You’ll agree when we say Excel is a powerful tool for visualizing data.
And this is because it comes with a familiar user interface (UI). In other words, it has been there for decades. Besides, it has proven time and again to be amazingly reliable in storing and visualizing data.
Some of the best charts in Excel for data storytelling include Column, Bar Chart, Line, Area, Pie, Donut, and Combo charts, among others.
But, Excel produces pretty basic charts that require a lot of tweaking to be appealing or communicate insights fast. Besides, this spreadsheet tool lacks advanced charts that you may need to create compelling data stories.
Well, there’s a tool that supercharges your favorite spreadsheet tool. Yes, you read that right. This tool enhances Excel to generate insightful, visually appealing, and most importantly, easy to interpret charts.
This blog will walk you through how you can supercharge your Excel to create visually appealing and insightful charts. You’ll also get to learn about the top 5 best charts in Excel produced by our mysterious tool.
In this blog you will learn:
Keep reading to discover the amazing visualization tool.
Before we delve into the best charts you need to try, let’s talk about the tool we introduced briefly at the introduction.
The name of the tool is ChartExpo.
This amazingly easy-to-use tool comes as an add-in you can download and install into your Excel.
So why do we recommend this tool?
ChartExpo integrates seamlessly with your Excel to create stunning and highly insightful charts for your data stories. Besides, it comes loaded with 50-plus charts to ensure you get the most out of your vast data.
With ChartExpo, you don’t need to know programming or coding. Yes, it’s that easy peasy to use.
When you’re curating a data story, feel confident you have a reliable data visualization buddy on your side. ChartExpo provides you unlimited freedom to customize your chart to align with your data story.
You can highlight the key insights you want your audience to take in with ease. You just need a few mouse clicks to access the best charts in Excel that fit seamlessly within your data narrative.
To Get Started with advanced Excel charts library which is ChartExpo for Excel add-In, follow the Simple and Easy Steps Below.
You will find 6 unique categories of data visualizations.
Let’s talk about the top 5 best charts in Excel you can create using ChartExpo.
A Comparison Bar Chart is one of the best charts in Excel you can use to compare the metrics in your data with respect to dimensions, such as time.
You can only access this chart template once you’ve installed ChartExpo in your spreadsheet.
You can use this chart to compare the performance of metrics in your data in different periods easily.
Like we said, a Comparison Bar Chart is one of the best advanced Excel charts you can use to create persuasive data narratives for your target audience.
Let’s use the tabular data below to get started with this advanced
Excel chart. This data is about students registered for the subjects in different years.
Year | Subject | Count |
2018 | Introduction to Probability | 700 |
2018 | Calculus Applied | 250 |
2018 | Computer Science for Lawyers | 300 |
2018 | The Architectural Imagination | 600 |
2018 | Principle of Biochemistry | 600 |
2018 | Data Science: R Basics | 250 |
2018 | Introduction to Game Development | 800 |
2018 | Entrepreneurship in Emerging Economics | 800 |
2018 | Understanding Technology | 600 |
2018 | Using Python for Research | 400 |
2018 | Data Science: Productivity Tools | 350 |
2018 | Data Science: Inference and Modeling | 800 |
2018 | Data Science: Wrangling | 250 |
2018 | Data Science: Linear Regression | 700 |
2019 | Introduction to Probability | 300 |
2019 | Calculus Applied | 350 |
2019 | Computer Science for Lawyers | 200 |
2019 | The Architectural Imagination | 350 |
2019 | Principle of Biochemistry | 800 |
2019 | Data Science: R Basics | 400 |
2019 | Introduction to Game Development | 650 |
2019 | Entrepreneurship in Emerging Economics | 550 |
2019 | Understanding Technology | 700 |
2019 | Using Python for Research | 250 |
2019 | Data Science: Productivity Tools | 500 |
2019 | Data Science: Inference and Modeling | 700 |
2019 | Data Science: Wrangling | 450 |
2019 | Data Science: Linear Regression | 500 |
2020 | Introduction to Probability | 700 |
2020 | Calculus Applied | 180 |
2020 | Computer Science for Lawyers | 250 |
2020 | The Architectural Imagination | 180 |
2020 | Principle of Biochemistry | 300 |
2020 | Data Science: R Basics | 500 |
2020 | Introduction to Game Development | 700 |
2020 | Entrepreneurship in Emerging Economics | 600 |
2020 | Understanding Technology | 300 |
2020 | Using Python for Research | 450 |
2020 | Data Science: Productivity Tools | 600 |
2020 | Data Science: Inference and Modeling | 600 |
2020 | Data Science: Wrangling | 500 |
2020 | Data Science: Linear Regression | 300 |
The subject with the highest enrollment rate in 2020 is “Introduction to Game Development,” up from 4th in 2019 and 3rd position in 2018.
