You could also use 2 or more Measures in some situations, even if it's recommended to keep Measures to a minimum.

🙋 Note: If you want 2 Measures (or more) make sure that the value ranges, of these Measures, are close enough for the value range on the y-axis to fit both Measures/bars. Otherwise, you could end up with one of the Measures/bars having a good fit, whilst the other would be too small and hard to tell what value it represents.

Examples

Example 1a:

In the above bar chart, we can see the Measure [Deposit Amount] being represented by the pink bars. The height of the bars are corresponding to the numbers/value on the y-axis. The Dimension [Country] is represented in the x-axis.

In the chart, we are comparing the total deposit amount for each country. Each bar represents the total deposit amount for each county found on the x-axis.

🧠 Let's reflect on the above example:

• The values differ a lot from country to country.

• The biggest value is way higher than the rest.

• We have a lot of very low values. Keeping in mind what has been mentioned in the above points. We can draw the following conclusions:

• The value range on the y-axis is not ideal for the majority of our Measures/bars. This leads to the main conclusion, that a bar chart with these Measures/values in mind isn't the most ideal. As we can't easily see the value for each bar and how they compare.

Example 1b:

Continuing with the above example, with a focus on the reflection. Let's adjust this bar chart, to make it better, by adding some filters.

Instead of looking at a bar chart with all countries, we've now decided to focus on 3 core markets.

In the above bar chart, we've added a filter with 3 values: SE, NO, and FI.

🧠 Now, let's reflect on the above example:

We can now clearly see that the y-axis value range is much more suited to our bars.

Conclusion:

It's worth asking yourself the following when creating a bar chart:

Are all the Measures/values comparable and is it necessary to keep all values?

If the answer is no, then think about splitting up some Measures into multiple charts and/or using filters.

Example 2:

We're continuing to add to the previous example.

With reference to the previous example, we've now added an additional Measure [Withdrawal Amount].

In the above chart, we can now see 2 bars for each country. The pink bar represents [Deposit Amount] and the blue bar [Withdrawal Amount].

So, from the above bar chart, we're still getting the comparison between each country. In addition, we're now also getting the comparison between the total deposit amount and total withdrawal amount for each of the 3 countries.

Example 3:

For our final example, let's continue with the comparison between the deposit amount and withdrawal amount, like in the previous example. But instead, we want to focus on 1 single market as well as add a Time Dimension.

In the above bar chart, we are now focusing on only the GB market (United Kingdom). We can see the comparison between the total deposit amount and total withdrawal amount for each year: 2016, 2017, 2018, 2019, and 2020.