How to build a simple Bitcoin and Ethereum dashboard in Google Data Studio

How to build a simple Bitcoin and Ethereum dashboard in Google Data Studio

In this post I'll show you how to make a simple dashboard that lets you monitor the price of two of the most popular Cryptocurrencies; Bitcoin and Ethereum.

All you need is;

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How to combine string fields in Google Data Studio

How to combine string fields in Google Data Studio

Have you ever needed to combine string fields in Google Data Studio? I tried to do it the other day and it was more difficult than expected.

In this post I'll show a method that solves how to combine different string fields into one field. This method is from Harry Bryars whom you can follow on Twitter or Medium. He was kind enough to show me this method!

Looking at the hypothetical Data Set

So in this hypothetical data set we have a list of tourist names in Column A and then the country they visited in each year, listed as five seperate columns. You'll notice that many cells are blank as some tourists did not travel to countries in some of the years. or in some cases no countries.

The First attempt at Combining the strings

So the first attempt at combining the strings seems like an obvious solution.

Use the CONCAT function to combine all the strings together, as shown below.

Here is the actual CONACT formula if you want to try it yourself.

CONCAT(Country 2015,", ", Country 2016,", ", Country 2017,", ", Country 2018,", ", Country 2019)

And below is what the formula displays in our Data Studio report. You'll notice that if all the fields (columns) contain a country then the formula works as intended and combines the countries into a list.

However if one of the columns has no county listed and is null then the formula doesn't work.

Second attempt at combining the strings

This is the second version for the formula from Harry Bryars that worked!

So it uses multiple CASE statements to insert a "_" when the column value is null, and otherwise lists the country.

Below is how the formula show look.

Here is the actual formula if you'd like to try replicate this with your own data source.

CONCAT
(CASE WHEN Country 2015 IS NULL THEN "_" ELSE Country 2015 END,", ", 
CASE WHEN Country 2016 IS NULL THEN "_" ELSE Country 2016 END,", ", 
CASE WHEN Country 2017 IS NULL THEN "_" ELSE Country 2017 END,", ", 
CASE WHEN Country 2018 IS NULL THEN "_" ELSE Country 2018 END,", ",
CASE WHEN Country 2019 IS NULL THEN "_" ELSE Country 2019 END,", "
)

Below in the final column you can see that we have the formula working close to how we would like it to.

Below is the actual Google Data Studio report if you'd like to take a look.



My Other Blog posts

If you enjoyed this post then you might like my other blog posts.


How to map Growth in Google Analytics sessions by Country in Data Studio

Google Data Studio has always had the ability to add in a comparison column to tables, but not to map out a change in values on a map. Ideally I would want to be able to see which countries have seen the highest rates of growth over a period of time. This is a method that worked for me and hopefully it will be useful for you too!

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How to use DATE_DIFF in Google Data Studio to work out Sessions per Day

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How to combine data from two BigQuery public datasets using SQL

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How to change Google Map metrics using a Parameter in Data Studio

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How to switch Google Map dimensions using a Parameter in Data Studio

How to switch Google Map dimensions using a Parameter in Data Studio

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Two methods for Mapping Google Analytics City data in Google Data Studio

Two methods for Mapping Google Analytics City data in Google Data Studio

In this post I'll just show two methods for mapping Google Analytics city data in Google Data Studio.

Recently Data Studio added Filled Area Google Maps which allow you to view city data by area instead of bubbles.

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