a visual representation of worksheet data in excel

How to Visualize Data in Excel (With Examples)

According to Linearity , it is easier for the brain to retain data when they’re visually represented. Especially for larger data sets, it is always a good idea to illustrate your data with color-coded formatting, charts, and graphs.

Excel is a powerhouse when it comes to analyzing data. It also contains many data visualization tools, including 19 types of charts, heat maps, and 4 library icon sets.

We’ll be going through these tools and discuss what data they best represent through examples!

Charts in Excel

Charts are best used to monitor performances and analyze results. If you’re creating a presentation to compare annual sales, represent it in a chart.

Excel offers a variety of charts from simple bar charts to even map charts! Each chart is usually of these types:

• Clustered Chart : Visualize your chart in a 2-D format that includes the horizontal (X), and vertical (Y) axis.
• Stacked Chart : Illustrates the contribution of each data value in the entire data set.
• 100% Stacked Chart : Show the relative percentage of each data value in the set. The total value of one stacked chart is equal to 100.
• 3-D Chart : Includes a third axis called the depth (Z) axis.

To insert charts in Excel, first select data. Then, go to the Insert tab. On the Charts section, click on the chart you wish to insert.

If you’re unsure of what chart to use, select your data and click on Recommend Charts from the Charts section to get suggestions.

With that, let’s see every chart in detail.

Column Chart

Column charts are vertical bars that represent items on the horizontal (X) axis and frequency on the vertical (Y) axis. 

Column charts are clustered, stacked, 100% stacked, and 3-D column charts. These charts (except 3-D column charts) can be formatted to show values in 2-D or 3-D.

A line chart is used to show trends over a specific interval. When data increases, the line flows vertically upwards. Similarly, if the progress declines, it moves down the chart. 

Excel offers line charts, stacked line charts, 100% line charts, and 3-D line charts. You can insert markers representing the data value specified on your data set. 

A pie chart illustrates the total composition of an object or a task. If you need to break the pie chart further down, insert either a pie of pie or a bar of pie chart instead of a pie chart.

Excel allows you to format these charts in both 2-D and 3-D format.

Doughnut Charts

A doughnut chart is similar to a pie chart, except it can also be used to display negative values in the chart. The data value in a doughnut chart is represented in percentages that sum up to 100%

Data values in a bar graph are represented as horizontal bars. The bar stretching the farthest is the greatest value, while the bar closest to the Y axis is the smallest value. 

You have the option to insert bar charts as clustered, stacked, or 100% stacked.

An Area chart looks quite similar to a line chart. While they both display trends, an area below the plotted lines in an area chart is filled with a color. This makes data analysis easier when there are multiple trends to follow.

Area charts are of three types: Area chart, stacked area chart, and 100% stacked area chart. Excel offers all three area charts in 2-D and 3-D formatting.

Scatter and Bubble Chart

Scatter and Bubble charts establish a relationship between two data sets. If you’re trying to visualize the cost of making and the total profit made on a product, creating such plots is the correct way to go.

Create scatter charts with just the markers, smooth lines, or both—smooth lines and markers. Similarly, you have the option to insert scatter lines with straight lines or straight lines with markers.

For bubble charts, formatting is available in 2-D and 3-D effects.

Stock Chart

As the name gives it away, the stock chart is handy when it comes to monitoring the rise and fall of stocks.

If you’ve scrapped such data from the web, create a stock chart to visualize how the stock you’ve invested in is performing in the market.

A stock chart is also useful in tracking geographical data such as temperature rise and annual precipitation.

There are multiple types of stock charts depending on the number of your data series in Excel. These types include High-low-close , Open-high-low-close , Volume-high-low-close , and Volume-open-high-low-close .

For Excel to identify your data, always label and arrange them according to the chart type.

Surface Chart

Surface charts are mostly used by engineers and geologists to determine the elevation of an area. Surface charts use three variables when plotting data, making it a 3-D chart.

Surface charts are of four types in Excel consisting of 3-D surface , wireframe 3-D surface , contour , and wireframe contour chart .

Radar Chart

Radar charts, also referred to as spider charts, are used to compare items on a specific characteristic. 

If you’re quantitatively comparing the qualities of products, use radar charts to spot which feature a certain product stands out the most.

You can insert markers with markers or even fill them up with colors in Excel.

Other Charts (Available for Excel 2016 and Later)

The above-mentioned charts are available in all versions of Excel. However, if you’re on Excel 2016 or later, you have the option to insert other charts including:

• Treemap chart
• Sunburst chart
• Histogram charts
• Box and Whisker charts
• Waterfall charts
• Funnel charts
• Combo charts

A heat map is a visualization technique where you color-code numbers according to their values. Heat maps are excellent for when you’re analyzing weather reports, profit-loss, and even a mark sheet. 

Excel offers six 3-color and  2-color scales to create heat maps. Additionally, you have the option to customize the color palette to create a heat map.

You can create heat maps on Excel range, tables, and even PivotTables .

Let’s create a Green-Yellow-Red color scale heat map in the sales sheet below:

Icon sets are a part of the conditional formatting utility. You can insert icons on your data set based on a hierarchy or a custom rule.

There are four types of icons— Directional , Shapes , Indicators , and Ratings .

Directional

Directional icons show if the values have increased, increased, or remained constant in the form of arrows.

Excel allows you to choose from seven sets of arrows when inserting directional icons. Use directional icons when analyzing financial data such as a sales report.

Let’s enter directional icons to compare the sales made by Julie in twenty days:

According to the results, Julie’s performance is not that great.

Shapes and Indicators

As Shapes and Indicators are more or less the same, I’ve grouped them under the same category.

Let’s review my expenses for the past six months as an example. I’ve set a budget of $50-$100 for each category. However, I’ve gone over budget in a few areas.

We’ll be inserting shapes to make this visualization:

• Go to Home > Conditional Formatting > Icon Sets .

As the data illustrates, I have gone over my budget every month except October. This might be my sign to start budgeting more seriously!

Excel offers five types of rating icons. You can represent your ratings in the form of 3 stars, 5 quarters, 4 boxes, 4 ratings, and 5 ratings.

In this table, I have the total rating of 10 different hotels on a scale of 1-5. Let’s enter the 5 ratings icons to represent these icons.

According to the illustration, Hotel Safe Haven and Hotel Paradise have the highest ranges. Whereas, Hotel Heaven and Lake View Hotel have the lowest ratings on average.

Use Analyze Data in Excel (Excel 365)

If you’re on Excel 365, use Excel’s Analyze Data feature to visualize your data set.

Excel uses its smart AI in the Analyze Data tool to generate meaningful visuals, mainly charts and PivotTables.

In this sheet, we have a stock report. Let’s analyze this data using the Analyze Data tool.

• Look for appropriate charts and tables under Discover Insights .

Visualize Excel Data via Power BI

If you frequently need to visualize data, load your Excel sheet to Power BI .

Power BI is a Microsoft 365 E5 package and is a powerful visualization utility. Using Power BI, build visuals using all sorts of charts, graphs, and data tables.

Asmi is a content writer specializing in MS Office. She loves writing Excel-related content to assist other users to learn their way around the program. She started using Excel when she first entered the industry as a marketing intern. Soon, she realized that learning the often-overlooked spreadsheet program was no piece of cake. In her articles, she attempts to brief out complex topics to help beginner to intermediate-level Excel users. Asmi uses Excel for everything, including creating a grocery list to managing her personal finance. She’s a bit dramatic when it comes to the Flash Fill feature; so much so that could write a eulogy out of it. When she’s not working, you’ll find her learning a new recipe, or cleaning up her mess (out of the failed recipe).

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Visualizing Data in Excel: A Comprehensive Guide

By   STC

July 15, 2023

Explore the diverse data visualization possibilities in Excel that aid in analyzing and interpreting your data effectively.

Introduction

Welcome to our comprehensive guide on visualizing data in Excel. In this article, we will delve into the world of data visualization and provide you with valuable insights on how to create compelling visual representations of your data using Excel. Whether you are a beginner or an experienced Excel user, this guide will equip you with the knowledge and techniques to effectively communicate your data through visually appealing charts and graphs.

Why Data Visualization Matters

Data visualization is a powerful tool that enables us to make sense of complex datasets. It allows us to identify patterns, trends, and outliers that might not be immediately apparent in raw data. Visualizing data in Excel not only enhances our understanding of the information at hand but also enables us to communicate our findings to others in a clear and concise manner.

Getting Started with Excel Charts

• Selecting the Right Chart Type Choosing the appropriate chart type is crucial for effectively representing your data. Excel offers a wide range of chart options, including bar charts, line charts, pie charts, scatter plots, and more. Consider the nature of your data and the message you want to convey when selecting the most suitable chart type.
• Formatting and Customization Excel provides extensive formatting and customization options to refine the appearance of your charts. From adjusting axis labels to modifying colors and styles, these features allow you to create visually appealing charts that align with your brand or presentation requirements.
• Adding Data Labels and Annotations To enhance the clarity of your visualizations, Excel enables you to add data labels and annotations. These labels provide additional context and make it easier for your audience to interpret the information being presented. You can include axis labels, data point labels, and explanatory text to further enrich your charts.

Advanced-Data Visualization Techniques

• Creating PivotCharts PivotCharts are a powerful feature in Excel that allows you to visualize data from pivot tables. By summarizing and aggregating data, pivot tables provide a comprehensive overview that can be transformed into dynamic and interactive charts. Utilizing PivotCharts enables you to explore and analyze complex datasets with ease.
• Utilizing Advanced Charting Features Excel offers advanced charting features that can take your visualizations to the next level. From trendlines and error bars to 3D charts and sparklines, these tools allow you to add depth and sophistication to your data representations. Experimenting with these features can help you create visually striking charts that captivate your audience.

Best Practices for Effective Data Visualization

To ensure your data visualizations have maximum impact, keep the following best practices in mind:

• Simplify and Declutter Avoid cluttering your charts with excessive information or unnecessary embellishments. Focus on the key message you want to convey and remove any elements that distract from that message. Remember, simplicity is key when it comes to effective data visualization.
• Use Color Strategically Colors can evoke emotions and draw attention to specific areas of your charts. Use color strategically to highlight important data points or to group related information. However, be mindful of accessibility considerations and ensure that your color choices are accessible to individuals with color vision deficiencies.
• Tell a Story with Your Data Data visualization is not just about presenting numbers; it’s about telling a story. Structure your visualizations in a way that guides your audience through a narrative. Start with an introduction, present the main findings, and conclude with a clear takeaway or call to action.

In conclusion, mastering the art of visualizing data in Excel can significantly enhance your ability to analyze and communicate complex information. By selecting the right chart types, utilizing advanced techniques, and following best practices, you can create visually compelling representations that effectively convey your data’s story. We hope this comprehensive guide has provided you with the knowledge and inspiration to create outstanding data visualizations in Excel. Start exploring the power of data visualization today and unlock new insights from your data.

Check StoryTelling with Charts – The Full Story

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We are passionate about the power of visual storytelling and believe that charts can convey complex information in a captivating and easily understandable way. Whether you're a data enthusiast, a business professional, or simply curious about the world around you, this page is your gateway to the world of data visualization.

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How To Create Data Visualizations in Excel? A Complete Guide

T ransform your Excel sheets from simple spreadsheets to storytelling tools with beautiful and intuitive “data visualizations in Excel”. This powerful feature turns complex data into clear, engaging visuals, making it easier to spot trends, patterns, and insights.

Excel templates can be used for data visualization. Excel as a data visualization tool has several charts, graphs, and maps you can use to visualize your data, like bar graphs, line charts, pivot tables, etc.

What is Data Visualization in Excel?

Definition : Data visualization is the graphic representation of data that makes it easier to interpret. We can create Data visualizations using tools like Data Wrapper, Google Charts, and others. Additionally, data is organized and visualized using an Excel spreadsheet.

Let’s explore Excel’s data visualization features in many different ways. We can use different Excel charts and graphs to visualize data. Additionally, data visualization using Excel templates is possible.

Column charts, bar charts, pie charts, progress bars , line charts, area charts, scatter charts, surface charts, Sankey diagrams , and many others are available in Excel.

Different Types of Data Visualizations in Excel

Column chart.

It is a simple type of graph where data is shown as vertical bars. Select the data and the required option from the Column chart menu to build a column chart. As we can see, several options exist for the Column chart; the best option must be picked.

Horizontal bars are the only difference between this chart type and a column chart. Select the suitable bar chart from the Bar option to make a horizontal bar.