Conversely, “Computer Science for Lawyers” has the lowest enrollment rate across the 3 periods (2018, 2019, and 2020).
Slope Charts are simple graphs that quickly and directly show transitions, changes over time, absolute values, and even rankings. Besides, they’re also called Slope Graphs.
You can use this chart to show the before and after story of variables in your data.
Slope Graphs can be useful when you have two time periods or points of comparison and want to show relative increases and decreases quickly across various categories between two data points.
Let’s use the tabular data below in our example to get you started with data storytelling using a Slope Chart.
Period | Months | Measure |
2020 | January | 69 |
2020 | February | 34 |
2020 | March | 16 |
2020 | April | 28 |
2020 | May | 43 |
2020 | June | 56 |
2020 | July | 74 |
2020 | August | 29 |
2020 | September | 60 |
2020 | October | 75 |
2020 | November | 67 |
2020 | December | 45 |
2019 | January | 78 |
2019 | February | 43 |
2019 | March | 20 |
2019 | April | 35 |
2019 | May | 39 |
2019 | June | 67 |
2019 | July | 65 |
2019 | August | 35 |
2019 | September | 70 |
2019 | October | 65 |
2019 | November | 87 |
2019 | December | 50 |
This chart gets its name from its shape. In other words, it looks like a spider web, in which variables are organized in different shapes.
The Radar Chart is one of the best charts in Excel, because it’s incredibly easy to understand and customize. Furthermore, you can show several metrics across a single dimension. Use Radar charts to uncover outliers and commonalities in your data.
So how can you get started with Radar Charts?
If you’ve already installed ChartExpo in your Excel, follow the steps below to get started. But, if you’ve not installed ChartExpo, follow the easy-to-follow instructions above to get started with this FREE add-on.
Let’s use the example below.
Imagine you run a beauty brand, and want to know the best and worst-sellers in a given financial year. The products in your inventory include face creams, skin lightening creams, and beauty creams.
Let’s use the table below for our scenario.
Product | Month | Number of Orders |
Face Cream | Dec | 80 |
Face Cream | Nov | 65 |
Face Cream | Oct | 75 |
Face Cream | Sep | 80 |
Face Cream | Aug | 90 |
Face Cream | July | 85 |
Face Cream | June | 65 |
Face Cream | May | 70 |
Face Cream | April | 80 |
Face Cream | Mar | 93 |
Face Cream | Feb | 99 |
Face Cream | Jan | 80 |
Skin Lightening Cream | Dec | 100 |
Skin Lightening Cream | Nov | 60 |
Skin Lightening Cream | Oct | 95 |
Skin Lightening Cream | Sep | 75 |
Skin Lightening Cream | Aug | 100 |
Skin Lightening Cream | July | 60 |
Skin Lightening Cream | June | 95 |
Skin Lightening Cream | May | 75 |
Skin Lightening Cream | April | 109 |
Skin Lightening Cream | Mar | 80 |
Skin Lightening Cream | Feb | 109 |
Skin Lightening Cream | Jan | 75 |
Beauty Cream | Dec | 50 |
Beauty Cream | Nov | 55 |
Beauty Cream | Oct | 51 |
Beauty Cream | Sep | 40 |
Beauty Cream | Aug | 45 |
Beauty Cream | July | 30 |
Beauty Cream | June | 39 |
Beauty Cream | May | 45 |
Beauty Cream | April | 56 |
Beauty Cream | Mar | 39 |
Beauty Cream | Feb | 48 |
Beauty Cream | Jan | 44 |
Face cream performed well in February, March, and July. On the other hand, skin lightening products performed well during April, June, August, October, and December.
The beauty cream was the poorest performer. And this means there’s a need for an in-depth investigation to determine the reason for abysmal performance of the product throughout the financial year.
A Matrix Chart shares remarkable similarities with the traditional bar chart. But, the critical difference is that the bars in this chart are stacked on each other to enhance comparison and come with parallel to other data to make it easier to understand the differences.
We recommend this diagram, which is one of the best charts in Excel, if your goal is to extract high-level insights from your data.
Let’s use the tabular data below to get started with this chart.
