Exploring YEAR Function in Looker Studio: A Detailed Guide to Extracting and Visualising Year Data

 Exploring YEAR Function in Looker Studio: A Detailed Guide to Extracting and Visualising Year Data

Google Data Studio FUNCTION: YEAR

With Google Data Studio, visualising, chaining and interacting with your data has never been easier. Among several immensely useful functions, the

YEAR
function is one that deserves more attention.

Introduction to the YEAR function

The

YEAR
function in Google Data Studio is an incredibly handy tool that allows you to extract the year from a given date. Whether this date is in the form of text, numbers, compatibility mode dates, or upgraded Date and Date & Time data types, the
YEAR
function has you covered.

How does the YEAR function work?

The

YEAR
function utilises the following syntax to retrieve years from dates:

1) Accessing the year from a Date value:

YEAR(date_expression)

2) Obtaining the year from compatibility mode Date values:

YEAR(X [,Input Format])

It’s important to recognise that the

X
is symbolic for a field or expression that evaluates to Text, Number, or compatibility mode Date, while the ‘Input Format’ dictates the format for X.

The

YEAR
function interacts with the given parameters and channels through a myriad of recognised input formats, such as 'BASIC', 'DEFAULT_DASH', 'DEFAULT_SLASH', 'RFC_1123', 'RFC_3339', among others, to deliver precise results.

Examples of the YEAR function in action

Let’s imagine our organisation's sales records for an example.

Assume our data has a column ‘Date_of_Sale’, formatted in the 'DEFAULT_DASH' style (%Y-%m-%d). If we want to determine the sales year, we would specifically utilise the

YEAR
function to draw out that information. The formula would look like this:

YEAR(Date_of_Sale)

This would give us the year of each sale in the form of '2018', '2019', '2020', and onwards.

Now, consider a scenario where our data is being stored in milliseconds since the epoch. Using the syntax mentioned previously, obtaining the sales year would appear as follows:

YEAR(sales_time, 'MILLIS')

This formula would return the same year data, despite the varying time storage methods, proving the versatility of the

YEAR
function.

Limitations of the YEAR function

While being extremely beneficial, the

YEAR
function is fundamentally constrained by the precision of the input data. If your date data is inaccurate or inconsistent, this can lead to unreliable results. It's highly recommended to ensure your date data is as precise and consistent as possible for maximum efficiency.

Furthermore, the

YEAR
function cannot process information that isn’t part of a valid year. This means, if the date input doesn't include a year, the function will be unable to provide the desired output.

Helpful tips for using the YEAR function

Make sure you are familiar with the syntax to get the most out of the

YEAR
function. Remember that while the function can interpret a wide range of date formats, it is crucial to specify the correct one in the formula.

Furthermore, be mindful of your organisation's data privacy regulations when using dates. Showing the complete date could inadvertently reveal sensitive information. Using the

YEAR
function could help anonymize the data while keeping the details you need.

In summary, the

YEAR
function is an amazingly straightforward and potent feature in Google Data Studio. Whether you need to streamline your report's visual clarity or efficiently manage your date data,
YEAR
is ready to assist.

More function to use with Looker Studio

FLOOR
:
Exploring the FLOOR Function in Looker Studio: A Comprehensive Guide on Rounding Down Numbers in Data Analysis
UPPER
:
Using the UPPER Function in Looker Studio for Text Modification and Data Presentation
SECOND
:
Mastering the SECOND Function in Looker Studio: Extraction, Usage, Examples, and Limitations
DATE_DIFF
:
Understanding and Utilizing DATE_DIFF Function in Looker Studio: Syntax, Examples, Limitations and Tips
ENDS_WITH 
:
Understanding the ENDS_WITH Function in Looker Studio: Syntax, Functionality, Examples, Limitations, and Usage Tips

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Florian Cabirol
CEO of Catchr
As a web development expert, I am actively enhancing and developing Catchr connectors to optimize the processing and analysis of your marketing data.