Pivot Table

A pivot table is a tabular representation of data used in data visualization that is used to group, sort, and summarize huge volumes of data.

Advanced Excel Charting Techniques

Combining multiple data series, creating pivot charts.

Pivot charts are powerful tools for summarizing and visualizing large datasets quickly. They work with pivot tables to provide a dynamic way to analyze data. Here’s how to create a pivot chart:

How to Make a Heat Map Visualization in Excel?

To make a heat map, follow the procedures below:

This article introduced the Excel data visualization concept and outlined various visualization techniques. Excel empowers users to communicate data insights, make informed decisions, and create compelling visual narratives , enhancing data analysis processes.

Nadeem Salam

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Excel Visualization: A Guide to Clear Data Presentation for Beginners

I once struggled with dull data tables.

Numbers clustered in rows and columns become a blur. But with Excel visualization , you can empower your audience to make informed decisions based on the data presented. Excel charts and graphs replace chaos, revealing patterns and trends.

Convey ideas efficiently with the right visual. It’s not just about creating a chart; it’s about making data understandable and engaging.

In this article, I’ll guide you step-by-step on transforming your Excel data into insightful visuals.

Let’s get started!

Table of Contents

Understanding the Basics of Excel Visualization

Excel provides various visualization options, whether 2D or 3D versions, standard, stacked, or 100% stacked options. It’s all about finding the right fit that best represents your data and message.

The Excel Charting Interface

Let’s start with creating a chart in Excel.

When you click on the Insert tab in Excel, you’ll see various chart types that you can use to visualize your data.

The Excel charting interface provides a wide range of options, from line and area charts to bar and column charts. When you click on a chart, the ‘ Chart Tools ’ contextual tab provides additional features for customizing your charts.

Types of Data for Visualization

Excel visualization data can be broadly categorized into numerical, categorical, and time-series data.

• Numerical data includes values that can be measured, such as sales figures or temperature readings.
• Categorical data includes information such as names, labels, or groups.
• Time-series data involves values measured over time, such as stock prices or website traffic.

Excel offers different chart types depending on your data type.

Selecting the Right Chart Type

Selecting the right chart type is half the battle for effective data visualization in Excel.

Pie charts are best for part-to-whole comparisons. Use line charts for time series or trends. Bar or column charts are the most suitable for categorical comparisons.

However, consider more advanced chart types for more complex data sets.

Scatter plots are excellent for correlation analysis , while histograms and box plots are ideal for distribution analysis of quantitative data.

It’s all about understanding your data and determining the best way to display it.

Steps for Visualizing Data in Excel – Creating Basic Charts

Creating basic charts in Excel is a fundamental skill for anyone looking to present data in a visual format.

Excel offers a variety of chart types, each with unique properties and use cases. The key to successful chart creation in Excel is understanding these different chart types and knowing how to present your data most effectively with them.

Organizing Your Data

Before you dive into creating Excel charts, it is crucial to organize your data correctly . 

Well-organized data will make the charting process easier and the resulting charts more meaningful. Ensure your data is clean, error-free, and arranged clearly and logically.

This will make it easier to select the data for your charts and create visuals that effectively communicate your data analysis results.

Pie and Donut Chart

Pie charts are popular for showing the proportion of different categories within a whole. While visually appealing, they are often misused and can lead to misleading interpretations.

Generally, they are most effective when comparing a few categories representing parts of a whole.

On the other hand, donut charts are a variation of pie charts with a hole in the middle (as the name implies!). Like pie charts, they can display multiple data series, but they should be used sparingly.

To create a pie chart in Excel:

• Select the data you want to visualize
• From the “ Insert ” tab, choose “ Pie ” from the chart options.
• You can customize your chart by changing the colors, adding labels, and adjusting other settings in the “ Format Chart Area ” pane.

Here’s a video guide on how to create a donut chart:

Line and Area Chart

Line and area charts are handy when dealing with time-series data . These charts plot data points on a graph and connect them with a line, allowing you to see trends over time. 

Check out this video for a step-by-step guide on how to create a line chart:

One of the business essentials when working with line and area charts is customizing the axis and gridlines. This can help make your chart more readable and meaningful .

The “ Format Axis ” pane allows you to customize the axis labels, adjust the scale, and add gridlines.

Column and Bar Graph

Bar and column charts are Excel’s most commonly used chart types. They are excellent for comparing different categories of data.

While bar charts and column charts are often used interchangeably, there is a difference: A bar chart presents data horizontally , while a column chart presents data vertically . This distinction can influence how easily your audience interprets the chart.

You can also choose between a stacked or clustered bar and column chart layout.

In a stacked chart , data series are stacked on each other, while in a clustered chart , they are placed side by side.

To create a bar or column chart:

• Select the data
• Then choose either “Bar” or “Column” from the chart options in the “ Insert ” tab
• Remember to format the chart and the axis labels to make the chart easier to understand

Advanced Charting Techniques

In this section, I’ll describe how to present complex data in a visually appealing and easily understandable format. Since each dataset is unique, treat these charts as ideas for meaningfully presenting your data.

Combination Charts

This type of chart combines the features of line and column charts, allowing you to present mixed data more comprehensively.

For example, when you have a target and actual data for comparison , a combination chart can be the perfect tool for visualization.

Clicking the Chart Design tab on the ribbon allows you to change the chart type and create a customized combination chart.

This allows you to have your target values in columns and the actual values marked along the line, which provides a clearer visualization of your data.

Trendlines and Data Analysis

Another essential feature of Excel charts is the ability to add trendlines. These can be linear, polynomial, or moving average trendlines.

A trendline graphically displays trends in your data , and you can extend it beyond the actual data to predict future values.

Along with trendlines, interpreting R-squared values is also crucial in data analysis. This will help you understand the relationship between your dependent and independent variables, thus enhancing your analysis results.

Check out our detailed how-to post on adding trendlines to Excel charts .

Conditional Formatting in Charts

Conditional formatting is another advanced charting technique in Excel that can enhance your data visualization. You can also add data bars, color scales, and icon sets.

These features allow you to customize your charts based on certain conditions, making it easier for your audience to understand your data. Applying these formatting options enables you to create more engaging and visually appealing charts for your data presentation.

Creating a Tornado Chart in Excel

Tornado charts are particularly effective when comparing and contrasting different variables . A well-crafted tornado chart can help you visualize how changes in several factors can impact a specific outcome – for example, the impact of inflation on NPV and IRR results.

Here’s a video showing you how to create a tornado chart:

Designing a Funnel Chart in Excel

Funnel Charts in Excel are highly effective tools for monitoring sales processes or any other process that narrows down over time.

Here are two quick methods for designing funnel charts in Excel:

Building a Waffle Chart in Excel

Waffle charts, also known as square pie or waffle bar charts, are a great way to visualize individual data points compared to the whole data set. They are a fun and engaging way to present percentages or proportions.

Here is a simple method for creating waffle charts:

Data Visualization Tips – Enhancing Chart Aesthetics

The aesthetics of your Excel chart play a significant role in how effectively your data is communicated.

A visually appealing chart is easier to understand and engages your audience. Enhancing chart aesthetics involves working with various chart elements and features, such as colors, styles, and data labels.

Adding data labels, for instance, provides additional information on your chart, making it easier to interpret.

Besides, you can customize the chart’s colors and styles to match your presentation theme or company branding.

Check out this post for more information on good dashboard design principles .

Working with Chart Elements

Working with chart elements can significantly improve the readability and effectiveness of your data visualization.

Some key chart elements you can manipulate include titles, legends, and data labels.

• Data labels provide additional context to your data and can be customized to suit your chart
• Modify axis labels and gridlines to adjust their appearance and improve readability. Check out this video on how to add gridlines to your Excel charts:

These chart elements can enhance your aesthetic appeal and make your data easier to interpret.

Customizing Chart Colors and Styles

Spicing up your Excel charts is easier than you think.

The ‘ Chart Design ‘ tab in the Excel ribbon allows you to alter your charts’ aesthetics significantly.

Navigate to the ‘ Chart Styles ‘ section, and you’ll see various styles for your chart. 

Looking for a bit more customization? No problem! Simply click the ‘ Change Colors ‘ dropdown and choose a color scheme.

You can use Excel’s preset color schemes or create a custom color palette for brand consistency. Minor visual changes can significantly affect your chart’s overall look and feel.

3D Charts and Effects

Adding a third dimension to your charts can make them pop . But be careful.

While 3D effects can add a specific wow factor, they can also lead to misinterpretations of your data if they are not used properly.

To add 3D effects to your charts, click the ‘ Chart Styles ‘ and choose a style with 3D effects. 

Remember, though, that 3D effects should be used sparingly and only when they can enhance the understanding of the data. Overuse of these effects can lead to cluttered, confusing charts. When it comes to 3D effects, less is often more .

Advanced Excel Graphics

Beyond the basic charts, Excel offers advanced graphics capabilities to take your data presentation to the next level.

This includes using Sparklines, shapes, and icons, among other features.

Sparklines are mini-charts within individual cells, each representing a row of data. They give a quick snapshot of trends, helping you understand your data at a glance.

Excel offers line, column, and win/loss types of Sparklines that you can add with the Quick Analysis tool.

Using Shapes and Icons

Remember to appropriately format these shapes and icons to convey the right message and not distract from the data.

Portraying a Story Through Data

Excel visualization is not just about creating charts or diagrams; it’s about telling a story with your data. This is where the concept of data storytelling comes in.

It’s about using visualization tools to highlight key points and trends in your data, making it easier for your audience to understand and absorb.

It’s not unlike creating a plot in a novel where rows and columns of data are the characters, and the chart is the narrative arc. Every element should convey your story effectively and compellingly, from simple bar charts to intricate trend analysis.

Exporting and Sharing Your Visualizations

Once you’ve created your data visualization in Excel, it’s important to know how to share it! This involves exporting the visual representation of data in a format that others can easily access.

Whether you’re sharing a simple bar graph or a complex infographic, the export method will depend on the intended use of the chart/graphic.

This process can be as simple as saving your chart as an image or embedding Excel visuals in PowerPoint presentations and documents.

Saving Charts as Images

One of the simplest ways to share visualizations is by saving them as images .

To do this, right-click the chart and select ‘Save as Picture.’ Several image formats are available, each with its uses.

For instance, JPEG is great for photographic images, while PNG is ideal for images with transparent backgrounds. However, it’s important to consider the resolution of your image. High resolution is crucial for clear, crisp images, especially if they’re intended for print.

Embedding Excel Visuals in Presentations and Documents

Embedding them in presentations and documents is another way to share your Excel visualizations.

This can be done in two ways: linking and embedding .

• Linking refers to connecting the original Excel file and the document where it’s inserted. Any changes made to the original file will automatically update in the document (assuming the link isn’t broken ).
• Embedding involves inserting a copy of the chart into the document. While this won’t update automatically, it ensures that the chart will always be available, regardless of the status of the original file.

Both methods have advantages and should be chosen based on your specific needs.

Frequently Asked Questions

What are some common mistakes for beginners to avoid in data visualization with excel.

Common mistakes include overcrowding the chart with too much data, using inappropriate chart types, neglecting to label axes or data points clearly, and choosing colors or styles that reduce readability.

What are the best practices for presenting Excel data visually to a non-technical audience?

Focus on simplicity and clarity .

Use straightforward chart types, avoid technical jargon, and highlight key takeaways. Ensure your charts are well-labeled, and use annotations or callouts to draw attention to important data points.

What are some resources to learn more about Excel visualization? 

For more tips and tricks, visit my YouTube channel . Alternatively, look at Chandoo’s training, where I learned many excellent dashboard design ideas.

Can Excel visualization help in career development?

Absolutely! Proficiency in Excel visualization is a valuable skill in many industries.

It’s especially relevant in fields like data science, finance, marketing, and others involving large amounts of data. Effectively communicating data through graphical representation can give you a significant advantage in your professional journey.

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Creating Data Visualizations in Excel: What to Keep in Mind

• 14 Oct 2021

One of the most valuable and abundant resources businesses have at their disposal is data. With vast amounts of data being generated every minute of every day, the insights gleaned can inform virtually every business decision —often resulting in favorable outcomes.

There are many data visualization tools on the market designed for creating illustrations for business purposes. Fortunately, one of the most popular and easy-to-use options is likely already installed on your computer: Microsoft Excel.

If you don’t have access to Microsoft Excel, consider using free options like Google Sheets for a similar, albeit more limited, experience.

While Excel isn’t visualization software, it’s a versatile, powerful tool for professionals of all levels who want to analyze and illustrate datasets. Here are the types of data visualizations you can create in Excel and the steps involved in doing so, along with some tips to help you along the way.

