How to Make a Column Chart in Looker

Creating a column chart is one of the most fundamental skills in data visualization, and Looker (now Looker Studio) provides a powerful set of tools to do just that. If you need to compare values across different categories - like monthly sales, campaign performance, or traffic by source - the column chart is your go-to visualization. This guide will walk you through every step of building, customizing, and sharing a column chart in Looker.

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What is a Column Chart and When Should You Use One?

A column chart uses vertical bars to represent different categories of data, with the height of each bar being proportional to the value it represents. It's a simple, intuitive way to display comparisons. While they seem basic, their clarity is their strength. You're not trying to be fancy, you're trying to communicate an insight quickly.

Use a column chart when you want to:

• Compare values across categories: This is the main purpose. For example, comparing the revenue generated by different product lines in a specific quarter.
• Show change over time: When you have a limited number of time periods (like months in a year or days in a week), a column chart can effectively show trends. For example, visualizing monthly website users over the last six months.
• Display rankings: Ordering the columns from highest to lowest helps you instantly see rankings, such as top-performing sales reps by deals closed.

Avoid using a column chart if you have too many categories, as this can make the chart cluttered and hard to read. In those cases, a bar chart (horizontal bars) might work better, giving you more space for category labels.

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Getting Started: Your Data in the Looker Explore

Before you can visualize anything, you need to pull the right data. In Looker, this process starts in the "Explore" section, which is a user-friendly interface for querying your database without writing any SQL.

Think of an Explore as a curated dataset designed for a specific purpose, like "Website Analytics" or "Sales Performance." Your data team sets these up for you.

1. Select Your Dimensions and Measures

Once you are in an Explore, you'll see a list of fields on the left, organized into two key types:

• Dimensions: These are the descriptive, categorical fields. They're the things you want to group your data by. Common dimensions include Date, Traffic Source, Product Category, Campaign Name, or Sales Rep Name. Dimensions are typically shown in blue.
• Measures: These are the quantitative, numerical fields you want to calculate or aggregate. Common measures include Total Sales, Session Count, Conversion Rate, or Number of Users. Measures are typically shown in orange.

To build a basic column chart, you need at least one dimension and one measure. For instance, to see sales by region, you would select Region (dimension) and Total Sales (measure).

2. Filter Your Data

Your database likely contains years of information, so you almost always need to apply filters to focus on the period or segment you care about. Use the "Filters" section at the top to narrow your results. For example, you might filter for "Date is in the last 90 days" and "Country is United States."

3. Run the Query

Once you've selected your fields and filters, click the Run button. Looker will generate a data table with the results of your query at the bottom of the page. This is the raw data your column chart will be based on.

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Step-by-Step Guide to Creating Your Column Chart

With your data table ready, it’s time to create the visualization. Looker automatically suggests a chart type, but you can easily select and customize the one you want.

Step 1: Open the Visualization Pane

Above your data table, you'll find the "Visualization" pane. Click on it to expand the options. This is your command center for all things charting.

Step 2: Select the Column Chart Type

Click on the icon with several vertical bars - this is the "Column" chart option. As soon as you select it, Looker will instantly transform your data table into a preliminary column chart.

Step 3: Customize Your Chart with the Settings Tabs

A basic chart is good, but a great chart is clear, labeled, and easy to interpret. To fine-tune your visual, click the "Edit" button in the top right of the Visualization pane. This unlocks several customization tabs:

Plot Tab

This tab controls the overall structure and appearance of your chart.

• Series Positioning: Here you can choose how to display your columns. "Grouped" is the default setting, placing bars side-by-side. "Stacked" places values on top of each other in a single bar, which is useful for showing part-to-whole relationships. "Stacked Percentage" normalizes each stacked bar to 100%, showing the proportional contribution of each value.
• Grid Layout: If you have pivoted your data (for example, moved a second dimension to columns instead of rows), you can use this to customize how your visualization handles multiple series.

Series Tab

This tab lets you customize each data series (the different columns) independently.

• Colors: Assign specific colors to each series to match brand guidelines or make your chart more readable.
• Labels: Display the values for different levels of each series, and configure where to display them. For example, you can have one series plot as a column and another as a line.

Values Tab

This tab impacts how the numeric values on your chart are presented.

• Data Labels: Toggle the display of the number above each column. This is extremely useful for making your charts easier to understand at a glance.
• Value Colors: Change the color of the numbers to help them stand out or adhere to your theme.
• Value Format: Set the formatting of your numbers, whether currency, percentage, plain number, etc.

Axes Tab

This tab controls the appearance of your horizontal (or categorical) axis.

• Labels: Add a clear label to explain what your categories represent.
• Type: Choose between different label types, including plain (text), numeric, date, and time.
• Grid Lines: Show or hide grid lines to enhance the readability of your chart.

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Final Step: Saving and Sharing Your Chart

Once you're happy with your final chart, Looker allows you to save it to dashboards or share it with your team. Click "Save" in the top right of the settings to add it to any existing dashboard or create a new one. You can also send it directly to other team members.

Advanced Tips for More Effective Column Charts

Once you've mastered the basics, there are advanced features in Looker you can use to take your visuals to the next level:

• Conditional Formatting: Use a single measure to compare different metrics side-by-side. This feature allows you to highlight areas of interest, making your chart visually informative.
• Custom Calculations: Easily add a calculated measure directly in Looker without needing to modify your database schema.

Creating a column chart in Looker is a straightforward process that allows you to compare data visually and easily identify trends. By customizing your chart using the visualization settings, you can turn a raw table into a clear, actionable insight. With practice, the potential of Looker's series and visualization tools becomes apparent, aiding in strategic decision making.

Experience the power of data-driven insights with Looker and grow your analytical prowess to make informed business decisions.

For more tips on using Looker, check out Graphed, where you can access a variety of resources to enhance your capabilities.