In today’s data-driven landscape, tools that simplify the journey from raw data to actionable insights are highly sought after. Looker Studio, a versatile data exploration and visualization platform, is at the forefront of this evolution. In this blog, we’ll delve into how Looker Studio can be your go-to solution for importing, analyzing, and visualizing data. Specifically, we’ll focus on creating a pivot table that showcases the top 10 average biomass values for each year, while also integrating a fixed-size list control for selecting the year.

Step 1: Importing Data into Google Sheets

Our journey begins with data. For this example, we’re utilizing a USDA dataset on biomass. Start by importing the dataset into a Google Sheet using the IMPORTDATA function. Open a new Google Sheet and input the formula in a cell:

=IMPORTDATA("https://data.nal.usda.gov/system/files/biomass.csv")

The formula fetches the dataset from the URL and fills the sheet with the imported data.

Step 2: Getting Acquainted with Looker Studio

Before we dive into pivot tables and controls, familiarize yourself with Looker Studio’s features. This platform for data exploration connects seamlessly to various data sources, including databases, data warehouses, and Google Sheets.

Step 3: Establishing the Foundation in Looker Studio

Ensure you have Looker Studio access and an active account. Follow these steps to set the stage for your analysis:

  1. Connect to Google Sheets: Start a new project in Looker Studio and select Google Sheets as the data source. Grant the necessary permissions to allow Looker Studio access to your Google Sheets data.

  2. Exploring the Dataset: With the connection in place, navigate the Google Sheets dataset using Looker Studio’s user-friendly data exploration tools. A list of available tables and sheets within your Google Sheet will be presented.

Step 4: Crafting a Pivot Table with Fixed-Size List Control

Let’s dive into the creation of a pivot table that spotlights the top 10 average biomass values for each year, while incorporating a fixed-size list control to choose the year:

  1. Data Source Selection: Choose the relevant sheet or table from your Google Sheets document that holds the data for analysis.

  2. Drag and Drop: Utilize Looker Studio’s drag-and-drop interface to place fields strategically within your pivot table. Put the “ID” field in the “Rows” section and the “Year” field in the “Columns” section.

  3. Averaging Biomass: In the “Values” section, apply the “Average” aggregation to the “Biomass” field. This step calculates the average biomass value for each combination of year and ID.

  4. Sorting and Limiting: Arrange the “Average Biomass” column within the “Values” section in descending order. Specify a limit of 10 to focus the pivot table on the top 10 average biomass values.

  5. Integrating Fixed-Size List Control: Enhance your analysis by including a fixed-size list control for selecting the year. This control enables users to interactively choose a specific year to view in the pivot table.

  6. Visualization and Insight: With the pivot table completed, you’ve unlocked valuable insights. Elevate your analysis by converting this data into visualizations like charts and graphs to amplify the clarity and impact of your discoveries.

In Conclusion, Looker Studio’s ability to import, explore, and interpret data from Google Sheets and beyond is unmatched. Armed with its intuitive interface and robust toolkit, you can seamlessly construct pivot tables that illuminate key trends and patterns. Whether you’re a data aficionado, strategic thinker, or analytical professional, Looker Studio empowers you with the tools to uncover insights that steer your decisions toward success.