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Types of Data Visualizations in Excel

There are different data visualization techniques you can employ in Excel, depending on the data available to you and the goal you’re trying to achieve, including:

• Area charts
• Scatter plots

Other visualization techniques can be used to illustrate large or complex data sets. These include:

• Gantt charts
• Highlight tables
• Bullet graphs

More advanced visualizations, such as those that include graphic elements like geographical heat maps, may not be possible to create in Excel or require additional tools.

Related: 6 Data Visualization Examples to Inspire Your Own

How to Create Data Visualizations in Excel

The steps involved in creating data visualizations in Excel depend on the type of graph or chart you choose. For basic visualizations, the process is largely the same. More complex datasets and illustrations may require additional steps.

To craft a data visualization in Excel, start by creating an organized spreadsheet. This should include labels and your final dataset.

Then, highlight the data you wish to include in your visual, including the labels. Select “insert” from the main menu and choose the type of chart or graph you’d like to create. Once you’ve made your selection, the visualization will automatically appear in your spreadsheet.

Right-click on the chart or graph to edit details, such as the title, axes labels, and colors. Doing so will open a pop-up or side panel that includes options to add a legend, adjust the scale, and change font styles and sizes.

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Tips for Creating Visualizations in Excel

1. choose the right type of visualization.

To create an effective data visualization, it’s critical to choose the right type of chart or graph. Consider the type of data you’re using, the size of your dataset, and your intended audience.

A mismatch between the type of data being leveraged and the visual used to present it can be detrimental to viewers’ understanding of the information. Whether you’re working with qualitative or quantitative data, for example, impacts how you should display the information.

Your intended audience also influences how simplified or complex your illustration should be. For instance, when presenting to a large audience or high-level stakeholders, it’s helpful to distill your presentation to highlight key trends and insights rather than individual data points.

2. Remove Irrelevant or Inaccurate Data

Ultimately, your visualization’s quality is only as good as that of the data you use. For this reason, it’s important to clean data after it’s been collected to remove any irrelevant or inaccurate information. This process is often referred to as data wrangling or data cleaning.

Failure to thoroughly clean data prior to using it can be detrimental to its integrity and lead to inaccurate or misleading data visualizations .

Related: What Is Data Integrity & Why Does It Matter?

3. Provide Context For the Visualization

If necessary, include a key or legend and additional context to help viewers make sense of your illustration.

For example, consider a heatmap that shows the frequency of COVID-19 infections in a location over a specific period. To form a clear understanding of the information being presented, viewers need to know details such as the period being examined, the data source, and what each color means.

This context is important because it helps viewers interpret the information being displayed. Without a key clearly defining the coloring system, for instance, it would be virtually impossible to know what each color indicates, rendering the heatmap useless.

4. Tell A Story

Finally, the key to crafting a compelling visualization is to use data to tell a story. If the data illustrates a trend or supports a hypothesis, your visualization should make that clear. After all, the purpose of visualizations is to present findings in a way that’s easy for viewers to digest and understand.

Telling a story not only makes your visualization more interesting and engaging but also aids in data-driven decision-making . In addition, it helps stakeholders understand the essence of your findings and, in turn, informs their decision-making processes .

Making Data-Backed Business Decisions

Data visualization is a powerful tool when it comes to addressing business questions and making informed decisions. Learning how to create effective illustrations can empower you to share findings with key stakeholders and other audiences in a manner that’s engaging and easy to understand.

You don’t have to be in an analytics or data science role to take advantage of data visualizations. Professionals of all levels and backgrounds can develop data skills to more effectively communicate within their organizations and make informed decisions.

Are you interested in improving your analytical skills? Learn more about Business Analytics —one of the three courses that comprise CORe —which teaches you how to apply analytical techniques in Excel to solve real business problems.

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• Excel Data Analysis Tutorial
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Excel Data Analysis - Data Visualization

You can display your data analysis reports in a number of ways in Excel. However, if your data analysis results can be visualized as charts that highlight the notable points in the data, your audience can quickly grasp what you want to project in the data. It also leaves a good impact on your presentation style.

In this chapter, you will get to know how to use Excel charts and Excel formatting features on charts that enable you to present your data analysis results with emphasis.

Visualizing Data with Charts

In Excel, charts are used to make a graphical representation of any set of data. A chart is a visual representation of the data, in which the data is represented by symbols such as bars in a Bar Chart or lines in a Line Chart. Excel provides you with many chart types and you can choose one that suits your data or you can use the Excel Recommended Charts option to view charts customized to your data and select one of those.

Refer to the Tutorial Excel Charts for more information on chart types.

In this chapter, you will understand the different techniques that you can use with the Excel charts to highlight your data analysis results more effectively.

Creating Combination Charts

Suppose you have the target and actual profits for the fiscal year 2015-2016 that you obtained from different regions.

We will create a Clustered Column Chart for these results.

As you observe, it is difficult to visualize the comparison quickly between the targets and actual in this chart. It does not give a true impact on your results.

A better way of distinguishing two types of data to compare the values is by using Combination Charts. In Excel 2013 and versions above, you can use Combo charts for the same purpose.

Use Vertical Columns for the target values and a Line with Markers for the actual values.

• Click the DESIGN tab under the CHART TOOLS tab on the Ribbon.
• Click Change Chart Type in the Type group. The Change Chart Type dialog box appears.

Click Combo.

Change the Chart Type for the series Actual to Line with Markers. The preview appears under Custom Combination.

Your Customized Combination Chart will be displayed.

As you observe in the chart, the Target values are in Columns and the Actual values are marked along the line. The data visualization has become better as it also shows you the trend of your results.

However, this type of representation does not work well when the data ranges of your two data values vary significantly.

Creating a Combo Chart with Secondary Axis

Suppose you have the data on the number of units of your product that was shipped and the actual profits for the fiscal year 2015-2016 that you obtained from different regions.

If you use the same combination chart as before, you will get the following −

In the chart, the data of No. of Units is not visible as the data ranges are varying significantly.

In such cases, you can create a combination chart with secondary axis, so that the primary axis displays one range and the secondary axis displays the other.

• Click the INSERT tab.
• Click Combo in Charts group.
• Click Create Custom Combo Chart from the drop-down list.

The Insert Chart dialog box appears with Combo highlighted.

For Chart Type, choose −

• Line with Markers for the Series No. of Units
• Clustered Column for the Series Actual Profits
• Check the Box Secondary Axis to the right of the Series No. of Units and click OK.

A preview of your chart appears under Custom Combination.

Your Combo chart appears with Secondary Axis.

You can observe the values for Actual Profits on the primary axis and the values for No. of Units on the secondary axis.

A significant observation in the above chart is for Quarter 3 where No. of Units sold is more, but the Actual Profits made are less. This could probably be assigned to the promotion costs that were incurred to increase sales. The situation is improved in Quarter 4, with a slight decrease in sales and a significant rise in the Actual Profits made.

Discriminating Series and Category Axis

Suppose you want to project the Actual Profits made in Years 2013-2016.

Create a clustered column for this data.

As you observe, the data visualization is not effective as the years are not displayed. You can overcome this by changing year to category.

Remove the header year in the data range.

Now, year is considered as a category and not a series. Your chart looks as follows −

Chart Elements and Chart Styles

Chart Elements give more descriptions to your charts, thus helping visualizing your data more meaningfully.

• Click the Chart

Three buttons appear next to the upper-right corner of the chart −

For a detailed explanation of these, refer to Excel Charts tutorial.

• Click Chart Elements.
• Click Data Labels.

• Click Chart Styles
• Select a Style and Color that suits your data.

You can use Trendline to graphically display trends in data. You can extend a Trendline in a chart beyond the actual data to predict future values.

Data Labels

Excel 2013 and later versions provide you with various options to display Data Labels. You can choose one Data Label, format it as you like, and then use Clone Current Label to copy the formatting to the rest of the Data Labels in the chart.

The Data Labels in a chart can have effects, varying shapes and sizes.

It is also possible to display the content of a cell as part of the Data Label with Insert Data Label Field.

Quick Layout

You can use Quick Layout to change the overall layout of the chart quickly by choosing one of the predefined layout options.

• Click the chart.
• Click the DESIGN tab under CHART TOOLS.
• Click Quick Layout.

Different possible layouts will be displayed. As you move on the layout options, the chart layout changes to that particular option.

Select the layout you like. The chart will be displayed with the chosen layout.

Using Pictures in Column Charts

You can create more emphasis on your data presentation by using a picture in place of columns.

Click on a Column on the Column Chart.

In the Format Data Series, click on Fill.

Select Picture.

Under Insert picture from, provide the filename or optionally clipboard if you had copied an image earlier.

The picture you have chosen will appear in place of columns in the chart.

You might have to present customer survey results of a product from different regions. Band Chart is suitable for this purpose. A Band Chart is a Line Chart with an added shaded area to display the upper and lower boundaries of groups of data.

Suppose your customer survey results from the east and west regions, month wise are −

Here, in the data < 50% is Low, 50% - 80% is Medium and > 80% is High.

With Band Chart, you can display your survey results as follows −

Create a Line Chart from your data.

Change the chart type to −

• East and West Series to Line with Markers.
• Low, Medium and High Series to Stacked Column.

Your chart looks as follows.

• Click on one of the columns.
• Change gap width to 0% in Format Data Series.

You will get Bands instead of columns.

To make the chart more presentable −

• Add Chart Title.
• Adjust Vertical Axis range.
• Change the colors of the bands to Green-Yellow-Red.
• Add Labels to bands.

The final result is the Band Chart with the defined boundaries and the survey results represented across the bands. One can quickly and clearly make out from the chart that while the survey results for the region West are satisfactory, those for the region East have a decline in the last quarter and need attention.

Thermometer Chart

When you have to represent a target value and an actual value, you can easily create a Thermometer Chart in Excel that emphatically shows these values.

With Thermometer chart, you can display your data as follows −

Arrange your data as shown below −

• Select the data.
• Create a Clustered Column chart.

As you observe, the right side Column is Target.

• Click on a Column in the chart.
• Click on Switch Row/Column on the Ribbon.

• Right click on the Target Column.
• Click on Format Data Series.
• Click on Secondary Axis.

As you observe the Primary Axis and Secondary Axis have different ranges.

• Right click the Primary Axis.
• In the Format Axis options, under Bounds, type 0 for Minimum and 1 for Maximum.
• Repeat the same for Secondary Axis.

Both Primary Axis and Secondary Axis will be set to 0% - 100%. The Target Column hides the Actual Column.

• Right click the visible column (Target)
• No fill for FILL
• Solid line for BORDER
• Blue for Color

• Axis → Primary Horizontal
• Axis → Secondary Vertical
• Chart Title
• In the chart, right click on Primary Vertical Axis
• In Format Axis options, click on TICK MARKS
• For Major type, select Inside

• Right click on the Chart Area.
• No line for BORDER

Resize the chart area, to get the shape of a thermometer.

You got your thermometer chart, with the actual value as against target value being shown. You can make this thermometer chart more impressive with some formatting.

• Insert a rectangle shape superimposing the blue rectangular part in the chart.
• Gradient fill for FILL
• Linear for Type
• 180 0 for Angle
• Set the Gradient stops at 0%, 50% and 100%.
• For the Gradient stops at 0% and 100%, choose the color black.
• For the Gradient stop at 50%, choose the color white.

• Insert an oval shape at the bottom.
• Format shape with same options.

The result is the Thermometer Chart that we started with.

Gantt Chart

A Gantt chart is a chart in which a series of horizontal lines shows the amount of work done in certain periods of time in relation to the amount of work planned for those periods.

In Excel, you can create a Gantt chart by customizing a Stacked Bar chart type so that it depicts tasks, task duration, and hierarchy. An Excel Gantt chart typically uses days as the unit of time along the horizontal axis.

Consider the following data where the column −

• Task represents the Tasks in the project
• Start represents number of days from the Start Date of the project
• Duration represents the duration of the Task

Note that Start of any Task is Start of previous Task + Duration. This is the case when the Tasks are in hierarchy.

• Create Stacked Bar Chart.

• Right-click on Start Series.
• In Format Data Series options, select No fill.

• Right-click on Categories Axis.
• In Format Axis options, select Categories in reverse order.

• Adjust the range
• Major Tick Marks at 5 day intervals
• Minor Tick Marks at 1 day intervals
• Format Data Series to make it look impressive
• Give a Chart Title

Waterfall Chart

Waterfall Chart is one of the most popular visualization tools used in small and large businesses. Waterfall charts are ideal for showing how you have arrived at a net value such as net income, by breaking down the cumulative effect of positive and negative contributions.