Brand | Store | Period | Number of Orders |
Adidas | Store-B | Current | 100 |
Adidas | Store-B | Previous | 200 |
Adidas | Store-C | Current | 450 |
Adidas | Store-C | Previous | 600 |
Adidas | Store-A | Previous | 400 |
Adidas | Store-A | Current | 620 |
Nike | Store-B | Current | 240 |
Nike | Store-B | Previous | 400 |
Nike | Store-C | Current | 70 |
Nike | Store-C | Previous | 100 |
Nike | Store-A | Previous | 500 |
Nike | Store-A | Current | 300 |
Tesco | Store-B | Current | 700 |
Tesco | Store-B | Previous | 600 |
Tesco | Store-C | Current | 500 |
Tesco | Store-C | Previous | 300 |
Tesco | Store-A | Previous | 1200 |
Tesco | Store-A | Current | 800 |
lucky brand | Store-B | Current | 150 |
lucky brand | Store-B | Previous | 70 |
lucky brand | Store-C | Current | 350 |
lucky brand | Store-C | Previous | 250 |
lucky brand | Store-A | Previous | 600 |
lucky brand | Store-A | Current | 700 |
Calvin Klein | Store-B | Current | 200 |
Calvin Klein | Store-B | Previous | 150 |
Calvin Klein | Store-C | Current | 60 |
Calvin Klein | Store-C | Previous | 80 |
Calvin Klein | Store-A | Previous | 200 |
Calvin Klein | Store-A | Current | 250 |
DIESEL | Store-B | Current | 800 |
DIESEL | Store-B | Previous | 500 |
DIESEL | Store-C | Current | 300 |
DIESEL | Store-C | Previous | 600 |
DIESEL | Store-A | Previous | 400 |
DIESEL | Store-A | Current | 500 |
DOCKERS | Store-B | Current | 250 |
DOCKERS | Store-B | Previous | 200 |
DOCKERS | Store-C | Current | 300 |
DOCKERS | Store-C | Previous | 100 |
DOCKERS | Store-A | Previous | 400 |
DOCKERS | Store-A | Current | 350 |
George | Store-B | Current | 700 |
George | Store-B | Previous | 500 |
George | Store-C | Current | 250 |
George | Store-C | Previous | 300 |
George | Store-A | Previous | 200 |
George | Store-A | Current | 100 |
SANMAR | Store-B | Current | 70 |
SANMAR | Store-B | Previous | 100 |
SANMAR | Store-C | Current | 40 |
SANMAR | Store-C | Previous | 80 |
SANMAR | Store-A | Previous | 150 |
SANMAR | Store-A | Current | 80 |
As soon as you click on the button chart will be ready.
A Stacked Bar Diagram is one of the best charts in Excel you can use to visualize part-to-whole relationships in your data.
Each bar in this chart represents a whole. And segments inside each bar represent different parts or categories of the whole. Different colors are used strategically to illustrate parts-to-whole insights.
A Stacked Bar Diagram is one of the advanced Excel charts you can easily use to compare data points for in-depth, high-level insights. This chart empowers you to see the percentage of each data point compared to the total value.
Stacked Bar Charts can help you save a lot of hours because it’s incredibly easy to plot, primarily if you use ChartExpo.
Let’s use the sample data below to get started with Stacked Bar Charts.
Team | Silver | Gold | Bronze |
USA | 41 | 39 | 33 |
Japan | 14 | 27 | 17 |
Australia | 7 | 17 | 22 |
Italy | 10 | 10 | 20 |
Germany | 11 | 10 | 16 |
France | 12 | 10 | 11 |
Brazil | 6 | 7 | 8 |
Cuba | 3 | 7 | 5 |
Poland | 5 | 4 | 5 |
Data visualization is incredibly important, especially in today’s world. Besides, it applies to almost all the sectors of the economy, including art and entertainment. Data visualization helps you save time taken to crunch raw numbers manually for in-depth insights.
Besides, it helps our brains to make sense of raw data in visual form quickly and effectively.
Data visualization is the graphical representation of raw data for insights. Some of the best charts in Excel to use are Radar, Line, Stacked Bar, Comparison Non Sentimental, and Bar Stack Comparison Charts, among others.
You can only access these advanced Excel charts via third-party add-ins, such as ChartExpo.
Congratulations if you’ve read the blog up to this point.
As we said, to get the most out of your data, you need the best charts in Excel. Why?
You don’t want your readers (or target audiences) to struggle to interpret the meaning and context of your data narrative. Using the right advanced Excel charts will not only save a ton of time but also make your data story persuasive.
Accessing the best charts in Excel (top 5 charts we highlighted earlier) does not have to be a struggle or even time-intensive. You need an intuitive and easy-to-use add-in to supercharge your Excel.
The data visualization tool we recommend to our readers is ChartExpo because of its full stack of tools, namely, graph maker, chart templates, and a data widget library.
These functionalities are incredibly easy to use. And this means you don’t need uber technical skills, such as coding or programming skills.
ChartExpo produces charts that are incredibly insightful and easy to read, even for non-technical audiences. So you can EASILY create social media reports, sales reports, and goal projections with this tool.
ChartExpo add-in has everything you need to create a compelling data story for your target readers (and target audiences). Try ChartExpo today to get the most out of your data.
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