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You’ll agree when we say storing and organizing data in tables is convenient. You can easily infer quick insights from tabular data in Google Sheets. But you can only go far with tables in data analysis.
Why?
Picture this: you have a gigantic data set that occupies tens of thousands of rows and columns in Google Sheets. How can you extract reliable insights from such huge tables efficiently?
Assuming persistence is one of your values, how long can it take you to extract meaningful insights? You guessed right. It could take you hours, if not days.
This is where graphs come in.
Graphs can help you distill critical insights from noise and outliers. Remember, a huge chunk of any data is always noise. Essentially, you stand to save a ton of time and effort when dealing with bulky and complex data.
In this blog, you’ll learn how to make a graph from a table in Google Sheets using easy-to-follow and straightforward steps.
We’ve rounded up tips and examples to help you save time for generating a graph from tables.
Keep reading if you intend to elevate your Google Sheets game to the elite level.
Before we delve into the how-to guide, let’s go through why we need to create graphs from tables.
Thanks to data visualization designs, you can interpret vast quantities of data clearly and cohesively. Besides, you can easily extract insights, draw conclusions, and see perspectives.
Using different business charts and graphs, you can keep track of crucial and strategic metrics of your business or workplace. Furthermore, you can easily spot anomalies, such as outliers, which can easily misinform your decisions.
You can use graphs to uncover risks and opportunities surrounding your business or workplace.
Graphs can help you spot emerging trends and respond in real time.
Patterns and trends make more sense when graphically represented.
Certain relationships in your data may be apparent, primarily if you use tables. But to uncover hidden insights, you need visual representations, which is beyond the capacity of tables.
Tables, especially long ones, are not recommended if you want your data story to be compelling. Data visualization experts use graphs, charts, and maps to help their target audiences understand key takeaways without struggle.
Let’s agree on this: You’ll be using visual diagrams, such as graphs from tables, to create compelling data stories for your audience (and readers).
Take a look at the tabular data below.
How to make a graph from a table like the one below?
| Year | Topic | Positive | Negative |
| 2019 | Quality of food | 11 | 12 |
| 2019 | Ease of ordering | 29 | 50 |
| 2019 | Services | 20 | 33 |
| 2019 | Parking | 2 | 4 |
| 2019 | Cleanness | 55 | 12 |
| 2019 | Ease of reading the menu | 12 | 7 |
| 2019 | wait time to be seated | 16 | 11 |
| 2019 | Seating space in the waiting area | 8 | 8 |
| 2019 | menu and drink choices | 4 | 3 |
| 2019 | Attitude of Waiter | 3 | 5 |
| 2019 | Payment method | 12 | 15 |
| 2020 | Quality of food | 15 | 12 |
| 2020 | Ease of ordering | 51 | 1 |
| 2020 | Services | 28 | 12 |
| 2020 | Parking | 4 | 2 |
| 2020 | Cleanness | 45 | 11 |
| 2020 | Ease of reading the menu | 12 | 8 |
| 2020 | wait time to be seated | 16 | 18 |
| 2020 | Seating space in the waiting area | 13 | 18 |
| 2020 | menu and drink choices | 4 | 1 |
| 2020 | Attitude of Waiter | 3 | 8 |
| 2020 | Payment method | 17 | 16 |
| 2021 | Quality of food | 18 | 12 |
| 2021 | Ease of ordering | 59 | 20 |
| 2021 | Services | 30 | 10 |
| 2021 | Parking | 2 | 0 |
| 2021 | Cleanness | 55 | 7 |
| 2021 | Ease of reading the menu | 18 | 10 |
| 2021 | wait time to be seated | 22 | 14 |
| 2021 | Seating space in the waiting area | 13 | 16 |
| 2021 | menu and drink choices | 4 | 1 |
| 2021 | Attitude of Waiter | 2 | 4 |
| 2021 | Payment method | 13 | 14 |
Let’s extract insights from the table above using a graph.
The above data visualization design (comparison bar chart) makes things a little easier. You can easily infer the key issues customers raised during the survey.
In the last three financial years (2019-21), the two most significant issues that customers have raised with regard to the restaurant brand are:
There’s a strong case for using graphs in place of tables. One of the strengths of data visualization is that you can save a ton of time, especially during the analysis phase.