Excel 2016 provides Waterfall Chart type. If you are using earlier versions of Excel, you can still create a Waterfall Chart using Stacked Column Chart.

The columns are color coded so that you can quickly tell positive from negative numbers. The initial and the final value columns start on the horizontal axis, while the intermediate values are floating columns. Because of this look, Waterfall Charts are also called Bridge Charts.

Consider the following data.

Prepare the data for Waterfall Chart

Ensure the column Net Cash Flow is to the left of the Months Column (This is because you will not include this column while creating the chart)

Add 2 columns – Increase and Decrease for positive and negative cash flows respectively

Add a column Start - the first column in the chart with the start value in the Net Cash Flow

Add a column End - the last column in the chart with the end value in the Net Cash Flow

Add a column Float – that supports the intermediate columns

Compute the values for these columns as follows

In the Float column, insert a row in the beginning and at the end. Place n arbitrary value 50000. This just to have some space to the left and right of the chart

The data will be as follows.

• Select the cells C2:H18 (Exclude Net Cash Flow column)
• Create Stacked Column Chart

• Right click on the Float Series.
• Click Format Data Series.

• Right click on Negative Series.
• Select Fill Color as Red.

• Right click on Positive Series.
• Select Fill Color as Green.

• Right click on Start Series.
• Select Fill Color as Grey.
• Right click on End Series.
• Delete the Legend.

• Right click on any Series
• In Format Data Series options, select Gap Width as 10% under Series Options

Give the Chart Title. The Waterfall Chart will be displayed.

Sparklines are tiny charts placed in single cells, each representing a row of data in your selection. They provide a quick way to see trends.

You can add Sparklines with Quick Analysis tool.

• Select the data for which you want to add Sparklines.
• Keep an empty column to the right side of the data for the Sparklines.

Click SPARKLINES . The chart options displayed are based on the data and may vary.

Click Line . A Line Chart for each row is displayed in the column to the right of the data.

PivotCharts

Pivot Charts are used to graphically summarize data and explore complicated data.

A PivotChart shows Data Series, Categories, and Chart Axes the same way a standard chart does. Additionally, it also gives you interactive filtering controls right on the chart so that you can quickly analyze a subset of your data.

PivotCharts are useful when you have data in a huge PivotTable, or many complex worksheet data that includes text and numbers. A PivotChart can help you make sense of this data.

You can create a PivotChart from

• A PivotTable.
• A Data Table as a standalone without PivotTable.

PivotChart from PivotTable

To create a PivotChart follow the steps given below −

• Click the PivotTable.
• Click ANALYZE under PIVOTTABLE TOOLS on the Ribbon.
• Click on PivotChart. The Insert Chart dialog box appears.

Select Clustered Column from the option Column.

Click OK. The PivotChart is displayed.

The PivotChart has three filters – Region, Salesperson and Month.

Click the Region Filter Control option. The Search Box appears with the list of all Regions. Check boxes appear next to Regions.

Select East and South options.

The filtered data appears on both the PivotChart and the PivotTable.

PivotChart without a PivotTable

You can create a standalone PivotChart without creating a PivotTable.

• Click the Data Table.
• Click the Insert tab.
• Click PivotChart in Charts group. The Create PivotChart window appears.
• Select the Table/Range.
• Select the Location where you want the PivotChart to be placed.

You can choose a cell in the existing worksheet itself, or in a new worksheet. Click OK.

An empty PivotChart and an empty PivotTable appear along with the PivotChart Field List to build the PivotChart.

Choose the Fields to be added to the PivotChart

Arrange the Fields by dragging them into FILTERS, LEGEND (SERIES), AXIS (CATEGORIES) and VALUES

Use the Filter Controls on the PivotChart to select the Data to be placed on the PivotChart

Excel will automatically create a coupled PivotTable.

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Excel Data Visualization: Creating Insightful Charts and Graphs

Explore Excel Data Visualisation techniques to create compelling charts and graphs, enhancing data interpretation and decision-making. This guide equips you with the tools to transform raw data into compelling insights. It covers understanding the basics, customising visuals, and employing effective strategies. Read the blog to learn more.

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Excel isn't just about crunching numbers. It is also a powerful tool for presenting data in visually appealing ways. In this blog, we will dive into the world of Excel Data Visualisation. We will discuss how you can turn rows and columns of data into insightful charts and graphs that tell compelling stories. Scroll down to learn more.  

Table of Contents

1) What Is Data Visualisation in Excel?  

2) Steps for visualising data in Excel  

3) Types of Data Visualisation in Excel with examples  

4) Customising and formatting Excel Charts  

5) Data Visualisation tips in Excel  

6) Conclusion  

What Is Data Visualisation in Excel? 

Data Visualisation in Excel is the art of representing information graphically using charts, graphs, and other visual elements. By converting raw data into visual formats, such as pie charts, bar graphs, and line graphs, Excel helps users better understand patterns, trends, and relationships within their data. 

Steps for visualising data in Excel 

Visualising data in Excel involves several steps to ensure that the resulting charts and graphs effectively communicate the insights hidden within the data. Here's a breakdown of the process:  

1) Prepare your data  

Before diving into visualisation, ensure your data is clean, organised, and formatted correctly. Remove any duplicates, errors, or irrelevant information. Ensure consistent formatting for dates, numbers, and text.  

2) Define your objective  

Clearly outline the purpose of your visualisation. What insights do you aim to convey? Understanding your objective will guide your choice of charts and graphs.  

3) Select the right chart type  

Choose a chart or graph that best represents your data and aligns with your objective. Common chart types include bar graphs, line charts, pie charts, and scatter plots. Consider factors such as data distribution, trends, and comparisons.  

4) Insert the chart  

Once you've selected the appropriate chart type, insert it into your Excel worksheet. Go to the "Insert" tab and choose the desired chart type from the options available. Excel will generate a default chart based on your data.  

5) Customise the chart  

Tailor the appearance of your chart to enhance clarity and visual appeal. Then, customise titles, axis labels, colours, and fonts. Adjust the chart's size and layout to fit your presentation or report. 

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6) Add data labels and annotations  

Incorporate data labels, annotations, or callouts to provide additional context or highlight essential data points. These elements help viewers interpret the chart more easily and understand the significance of the data.  

7) Format data series  

Fine-tune the appearance of individual data series within the chart. Adjust line styles, marker shapes, or bar widths to distinguish between different categories or datasets.  

8) Include trendlines or forecasting  

If applicable, add trendlines or forecasting to visualise patterns or predict future trends. Excel offers various options for trendline analysis, including linear, exponential, and polynomial regression.  

9) Review and revise  

Once your chart is complete, review it carefully to ensure accuracy and clarity. Check for any discrepancies or inconsistencies in the data and make necessary revisions. Solicit feedback from colleagues or stakeholders to validate your interpretation.  

10) Finalise and share  

Once you're satisfied with your visualisation, finalise it for presentation or sharing. Embed the chart into reports, presentations, or dashboards as needed. Consider exporting the chart as an image or PDF for easy distribution.  

By following these measures, you can create compelling and informative visualisations in Excel that effectively communicate insights and drive informed decision-making.  

Types of Data Visualisation in Excel with examples  

Now that you know about the steps for visualising data in Excel, let's break down different types of Data Visualisation with simple explanations.  

1) Column Diagram 

A column diagram, also known as a column chart or bar chart, shows data in vertical columns. Each column here represents a category, and the height of the column indicates the value of the data. For example, you can compare the sales performance of different products over a period of time using a column chart.  

2) Pie Diagram 

A pie diagram, or pie chart, displays data in a circular graph, divided into slices to represent proportions. Each slice corresponds to a category, and the size of the slice shows the proportion of that category relative to the whole. For example, you can use a pie chart to visualise the distribution of expenses in a budget.  

3) Bar Graph 

A bar graph, similar to a column chart, represents data using horizontal or vertical bars. Each bar represents a category, and the length of the bar indicates the value of the data. You can utilise a bar graph to compare different categories or track changes over time, such as comparing monthly sales figures for other regions.  

4) Line Diagram  

A line diagram, also called a line chart, illustrates data points with lines connecting them. It's commonly used to show trends over time. For example, you can plot monthly temperature readings to visualise seasonal variations or track stock prices over a year to identify trends.  

5) Pivot Table 

A pivot table is a powerful tool for summarising and analysing large datasets. It allows you to arrange and summarise data dynamically, making it easier to analyse trends and patterns. Pivot tables can be used to create various types of visualisations, such as pivot charts, which provide a visual representation of the data summarised in the pivot table.  

Customizing and formatting Excel Charts  

Excel offers various customisation options to fine-tune your charts and make them visually appealing and easy to interpret. Experiment with colours, fonts, and chart styles to create professional-looking visuals that align with your data analysis goals.  

Learn to create and prepare Gantt charts by registering for our Excel Training With Gantt Charts course!   

Data Visualisation tips in Excel  

Data Visualisation is about more than just creating charts and graphs. It is about presenting your data in a way that is easy to understand and draws out meaningful insights. In Excel, there are various techniques and strategies you can use to make your visualisations more effective and impactful. Let's explore some key tips for mastering Data Visualisation in Excel:  

1) Select the appropriate visualisation format 

Choosing the correct type of chart or graph is crucial for effectively conveying your message. Consider the nature of your data and the story you want to tell. For example, if you're comparing different categories, a column or bar chart might be suitable. If you're showing proportions, a pie chart could be more appropriate. Experiment with different formats to see which one best represents your data.  

2) Eliminate inaccurate data points 

Ensure the accuracy of your visualisations by identifying and removing any incorrect or irrelevant data points. These inaccuracies can skew the interpretation of your data and lead to wrong conclusions. Take the time to clean and validate your data before creating visualisations to ensure the reliability and integrity of your insights.  

3) Establish context for visualisation 

Make your audience understand the significance of your visualisations by providing the context and background information. Clearly label your axes, include titles and captions, and provide explanations where necessary. Contextualising your visualisations helps viewers grasp the meaning behind the data and enables them to make informed decisions based on the insights presented. 

4) Convey a narrative through Visualisation:  

Craft a compelling narrative around your data to engage and captivate your audience. Use visual elements such as colours, shapes, and annotations to highlight key points and guide the viewer's attention. Your visualisations should tell a story, guiding the viewer through the data and leading them to the insights you want to communicate. Think about the message you want to convey and use visualisation techniques to reinforce that narrative.  

By following these tips, you can elevate your Data Visualisation skills in Excel and create visualisations that are not only informative but also engaging and impactful.  

Conclusion  

Excel Data Visualisation is about more than just making pretty charts and graphs. It's about transforming data into actionable insights. By mastering the art of Excel Data Visualisation, you can unlock your data's full potential and confidently make informed decisions. So, dive in, experiment, and let your data speak volumes through captivating visuals.  

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Frequently Asked Questions

Excel is used for Data Visualisation due to its familiarity, accessibility, ease of use, integration capabilities, and flexibility

Excel offers techniques such as bar charts, pie charts, line charts, scatter plots, histograms, pivot charts, sparklines, and conditional formatting. 

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How to use Excel as a data visualization tool

Microsoft excel has more dataviz capabilities than you may realize. find out how to make your data stand out with charts, pivottables, sparklines, slicers and more..

Everyone knows Microsoft Excel as a number cruncher, but there’s a whole lot more to the popular spreadsheet program. Just as Excel can perform basic data analysis functions , it has a surprising number of data visualization tools under the hood.

“Excel isn’t explicitly a data visualization tool, it’s a spreadsheet,” says Excel developer and consultant Jon Peltier . However, one of Excel’s strengths is its flexibility, he adds. “It’s kind of a Swiss Army knife of software. In addition to formulas, Excel has structures in the worksheet that give it additional functionality for preparing data for analysis in data visualization.”

Read on for a guide to using Excel’s dataviz tools to present your data. We use the Office 365 version of Excel for Windows in the descriptions below; some features may not be available if you use a different version.

The most obvious data visualization option in Excel is its array of charts. Over the years, Microsoft has added more and more chart types to Excel, from basics like bar, line, and pie charts to more advanced styles like scatter and surface charts. Excel 2016 for Windows saw the addition of six new chart types including treemap, sunburst and waterfall, while Excel 2019 added funnel and map charts. (All the new chart types are available to Office 365 subscribers.) See “ Excel 2016 and 2019 cheat sheet ” for details about the new chart types.

A treemap chart shows categories and subcategories of data as different-sized blocks.

To add any kind of chart to a worksheet, select the data you want to chart, click the Insert tab in the Ribbon and click the Recommended Charts button. The Recommended Charts feature looks at your data and suggests a few chart types that will display that data in most impactful way. If none of its suggestions suits you, click the All Charts tab and choose the type you want. To add a trendline to the chart, click Design > Add Chart Element > Trendlines and choose a trendline style.

PivotTables and PivotCharts

A basic Excel feature from which many other visualizations derive is the PivotTable. Doing proper data visualization in Excel starts with knowing how to use PivotTables and understanding how they work, says Peltier.

PivotTables provide a summary of your data, whereby thousands of rows and dozens of columns can be packaged into an easily readable form so you can highlight information and spot trends. They also let you group your data together in different ways so you can draw conclusions more easily, such as how the bottom line for a stat would look without a certain source.

PivotTables are particularly useful if you have long rows or columns of values. Excel has a basic summarization feature, the SUM (=Sum) function, which is great if you want to total up a dozen rows and a few columns. But what if you have hundreds of rows and many columns? PivotTables are like an amped-up SUM function.

The “pivot” part of a PivotTable is the ability to rotate (or pivot) the data in the table in order to view it from a different perspective. Again, this reflects greater data manipulation than the SUM function. For example, if you wanted to look at annual sales but exclude a month or quarter, you can do it with a click or two in a PivotTable. SUM requires more manipulation.

Three PivotTables on the right sum up the raw data on the left.

In the image above, you see the original data on the left, with columns for Product, Origin, Day sold, Price, Unit Sales, and Dollar Sales. There are three PivotTables next to the columns comparing sales of each fruit from imported vs. local sources, total sales for each type of fruit, and how each fruit sold by day of the week. This type of insight is simply impossible with the SUM function.

It’s easy enough to create a PivotTable. Select the rows and columns, with the label at the top of each column, from your data set. Click the Ribbon’s Insert tab, and the first two options are PivotTable and Recommended PivotTables.

With Recommended PivotTables, Excel looks at the contents of the sheet and presents you with a list of thumbnails for various PivotTables generated from all of the categories in your spreadsheet. Select the PivotTable you want and click OK.

The alternative way requires a few more clicks but lets you build a table using your own criteria, in case the manner you’d like to sort the data isn’t among the Recommended options. Click the PivotTable button and you will be asked to select the data range, the rows and columns to be included in the table. Click and drag to cover the range you want and click OK.

Whichever method you use to create the table, Excel will open a new worksheet with the table in it. If you like, you can copy it into the original data sheet as I did in the screenshot. Once you select OK, the PivotTable Fields pane will open on the right side of the screen; here you can select the fields by which to filter your data. If you chose a Recommended PivotTable, you can tweak it by checking and unchecking the fields in the PivotTable Fields pane.

PivotTables have the side benefit of finding sloppiness in your spreadsheets. For example, I do all my personal accounting in Excel, income and expense. In generating a PivotTable for 2018 I saw I had my estimated federal taxes entered as both “Fed” and “Feds,” while deposits were listed either under the publication name or “Deposit.” This forced me to go back and clean up the entries for a more accurate view in the table.

PivotCharts are visual representations of PivotTables. To insert a PivotChart, go to the Ribbon’s Insert tab and select PivotChart. It will ask you to select the data source range, just like a PivotTable, and pick the fields to chart.

PivotCharts let you visually represent the data from a PivotTable.

Excel lets you apply filters to PivotTables to focus on a smaller portion of their data. Slicers are canned filters that slice up data by categories, letting you quickly turn on and off categories to drill down into specific information.

Slicers are inserted from an existing PivotTable, so you must make the table first. From there, go to the Insert tab and click the Slicer button. Using our fruit sales spreadsheet, you can create slicers for specificity on day, location, or unit sales. In this example, we select Product, Origin, and Day.

From there, three boxes pop up for each category. Under Product, select Apples, under Origin select Imported, and leave Day alone. Now we know the total number of imported apples sold that week and on which days. (In the example below, the days shown are automatically generated from the data. Imported apples were sold only on Wednesdays, Thursdays and Saturdays, so the slicer lists those days.)

Slicers let you quickly filter data by category, such as the product, place of origin, and day sold.

Unlike filters, slicers can work across multiple PivotTables. And that is where Slicers work best, on multiple PivotTables. For a single PivotTable, a slicer is not really different from a filter.

You connect two or more PivotTables by first creating them, then right-clicking on any of them and selecting Report Connections. This pops up a box with the connected tables. Initially, only one will be checked, the first one you made. By checking the others, you build the connection.

So again using our fruit spreadsheet, by connecting two PivotTables I can report on product and origin, and thus get a lump sum unit sales figure for locally grown fruit.

Build slicer connections between PivotTables for even more specificity.

A sparkline is a tiny basic chart that appears within a single Excel cell. You can make a line, column, or win/loss sparkline within the cell and use it to highlight trends in your data.

For example, “you might have a dashboard showing how five divisions of your company have done every quarter over the last two years,” says Peltier. If you want a visual representation of how each division has performed, he adds, “you won’t have room on the screen for five regular charts. That type of information is nicely suited to sparklines.”

Sparklines are mini-charts contained in single cells that highlight data trends, as shown at lower right.

You can create a sparkline from data in a table or a PivotTable. Select the data range, such as sales for a 12-month period, then go to the Insert tab on the Ribbon and select Line, Column or Win/Loss from the Sparklines section. Confirm the source data range, choose a destination cell for the sparkline, and click OK.

Remember that a sparkline goes in a single cell, so you’ll want to select data for it from a single row or a single column. That said, you can add multiple sparklines simultaneously by choosing a data range from multiple rows or columns, and choosing the corresponding number of destination cells for the sparklines. In other words, if you want three sparklines to show trends for three rows of data, select three destination cells.

Conditional formatting

Scanning over rows and columns of numbers in a spreadsheet can make your eyes glaze over. To make it easier to spot important data points and trends, you can use Excel’s conditional formatting feature to a table, PivotTable, or range of cells. For instance, you can tell Excel to make high values green and low values red; it will automatically lighten or darken the red and green color depending on how severe the high or low.

Three types of conditional formatting in a single cell: color, bar, and arrow.

Conditional formatting can also be used to highlight profit and loss, giving a good visualization of profit and loss over time, among regions, for different products, and so on. In addition to changing cells’ colors, you can use data bars or a set of icons.

To add conditional formatting, select the data you want to format, select the Home tab on the Ribbon and click the Conditional Formatting button in the Styles group. There you can choose which cells to highlight (e.g., greater than or less than a value, or the top or bottom 10%) and/or apply data bars, color scales or icon sets to the whole selection. The best part is you can add multiple formats. I added a light-to-dark color scale, arrows to indicate an increase or decrease from the previous month, and bars comparing the data in the cells to the single largest monthly entry.

An ancillary feature to conditional formatting and sparklines is adding tiny graphics to a spreadsheet using the Webdings font. “You can’t link to formulas but you can add pizzazz to a workbook by inserting a static picture to describe what your data is,” says Ken Puls, who runs the Excelguru Blog . This helps you summarize information so a manager can get in, see the overall trend and get out, Puls says.

The embedded icons can demonstrate things like upward and downward trends, profit and loss, or status level. To add an icon to a worksheet, go to the Insert tab on the Ribbon, select Icons in the Illustrations group, choose an icon and click Insert. The image appears on your worksheet, with “handles” so you can easily resize, rotate or move it.

Linked data types

Microsoft has recently rolled out an Excel feature it calls linked data types to Office 365 subscribers. Instead of simply numbers or strings, cells can now hold values that linked to an online data source — in this case, Microsoft’s Bing search engine.

Right now there are only two data types: stocks and geography. Excel recognizes a stock ticker symbol or state name in a cell and pulls in relevant data from Bing in real time. Cells with one of these data types include an icon indicating their status, and clicking on the icon brings up a card with relevant information.

A stock cell, for instance, can show all kinds of information about the company and its stock performance, such as current price, 52-week high and low, P/E, and more. And a geography cell can show anything from a location’s population to its power consumption.

Click a linked geography cell to see all sorts of information about that location.

Adding stock cells is quite simple. Enter in a bunch of stock tickers or company names in a single column, then highlight them and click on the Data tab in the Ribbon. In the middle of the Ribbon you’ll see a Data Types group with buttons for Stocks and Geography.

Click Stocks, and your tickers will be replaced with the names of the companies and an icon to the left of each name. Selecting a company will pop up a menu where you can select the types of data you want the company’s card to show.

Geography is also interesting. As with stocks, you enter a bunch of locations — states, countries, cities, etc. — in a single column, select the cells and click Data > Geography. You need to be precise, though. Entering GA, CA, MN and NC and then clicking the Geography button did not yield Georgia, California, Minnesota, and North Carolina for me, but Gabon, Canada, Mongolia, and New Caledonia. Geo, Calif, Minn, and N.C. did the trick. The full state names also work.

Office 365 subscribers can perform a variety of stock and state-to-state comparisons and analysis in Excel.

The array of information about locations that Bing offers is astounding, covering basics like population and GDP but also esoterics like fossil fuel consumption and life expectancy.

Excel’s new linked data types are available only to Office 365 subscribers. Microsoft says it hopes to roll out additional linked data types, but so far the company hasn’t said when.

Introduced in Excel 2016 for Windows (it’s not available for Macs), the Forecast Sheet feature uses AI to project values in the future based on past performance. It works with historical, time-based data and creates a chart with high, low, and median projections. The more data you have to work with, the more precise a prediction it makes.

Using historical data, Excel can project where your data points are headed.

To create a forecast, you must use time-based historical data. Put your cursor in one of the data cells, go to the Data tab on the Ribbon, and in the Forecast group, select Forecast Sheet. On the screen that appears, choose the type of chart (line or bar), the forecast end date, and other options. Click Create, and Excel creates a new worksheet with a chart that contains both the historical data and the predicted values, which are shaded differently than the historical data. This is considered especially helpful for seasonal data.

Quick Analysis

One last tip: If you use Excel 2016, Excel 2019, or Excel for Office 365 in Windows, you can use the Quick Analysis feature to quickly apply an array of visualizations, including conditional formatting, charts, PivotTables and sparklines, to selected data. Highlight the cells you want to analyze, and the Quick Analysis icon pops up near the lower-right corner of the highlighted data. Click the icon and choose the type of visualization you want to add.

The Quick Analysis feature gives you a variety of tools for analyzing your data instantly. (Click image to enlarge it.)

Data visualization in Excel has never been easier.

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Andy Patrizio is a freelance journalist based in southern California who has covered the computer industry for 20 years and has built every x86 PC he’s ever owned, laptops not included.

The opinions expressed in this blog are those of the author and do not necessarily represent those of ITworld, Network World, its parent, subsidiary or affiliated companies.

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MS Excel: Charts

In Microsoft Excel, a chart is often called a graph. It is a visual representation of data from a worksheet that can bring more understanding to the data than just looking at the numbers.

A chart is a powerful tool that allows you to visually display data in a variety of different chart formats such as Bar, Column, Pie, Line, Area, Doughnut, Scatter, Surface, or Radar charts. With Excel, it is easy to create a chart.

Here are some of the types of charts that you can create in Excel.

• How to create a bar chart in Excel 2016 | 2010 | 2007

Column Chart

• How to create a column chart in Excel 2016 | 2010 | 2007

• How to create a pie chart in Excel 2016 | Excel 2007

• How to create a line chart in Excel 2016 | Excel 2007

Advanced Charting

• Create a column/line chart with 8 columns and 1 line in Excel 2003
• Create a chart with two Y-axes and one shared X-axis in Excel 2007

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Guide To What Is The Pictorial Representation Of Worksheet Data

Introduction.

When dealing with a large amount of data, it can be overwhelming to make sense of it all. This is where the pictorial representation of worksheet data comes into play. It is a visual way of representing data using graphs, charts, and other visual elements. This method helps in presenting complex data in a simplified and easy-to-understand format, making it easier for anyone to analyze and interpret the information.

Using pictorial representation in data analysis is crucial as it allows for quick and easy identification of patterns, trends, and outliers at a glance. This visual aid helps in making informed decisions and presenting findings effectively to stakeholders.