Different types of charts and graphs make it easy for you to extract hidden insights into patterns, trends, and outliers within your data. It’s a matter of interpreting a visual representation rather than sifting through individual data points.
You’ll agree when we say Google Sheets is one of the best data visualization tools around. You can use this tool to create tables, such as Pivot tables. More so, you can use Google Sheets to visualize your data.
Essentially, you can generate a graph from tables using Google Sheets.
However, this spreadsheet tool comes with pretty basic graphs that require a lot of tweaks and edits to align with your needs. And this means you stand to spend a lot of time visualizing your data using Google Sheets.
To create a compelling data story, you need charts that are easy to interpret such as Sankey Diagram, Pareto Chart, Comparison Charts, Control Charts, and Funnel Charts. And this means you need to think beyond Google Sheets.
Here’s the kicker: we’re not advising you to ditch Google Sheets for other pricey data visualization tools in the market. We would like to see you enjoying your freemium tool for free until Google decides otherwise.
For this, we recommend you supercharge your Google Sheets with third-party applications (add-ons). It’s no doubt there’re thousands of add-ons for Google Sheets.
The add-in we’ve tested and has provided remarkable results is ChartExpo.
As we said, how to turn a table into a graph on google sheets does not have to be stressful or even time-intensive.
ChartExpo is a trusted tool that thousands of professionals worldwide use to create insightful and easy-to-understand graphs from tables.
Besides, it comes as an add-on you can easily install in your Google Sheets to get the most from your data
ChartExpo comes loaded with many advanced data visualization designs such as Sankey Diagram, Pareto Chart, Comparison Charts, Control Chart, and Funnel Charts to ensure you never struggle to generate a graph from the table.
Follow the example below to discover more.
We’ll use a Progress Chart in Google Sheets to visualize the table below.
| Mobile Brand | Previous Sales | Current Sales |
| Samsung | 10 | 90 |
| Apple | 10 | 75 |
| Huawei | 20 | 80 |
| Nokia | 50 | 50 |
| Sony | 70 | 30 |
| LG | 30 | 70 |
| HTC | 67 | 33 |
| Motorola | 54 | 56 |
| Lenovo | 40 | 60 |
Tables are best suited for storing and organizing raw data. Anything beyond the aforementioned, you should opt for graphs.
Yes, you read that right.
Data in tables can be displayed as text, using words and numbers. Besides, tables make it easy to compare pairs of related values (e.g., quarterly sales in a given financial year).
Remember, you cannot use tables exclusively to display quantitative information. Whenever you have more than one set of values with a direct relationship, you may use a table to organize the data.
For example, some professionals often use tables to display meeting agendas with particular times, topics, locations, and speakers.
So when should you use graphs instead of tables?
When the data grows beyond the reasonable scope, you need to explore data visualization to display insights easily.
Graphs are essentially a visual display of data along two axes (x and y-axes). There’s scientific reasoning behind why data stories with visual designs are more compelling than those without one. Did you know our brains can interpret visual content 60,000 times faster than words and numbers?
Use interactive data visualization designs in your data stories to arouse the interest of the target audience. Graphs and charts can show insights into bulky data in a way that’s easy to process.
Data visualization is a quick, easy way to convey insights into raw data. You can use visual designs, such as bar charts, graphs, and maps, to achieve the following:
When debating table versus graph, do the following:
Data visualization entails translating raw data into a visual context, such as a map or graph, to make data easier for audiences to infer critical insights.
You can use visualization designs, such as Bar, Column, Pareto, Progress, and Donut Charts (among others) to make your data stories persuasive.
A good data visualization tool should have the following attributes:
Tables are convenient in storing and organizing raw data. However, when the complexity and size of data start growing: you need to explore other more innovative options, such as data visualization.
This is where graphs come in.
Well-constructed visualization designs can complement your data stories. You can use them to uncover hidden patterns, trends, and outliers in your data.
Freemium tools, such as Google Sheets, come with pretty basic data visualization designs, which require a lot of editing. And this means you stand to spend a lot of time.
We recommend our readers to use the ChartExpo add-on to supercharge their favorite spreadsheet app (Google Sheets).
Why?
ChartExpo comes pre-loaded with over 50 graphs that are easy to read and interpret. Besides, it has an ultra-friendly user interface (UI), which means you don’t need coding or programming skills to visualize your data.
Sign up today to save the time you can take to generate a graph from tables.
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