Key Takeaways

• Pictorial representation of worksheet data uses graphs, charts, and visual elements to simplify complex data and make it easier to analyze.
• Using pictorial representation allows for quick identification of patterns, trends, and outliers, aiding in making informed decisions.
• When choosing the right pictorial representation, consider the type of data, the message you want to convey, and the audience's familiarity with different types of graphs.
• Best practices for creating pictorial representation include using appropriate scaling, labeling axes, using consistent colors and symbols, and avoiding data distortion.
• Benefits of using pictorial representation include making data easier to understand, highlighting trends and patterns, simplifying complex information, and engaging the audience.

Types of Pictorial Representation

When it comes to representing worksheet data in a visual format, there are several types of pictorial representations to choose from. Each type has its own unique characteristics and is best suited for displaying specific types of data. Let's take a closer look at some of the most commonly used types of pictorial representation:

Bar graphs are one of the most popular and widely used forms of pictorial representation. They are ideal for comparing the values of different categories or groups. The length of the bars represents the value of each category, making it easy to visualize and compare the data.

Pie charts are circular graphs that are divided into slices to represent the proportion of each category within the data set. They are useful for illustrating the breakdown of a whole into its constituent parts and are particularly effective for showing percentages.

• Line graphs

Line graphs are used to display data points connected by straight lines, making it easy to see trends and patterns over time. They are especially useful for showing changes and fluctuations in data over a continuous period.

• Scatter plots

Scatter plots are used to display the relationship between two variables. Each data point is represented by a dot on the graph, and the pattern of the dots can reveal the nature of the relationship between the variables, such as correlation or clustering.

How to Choose the Right Pictorial Representation

When it comes to representing worksheet data visually, selecting the right pictorial representation is essential for effectively communicating information. Here are some key factors to consider when making this decision:

A. Consider the type of data being represented

• 1. Numerical data: If your data consists of numerical values, bar graphs, line graphs, and pie charts are commonly used to depict this type of information. Bar graphs are ideal for comparing values across different categories, while line graphs show trends over time. Pie charts can be used to illustrate the proportion of each category within a whole.
• 2. Categorical data: When dealing with categorical data, bar graphs, pie charts, and stacked bar graphs can effectively showcase this type of information. Bar graphs and stacked bar graphs can compare values within categories, while pie charts display the distribution of each category.
• 3. Relationships between variables: For showing relationships between variables, scatter plots and line graphs are often utilized. These types of graphs can reveal patterns and correlations within the data.

B. Determine the message you want to convey

• 1. Trends: If the goal is to highlight trends or patterns within the data, a line graph or scatter plot may be the most suitable choice. These representations can effectively showcase changes over time or relationships between variables.
• 2. Comparisons: When the objective is to compare different categories or values, bar graphs and pie charts can clearly illustrate these comparisons. Stacked bar graphs are particularly useful for simultaneously comparing subcategories within larger categories.
• 3. Distribution: If you need to display the distribution of categorical data, a pie chart or stacked bar graph can visually represent the proportions of each category within the dataset.

C. Assess the audience's familiarity with different types of graphs

• 1. General audience: If the intended audience is not familiar with complex data representations, it may be best to opt for simpler graphs such as bar graphs and pie charts. These are commonly understood and can effectively convey the information to a broad audience.
• 2. Data-savvy audience: For an audience well-versed in data analysis, more advanced representations like scatter plots and stacked bar graphs may be appropriate. These individuals can interpret and derive insights from more intricate visualizations.

Best Practices for Creating Pictorial Representation

When creating pictorial representations of worksheet data, it's important to follow best practices to ensure that the visualizations accurately and effectively communicate the information. The following are some key best practices to keep in mind:

• Use appropriate scaling

It's important to choose the right scale for your pictorial representation to ensure that the data is accurately represented. Be mindful of the range of the data and choose a scale that effectively captures the variations without distorting the overall picture.

• Label axes and provide a clear title

Labeling the axes and providing a clear title for your pictorial representation is essential for helping the audience understand the context and meaning of the data. Make sure the labels and title are clear, concise, and informative.

• Use consistent colors and symbols

Consistency in the use of colors and symbols in your pictorial representation is crucial for clarity and coherence. Choose a color palette and set of symbols that are easily distinguishable and use them consistently throughout the visualization.

• Avoid distorting the data

It's important to avoid distorting the data in your pictorial representation. Be cautious of various visual techniques such as skewed scales, exaggerated proportions, and manipulated axes that can misrepresent the data.

Tools for Creating Pictorial Representation

When it comes to visualizing data from a worksheet, there are several tools available that can help you create pictorial representations. Here are some of the most popular ones:

Excel is a widely used spreadsheet software that offers various chart and graph options to visually represent data. You can easily create bar graphs, pie charts, line graphs, and more to effectively showcase your worksheet data.

Google Sheets also provides a range of chart types to visually depict your data. With its intuitive interface and built-in chart tools, you can quickly create appealing visual representations of your worksheet data.

Tableau is a powerful data visualization tool that allows you to create interactive and dynamic visualizations. It offers advanced features for creating dashboards, maps, and other complex visual representations of worksheet data.

Infogram is a user-friendly tool for creating infographics, charts, and maps. It provides a range of templates and customization options to easily transform your worksheet data into engaging visual content.

Benefits of Using Pictorial Representation

When it comes to presenting worksheet data, using pictorial representation can offer several benefits that can enhance understanding, highlight key trends, simplify complex information, and engage the audience.

Pictorial representation such as graphs, charts, and diagrams can make it easier for individuals to comprehend the data presented. Visualizing the data can help in clarifying the information and making it more accessible.

By using visual representations, it becomes easier to identify trends and patterns within the data. Whether it's a fluctuation in sales over time or a correlation between different variables, pictorial representation can make these insights more apparent.

For datasets that contain complex information, using visuals can simplify the presentation of the data. Instead of overwhelming the audience with raw numbers and figures, creating a visual representation can simplify the message and make it more digestible.

Visuals are inherently more engaging than plain text or tables of data. Pictorial representation can capture the audience's attention and make the information more memorable. This can be particularly effective when presenting to a diverse audience with varying levels of data literacy.

As we wrap up this discussion on the pictorial representation of worksheet data, it's important to emphasize the significance of using graphs and charts to visually represent data. Not only do they make complex data more understandable, but they also facilitate quick and easy analysis. I encourage all readers to incorporate various types of graphs, such as bar graphs, pie charts, and line graphs, in their data analysis to gain deeper insights into their data.

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Today is your last chance to enroll in the data visualization academy. this is where you totally change how you think about data., free class october 6: ✨ which viz is it ✨, how to build data visualizations in excel.

When I show people a dot plot, the first thing they say is “Cool, but how do I make that?” and this page has all your answers. From time to time I publish blog posts with step-by-step directions on how to make amazing visualizations right inside Excel and I’ve collected those instructions for you right here.

You’ll find dozens and dozens more chart choices with updated instructions on how to make them – AND my Quantitative Chart Chooser – in my Data Visualization Academy .

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Vertical dumbbells, overlapping bars, diverging stacked bar, benchmark line, back to back, bullet chart, sparklines & indicators, small multiple lines, dot and bar, standard deviation, proportion plot.

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• Add or remove a secondary axis in a chart in Excel Article
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• Choose your chart using Quick Analysis Article
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• Use sparklines to show data trends Article

Use sparklines to show data trends

A sparkline is a tiny chart in a worksheet cell that provides a visual representation of data. Use sparklines to show trends in a series of values, such as seasonal increases or decreases, economic cycles, or to highlight maximum and minimum values. Position a sparkline near its data for greatest impact.

Add a Sparkline

Select a blank cell at the end of a row of data.

Select Insert and pick Sparkline type, like Line , or Column .

Select cells in the row and OK in menu.

More rows of data? Drag handle to add a Sparkline for each row.

Format a Sparkline chart

Select the Sparkline chart.

Select Sparkline  and then select an option.

Select Line , Column , or Win/Loss to change the chart type.

Check Markers to highlight individual values in the Sparkline chart.

Select a Style for the Sparkline.

Select Sparkline Color and the color.

Select Sparkline Color > Weight to select the width of the Sparkline.

Select Marker Color to change the color of the markers.

If the data has positive and negative values, select Axis to show the axis.

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Creating Venn Diagrams With Excel Data In Excel

Key takeaway:.

• Venn diagrams in Excel provide a visual representation of data overlap, making it easy for viewers to understand complex relationships between data sets.
• Before creating a Venn diagram, it is important to prepare the Excel data by sorting it and removing duplicates.
• Excel offers two methods for creating Venn diagrams: inserting pre-made diagrams from SmartArt or creating the diagram from scratch using shapes. Once created, the diagram can be customized with colors and labels to further enhance its visual impact.

Do you need visuals to represent your data in Excel? Learn how to easily create Venn diagrams with Excel data to effectively communicate your data’s complexity!

Preparation of Excel Data for Venn Diagram

Need to get your Excel data ready for Venn diagrams ? Solution: sort and remove duplicates . Sorting the data organizes it in a logical way, so you can use it to make the diagram. Eliminating duplicates guarantees the diagram is accurate.

Sorting Data in Excel

When it comes to handling data in Excel, one essential task is arranging the information in a particular order that suits the purpose of analysis. This process involves categorizing and sorting data based on several criteria.

To sort data in Excel, start by highlighting the entire dataset you wish to sort. Then navigate to the “Data” tab on Excel’s toolbar and select “Sort.” Afterward, choose the category or criterion you want to use for sorting the data and indicate if it should be sorted in ascending or descending order.

Organizing Data for Analysis in Excel: Sort & Categorize Efficiently

To demonstrate sorting data in Excel differently, we can create a table with rows, columns, and carefully selected data. For instance, let’s take a table that lists different brands’ sales for clothing articles across various stores . The rows will represent each store location while the columns list each brand’s sales figures. After this step, you can select any criterion such as brand name or sales volume and order them in ascending/descending values accordingly.

When sorting data in Excel, ensure that each column has relevant content that aligns with your objective. If a column contains inconsistent data types like dates and text strings, it may yield unreliable results when sorted out of sequence.

Don’t risk incorrect analysis due to disorganized datasets – sort your information meticulously using appropriate strategies! Consistent sorting methodology guarantees accurate conclusions from your analysis outputs.

Looks like Excel is about to rid your data of the ‘copy cats’ with its handy ‘Removing Duplicates’ feature.

Removing Duplicates

When it comes to eliminating repetitive values in Excel data, the process is called ‘data deduplication.’ This step is crucial as it helps avoid calculation errors and facilitates the creation of accurate visualizations. Below are some key points to consider during this process:

• Data deduplication can be accessed by selecting an area of data, clicking on the ‘Data’ tab in Excel’s toolbar & selecting the ‘Remove Duplicates’ option.
• Excel identifies real duplicates based on multiple criteria such as whole rows or specific columns.
• After identifying and removing duplicates, Excel displays a message indicating how many duplicate records were found and eliminated from the selected data set.
• If a dataset contains more than one field with different variations of the same values (e.g., abbreviation & full name), editing might be required before deduplication.
• The ‘Highlight Duplicate’ condition under Excel’s ‘Conditional Formatting’ rules allows users to identify duplicates visually; thus, providing another way to remove redundant values from the data set.

It’s important to note that removing duplicates should be performed only after verifying that they are genuinely identical records that offer nothing unique. This approach will help retain useful information and aspects that contribute value to your analysis.

When cleaning large datasets manually doesn’t seem practical or feasible for your intended purpose, there are other options available such as implementing a programming language like Python, which offers powerful libraries specifically for cleaning up structured data.

By adhering to these tips while removing duplicates from your excel worksheets provides cleaner datasets resulting in precise visualisations. Excel isn’t just for boring number crunching, it’s also a Venn diagram creating machine!

Creating Venn Diagram in Excel

Efficiently create Venn Diagrams in Excel by using the ‘Creating Venn Diagrams in Excel’ section. Turn your Excel data into rich and meaningful diagrams. There are two sub-sections: ‘Inserting Venn Diagrams from SmartArt’ and ‘Creating Venn Diagrams from Scratch using Shapes’ . These solutions will help you make compelling Venn Diagrams in Excel.

Inserting Venn Diagrams from SmartArt

To insert Venn diagrams from SmartArt in Excel, follow these simple steps:

• Open your Excel worksheet and click on the ‘Insert’ tab.
• Click on the ‘SmartArt’ option to open the gallery of SmartArt graphics.
• In the left panel, select ‘Relationship’ , and then choose a Venn diagram style that you prefer.
• After selecting your preferred Venn diagram style, click ‘OK’ to complete.

It’s essential to note that there are other ways of inserting Venn diagrams in Excel, like using third-party add-ins or manually creating them using shapes and objects.

Pro Tip: Using SmartArt is a quick and convenient way of creating Venn diagrams in Excel as it streamlines the process.

Shape up your Venn diagram game with these tips for creating diagrams from scratch in Excel.

Creating Venn Diagrams from Scratch using Shapes

To create a Venn Diagram from scratch using shapes, you can follow these simple steps:

• Open a blank worksheet in Excel.
• Insert three circles of equal size using the Shape tool under the Insert tab .
• Align and overlap the circles to create a Venn diagram.
• Finally, label the sections with appropriate text and adjust the color and font as per your preference.

It’s essential to note that creating a Venn diagram allows you to represent data more visually and effectively compared to traditional charts or tables. You may use different colors or shading techniques to highlight distinctions between individual groups and overlapping regions. The resulting graphic represents both similarities and differences information that can be useful for analysis.

It is crucial always to adhere to best practices when designing any visual representation of data in Excel or other tools . These include simplifying concepts through clear labeling and easy-to-read formatting, ensuring accuracy by verifying all inputs are correct before producing output graphics. Additionally, consider using images sparingly and appropriately; too many visuals distractions detract from critical details in data presentations.

Overall, following these simple steps will help you create beautiful Venn diagrams that communicate information quickly while also being aesthetically pleasing for clients or colleagues alike without relying on external tools such as Microsoft Visio or Adobe Illustrator. Why settle for a basic Venn diagram when you can add some flair to it? Customize like a boss in Excel.

Customizing Venn Diagram in Excel

Customize your Venn diagram in Excel using solutions from the ‘Customizing Venn Diagram in Excel’ section. Change colors and shapes of the Venn Diagram, or add labels to it. These sub-sections will help you to make your diagram look beautiful and more understandable.

Changing colors and shapes of the Venn Diagram

Venn Diagrams provide a unique way of visualizing data. By changing their colors and shapes, the representation becomes more intuitive and useful for interpretation.

Follow these four simple steps to change the color and shape of your Venn Diagrams:

• Click on the ‘Format’ tab after selecting your Venn Diagram in Microsoft Excel.
• Choose various options for color like gradient fills, solid fills or choose 3-D effects instantly .
• You can change the border styles, width and transparency too.
• Experiment with different styles and choose what suits best to the data you’re presenting.

It’s important not to overdo changes in colors as it can lead to misinterpretation by cluttering the image. Rather go with a simple representation that highlights key differences in mutual sets.

Avoid using bright colors that make sections of data look imbalanced in terms of comparison . Stick to a neutral palette that doesn’t overwhelm the diagram.

Don’t miss out on this opportunity to customize your Venn Diagrams accordingly. Make sure you employ this interesting feature while presenting data next time.

Labeling your Venn diagram is like putting name tags on awkward party guests – it’s necessary, but can lead to some unexpected combinations.

Adding Labels to the Venn Diagram

To Enhance Venn Diagrams with Labels

To improve the Venn diagram, adding labels is significant. It can help to provide detailed information about overlapping areas and increase the readability of the diagram.

Consider creating a table with three columns: set A, set B, and overlapping regions. Fill each row with relevant data such as numerical values or unique labels. Then paste it into the Venn diagram.

Moreover, using contrasting colors for labels and finding appropriate font sizes is vital to increase visibility and clarity of each label in the diagram.

By adding informative labels to the Venn diagram, viewers will be provided with a better understanding of how sets interact and overlap. This can lead to improved decision-making skills when analyzing data and discovering new insights.

Five Facts About Creating Venn Diagrams with Excel Data in Excel:

• ✅ Venn diagrams are used to compare and contrast sets of data. (Source: Excel Campus)
• ✅ Excel has a built-in tool for creating Venn diagrams using two or three data sets. (Source: Microsoft)
• ✅ Venn diagrams can help identify commonalities and differences between data sets, making them useful for data analysis. (Source: Techwalla)
• ✅ Venn diagrams can be customized with colors, labels, and other options to enhance their visual impact. (Source: BetterCloud)
• ✅ Venn diagrams can be shared and collaborated on with others using Excel Online. (Source: Microsoft)

FAQs about Creating Venn Diagrams With Excel Data In Excel

How do i create a venn diagram using excel data in excel.

To create a Venn diagram using Excel data in Excel, you need to follow these steps:

• Select the data you want to use to create the Venn diagram
• Go to the “Insert” tab and click on “Insert Statistic Chart”
• Select “Venn”
• Your Venn diagram will appear on the worksheet and can then be customized as needed.

Can I customize my Venn diagram using Excel data in Excel?

Yes, you can customize your Venn diagram using Excel data in Excel. You can change the colors, add labels, and adjust the formatting as needed.

What is a Venn diagram?

A Venn diagram is a type of chart that uses circles to show the relationships between sets of data. The circles overlap to indicate where the data sets have things in common. They are often used in decision-making, statistics, and data analysis.

What types of data can be used to create a Venn diagram in Excel?

Any type of data that can be represented as sets can be used to create a Venn diagram in Excel. This includes numerical data, categorical data, and textual data.

Do I need any special software to create Venn diagrams with Excel data in Excel?

No, you do not need any special software to create Venn diagrams with Excel data in Excel. Excel has built-in tools that allow you to create these types of diagrams easily.

What are some common uses for Venn diagrams?

Venn diagrams are commonly used to illustrate concepts in classrooms, scientific research, and marketing. They are also used in problem-solving, decision-making, and business analysis. Venn diagrams are useful for showing relationships between data sets and for identifying similarities and differences between them.

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Data Visualization in Excel

Data Visualization is the representation of data in a graphical format. It makes the data easier to understand. Data Visualization can be done using tools like Tableau, Google charts, DataWrapper, and many more. Excel is a spreadsheet that is used for data organization and data visualization as well. In this article, let’s understand Data Visualization in Excel.

Excel provides various types of charts like Column charts, Bar charts, Pie charts, Linecharts, Area charts, Scatter charts, Surface charts, and much more.

Steps for visualizing data in Excel:

• Open the Excel Spreadsheet and enter the data or select the data you want to visualize.
• Click on the Insert tab and select the chart from the list of charts available or the shortcut key for creating chart is by simply selecting a cell in the Excel data and press the F11 function key .

• A chart with the data entered in the excel sheet is obtained.
• You can design and style your chart with different types of styles and colors by selecting the design tab.
• In Excel 2010, the design tab option is visible by clicking on the chart.

The Excel data is as follows:

The column chart obtained for the data by following the above steps:

When excel data contains multiple columns and if you want to make a chart for only a few columns, then select the columns required for making the chart and press the ‘F11’ function key or click on the Insert tab and select the chart from the list of charts available.

We can also select the required data columns by doing right-click on the chart and click on the ‘ select data ‘ option. Now, data can be added or removed for making the chart.

For swapping rows and columns in the chart, use the ‘S witch Row/Column ‘ option available in the design tab.

We can also make different types of charts for the same spreadsheet data by clicking on the ‘ Change Chart Type’ option in the Design tab .

To make your chart more clear, use the ‘Layout’ tab. In this tab, you can more changes to your chart like editing the chart title, adding labels to your chart, adding a legend, and adding horizontal or vertical grid lines.

Example 3: Formatting Chart Area

To format the chart area, right-click on the chart and select the option ‘ Format chart Area ‘.

The format chart area provides various options for formatting the chart like Filling the chart with patterns and solid colors, Border colors, Styles for borders, the shadow effect for your chart, and many more. Formatting makes the chart look more attractive and colorful.

Example 4: Creating Sparklines

Sparklines in Excel are small charts that fit in the data cells of the excel sheets.

Steps for Creating Spark Lines:

• Select the Excel data range for sparklines as shown in the below figure.
• Click on Sparklines in the Insert tab and select any one of the three sparklines.

• Add the Location Range and Data Range for the creation of sparklines and click ok.

Finally, the F, G, H columns are displayed with the line, column, and Win/loss sparklines.

We can also color these sparklines by the Design tab as shown below:

 We can Mark data points and also change Sparkline Color.

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How to Make a Box Plot in Excel: A Step-by-Step Guide

Published: August 2, 2024 - 9 min read

Ever wondered how to quickly grasp your data’s spread and outliers? Box plots in Excel can help. This guide shows you how to create these handy charts step-by-step.

You’ll learn to set up your data, use Excel’s features, and customize your box plot to reveal key insights about your dataset.

Box Plot 101: Understanding the Basics

A box plot, also known as a box-and-whisker diagram, is a statistical graph that provides a visual representation of a dataset’s distribution. It displays a five-number summary of the dataset: the minimum value, the first quartile (Q1), the median, the third quartile (Q3), and the maximum value.

The key components of a box plot are:

• Whiskers : The lines extending from the box that indicate the minimum and maximum values, excluding outliers.
• Box : The rectangular area that represents the middle 50% of the data, with the median line dividing the box.
• Outliers : Data points that fall outside the whiskers, typically represented as individual points.

Box plots are particularly useful for identifying the central tendency, spread, and skewness of a dataset. They allow you to quickly assess the distribution of your data, identify potential outliers, and compare multiple datasets side by side.

Step-by-Step Guide: How to Make a Box Plot in Excel

Creating a box plot in Excel is a straightforward process. Follow these steps to get started:

• Prepare your data : Ensure that your data is organized in a single column or row, with each data point in a separate cell.
• Select the data you want to enter on the box plot.

• Click ‘Insert’ in the Excel ribbon and navigate to ‘ Statistical Chart ’ in the array.

• Select the ‘ Box and Whisker ’ option in the chart dropdown

• The chart automatically shows on the Excel page

• Customize the plot (optional) : You can further customize your box plot by adjusting the chart title, axis labels, and other visual elements.

• Create the box plot : Click “OK” to generate the box plot in a new worksheet.

That’s it! You’ve successfully created a box plot in Excel. Remember, you can further refine and customize the plot to suit your specific needs and preferences.

Video Tutorial

Interpreting Your Box Plot: What the Data Tells You

Box plots are a powerful tool for visualizing the distribution of your data. By understanding how to read and interpret the different components of a box plot, you can gain valuable insights about your dataset.

The key elements of a box plot include:

• Median : The middle value, represented by the horizontal line in the center of the box.
• Interquartile Range (IQR) : The range between the 25th and 75th percentiles, shown by the box itself.
• Whiskers : The lines extending from the box that represent the minimum and maximum values, excluding outliers.
• Outliers : Data points that fall outside the whiskers, typically more than 1.5 times the IQR above the 75th percentile or below the 25th percentile.

A symmetrical box plot with the median line in the center of the box indicates a normal distribution. Skewed distributions will have the median line shifted towards one side of the box. Wider boxes represent greater variability in the data, while narrower boxes indicate less dispersion.

By analyzing the shape and positioning of the box plot, you can quickly identify key characteristics of your data, such as:

• Central Tendency : The median value provides a measure of the central tendency of your data.
• Spread : The size of the IQR and the length of the whiskers indicate the overall spread or variability of the data.
• Symmetry : The symmetry (or lack thereof) of the box plot can reveal the underlying distribution of the data.
• Outliers : Identifying outliers can help you detect anomalies or data points that may require further investigation.

Understanding how to interpret these box plot elements will allow you to draw meaningful insights from your data and make more informed decisions.

Common Mistakes and Troubleshooting Tips for Box Plots in Excel

While creating box plots in Excel is generally straightforward, there are a few common pitfalls to watch out for:

• Incorrect Data Range : Ensure that you have selected the correct data range for your box plot. Double-check that you haven’t accidentally included or excluded any relevant data points.
• Missing Outliers : If your box plot is not displaying any outliers, check that your data does not contain any extreme values that fall outside the whisker range. Adjust the whisker settings or the outlier threshold if necessary.
• Overlapping Boxes : When creating multiple box plots in the same chart, make sure to adjust the spacing between the boxes to ensure they are clearly visible and don’t overlap.
• Incorrect Axis Scaling : Verify that the axis scaling is appropriate for your data. Adjust the minimum and maximum values, as well as the tick intervals, to ensure the box plot is displayed clearly.
• Incorrect Sorting : If your data is not sorted, the box plot may not accurately represent the distribution. Consider sorting your data before creating the box plot.
• Incorrect Grouping : Ensure that you have properly grouped your data if you are creating multiple box plots for different categories or variables.

To troubleshoot these issues, try the following steps:

• Inspect Your Data : Carefully review your data to identify any potential errors or outliers that may be affecting the box plot.
• Experiment with Settings : Adjust the box plot settings in Excel, such as the whisker length, outlier threshold, and spacing between boxes, to see how they impact the visualization.
• Consult Excel Help : Refer to Excel’s built-in help resources or online tutorials for guidance on properly creating and customizing box plots.
• Seek Community Support : If you’re still struggling, consider reaching out to Excel user forums or communities for additional troubleshooting assistance.

By addressing these common issues, you can ensure that your box plots accurately represent the distribution of your data and provide meaningful insights.

Comparing Tools: Box Plots in Excel vs. Google Sheets vs. R

While Excel is a popular choice for creating box plots, it’s not the only option available. Let’s explore the pros and cons of using Excel, Google Sheets, and the R programming language for this task:

• Pros : Widely accessible, easy to use, and integrated with other Microsoft Office tools.
• Cons : Limited customization options, may struggle with large datasets, and can be prone to formatting issues.

Google Sheets :

• Pros : Cloud-based, collaborative, and often more user-friendly than Excel for basic data visualization.
• Cons : Fewer advanced charting options, limited functionality compared to Excel, and may not handle large datasets as well.
• Pros : Highly customizable, powerful for advanced data analysis and visualization, and can handle large datasets with ease.
• Cons : Steeper learning curve, requires programming knowledge, and may not be as accessible for non-technical users.

Depending on your specific needs and preferences, you may find one tool more suitable than the others. For example, if you’re working with a small to medium-sized dataset and need a quick and easy way to create box plots, Excel or Google Sheets may be the better choice. However, if you require more advanced customization options or need to handle large datasets, R may be the more appropriate tool.

Regardless of the platform you choose, the key is to select the one that best fits your workflow and provides the functionality you need to effectively analyze and interpret your data.

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Real-World Examples: Using Box Plots in Data Analysis

Box plots are a versatile data visualization tool that can be applied in a wide range of industries and scenarios. Here are a few real-world examples of how box plots can be used:

Finance : In the financial sector, box plots can be used to analyze stock price distributions, compare the performance of different investment portfolios, or identify outliers in financial data.

Healthcare : In the healthcare industry, box plots can be used to visualize the distribution of patient outcomes, such as hospital stay durations or medication dosages, to identify potential areas for improvement.

Marketing : Box plots can be used in marketing to analyze the distribution of customer satisfaction scores, website traffic data, or campaign performance metrics, helping identify trends and outliers.

Manufacturing : In manufacturing, box plots can be used to monitor the quality of production processes, identify sources of variability, and detect potential issues in the manufacturing workflow.

Education : Box plots can be used in the education sector to analyze student test scores, compare the performance of different schools or classrooms, and identify areas where additional support may be needed.

By incorporating real-world examples and case studies, you can help readers better understand the practical applications of box plots and how they can be used to gain valuable insights from their own data.

Advanced Tips: Enhancing Your Box Plots in Excel

While the basic box plot in Excel is a powerful tool, there are several ways you can enhance your visualizations to make them more informative and visually appealing:

• Add Trend Lines : Overlay trend lines on your box plot to identify patterns or trends in the data over time. This can be particularly useful when analyzing data series with multiple box plots.
• Combine with Other Charts : Combine your box plot with other chart types, such as scatter plots or line charts, to provide a more comprehensive view of your data and the relationships between different variables.
• Handle Large Datasets : When working with large datasets, consider creating small multiples (also known as trellis plots) to display multiple box plots in a grid-like layout. This can help you identify patterns and trends more easily.
• Customize Appearance : Experiment with different color schemes, font styles, and formatting options to make your box plots more visually appealing and aligned with your brand or design guidelines.
• Add Annotations : Enhance your box plots by adding annotations, such as labels, data points, or explanatory text, to provide additional context and insights to your audience.
• Integrate with Other Tools : Leverage the power of Excel by integrating your box plots with other tools, such as Power BI or Tableau, to create more sophisticated data visualizations and dashboards.

By incorporating these advanced techniques, you can create box plots that not only provide valuable insights but also engage your audience and elevate the overall quality of your data analysis.

Take Your Data Visualization to the Next Level

Box plots in Excel offer a clear way to show data distribution. By following the steps in this guide, you can now create your own box plots to analyze datasets. Remember to organize your data properly and use Excel’s Chart Tools to refine your plots.

For more advanced data visualization, consider using real-time data connections. Coefficient can help you automate your Excel reporting and keep your box plots up-to-date.

Want to learn more? Start using Coefficient to connect live data to your Excel sheets and create dynamic box plots.

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Excel: Charts and Data Visualization

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• 1. Multiple Choice Edit 30 seconds 1 pt A visual representation of worksheet data. Column Data Chart Legend
• 2. Multiple Choice Edit 30 seconds 1 pt Part of a pie chart that represents one value from the series. axis data slice chart
• 3. Multiple Choice Edit 30 seconds 1 pt Data graphed as slices of a circular area is a  bar chart scatter plot pie chart column chart
• 4. Multiple Choice Edit 30 seconds 1 pt The part of the chart area that displays data. legend axis series plot area
• 5. Multiple Choice Edit 30 seconds 1 pt Corresponds to the category labels in a pie chart and series names in other charts. Plot area Legend Gridelines Slice
• 6. Multiple Choice Edit 30 seconds 1 pt This describes what is charted. It can be placed above or below the chart. Chart title chart area bar chart pie chart
• 7. Multiple Choice Edit 30 seconds 1 pt Once a type of graph is chosen, it can not be changed. True False

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The Importance of Excel in Business

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Microsoft (MSFT) Excel is a spreadsheet software application used to store, organize, and analyze data. It was released in 1985 and has grown to become arguably the most important computer program in workplaces around the world. In business, any function in any industry can benefit from those with strong Excel knowledge—and gaining that knowledge is easy with the help of an online Excel course .

Excel is a powerful tool that has become entrenched in business processes worldwide—whether for analyzing stocks or issuers, budgeting, or organizing client sales lists.

Key Takeaways

• Microsoft Excel is a spreadsheet application used to manipulate stored data.
• Finance and accounting professionals choose Excel for its complex analytical and computing features.
• Microsoft Excel enables users to identify trends and organize and sort data into meaningful categories.
• Excel also performs Human Resources functions, such as sorting worked hours and organizing employee profiles and expenses, which help businesses better understand the structure and activities of their workforce.
• Pivot tables summarize data from a worksheet into a chart.

Financial services and financial accounting are the areas of finance that rely on and benefit from Excel spreadsheets the most. In the 1970s and early 1980s, financial analysts would spend weeks running advanced formulas either manually or (beginning in 1983) on programs like Lotus 1-2-3. Now, you can perform complex modeling in minutes with Excel.

Walk through the finance or accounting department of any major corporate office, and you will see computer screens filled with Excel spreadsheets crunching numbers, outlining financial results, and creating budgets, forecasts , and plans used to make major business decisions.

Most users know that Excel can add, subtract, multiply, and divide, but it can do much more with advanced IF functions when coupled with VLOOKUP, INDEX-MATCH-MATCH, and pivot tables.

While marketing and product professionals look to their finance teams to do the heavy lifting for financial analysis, using spreadsheets to list customer and sales targets can help you manage your  salesforce and plan future marketing strategies based on past results.

Using a pivot table, users can quickly and easily summarize customer and sales data by category with a quick drag-and-drop.

While database systems like Oracle ( ORCL ), SAP ( SAP ), and Quickbooks ( INTU ) can be used to manage payroll and employee information, exporting that data into Excel allows users to discover trends, summarize expenses and hours by pay period, month, or year, and better understand how their workforce is spread out by function or pay level.

In Excel, all dates prior to March 1, 1900 are incorrect due to an irreparable error.

HR professionals can use Excel to take a giant spreadsheet full of employee data and understand exactly where the costs are coming from and how to best plan and control them for the future.

Why Is Excel an Important Tool?

Using Excel for business has almost no limits for applications. Here are some examples:

• When planning a team outing to a baseball game, you can use Excel to track the RSVP list and costs.
• Excel creates revenue growth models for new products based on new customer forecasts.
• When planning an editorial calendar for a website, you can list out dates and topics in a spreadsheet.
• When creating a budget for a small product, you can list expense categories in a spreadsheet, update it monthly and create a chart to show how close the product is to budget across each category.
• You can calculate customer discounts based on monthly purchase volume by product.
• Users can summarize customer revenue by product to find areas where to build a stronger customer relationships.
• Use complex calculation methods, like Sharpe ratios .

Excel was the first software application to use a toolbar.

What Is Microsoft Excel and How Is It Used in Business?

Microsoft Excel is a computer software program that uses spreadsheets to organize and analyze stored data. Businesses use Excel for budgeting, analysis, forecasting, spotting trends, reporting, and more.

How Can You Create a Business Budget in Excel?

Excel is outfitted with many templates for personal and business uses. The simplest way to create a business budget is to select a budget template that's most appropriate for your business. Most contain labels for input, formulas for analysis, and other worksheets for the most recognized budgeting categories, such as income, personnel expenses, and operating expenses. Users can also manually create their budget, inputting their labels, tables, and formulas.

How Do You Track Business Expenses in Excel?

Excel contains templates for tracking expenses. One of the most commonly used is the Expense Report template with categories for specific business-related expenses. Data is organized into columns with column headers or labels that can be changed or deleted if not fitting for the user's business. The template is formatted for ease of use, allowing the user to input data into designated cells. Users can also create their expense reports manually.

Excel is not going anywhere, and businesses will continue to use Excel as a primary tool for diverse functions and applications ranging from IT projects to company picnics.

Working knowledge of Excel is vital for most office-based professionals today, and stronger Excel skills can open the door to promotion and leadership opportunities. Excel is a powerful tool but cannot function alone. It takes a savvy computer user to take advantage of everything Excel has to offer to provide the best results for their company.

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Excel Sample Data (Free Download 13 Sample Datasets)

Project Management Sample Data

A project management sample data is suitable for various types of data filtering, analyzing, and visualizing. Here are the variables that we have included in the sample data:

• Project Name
• Assigned to
• Days Required

Here is a preview of the project management dataset:

Download the Sample Workbook

Inventory Records Sample Data in Excel

Inventory management records consist of product and stock information. In our sample dataset, we have included the following fields:

• Product Name
• Opening Stock
• Purchase/Stock-in
• Number of Units Sold
• Hand-in-stock
• Cost Price Per Unit
• Cost Price Total

Here is a preview of the inventory records sample data:

Call Center Customer Satisfaction Data

Call centers deal with customer service and receive various types of feedback from customers. In our Call Center Customer Satisfaction data, we have included the following fields:

• Customer Name
• Call Timestamp
• Response Time
• Call Duration
• Call Center

Here is a preview of our sample data:

Supermarket Sales Sample Data in Excel

Supermarket sales sample data is a popular dataset for learning and practicing your Excel skills. Here is the list of variables we have included in our supermarket sales sample data:

• Retail Price
• Order Quantity

Here is a preview of the sample supermarket sales data in Excel:

Download the Practice Workbook

Employee Management Data

Employee management data contains information on all employees in an organization. In our sample employee management data in Excel, we have listed the following variables:

• Employee ID
• Designation
• Annual Salary

Here is a preview of the employee management data:

Technological Product Sample Data

Any technological product information requires various specifications. In our sample dataset, we have listed the following specifications:

• Country of Origin
• Release Date

The following image shows a preview of our sample technological product dataset:

Engineering and Manufacturing Sample Data

Engineered or manufactured products also require various specifications. Here is the list of variables we have included in our sample engineering and manufacturing sample data:

• Manufacturer
• Stock Quantity

Here is a preview of the sample dataset:

Students Marksheet Sample Data in Excel

A student mark sheet contains the student identifiers and marks in various subjects. In our sample students marksheet dataset, we have listed the following variables:

• Marks in Mathematics
• Marks in Physics
• Marks in Chemistry

Here is a preview of the sample student marksheet dataset:

2022 FIFA World Cup Performance Data

In our sample dataset, we have listed the information of each player from the World Cup-winning Argentina team. Here is the list of variables we have included:

• Player Name
• Jersey Number
• Appearances
• Goals Scored
• Assists Provided
• Dribbles per 90 Min
• Interceptions per 90 Min
• Tackles per 90 Min
• Total Duels Won per 90 Min

You can preview the sample dataset in the following image:

Tokyo Olympic Data

This sample dataset contains the team names, number of Gold, Silver, Bronze, and total medals, and ranking of teams (based on gold medal and total medal count) in the Tokyo Olympics. Here is a preview of the sample dataset:

Healthcare Insurance Sample Data in Excel

The price of healthcare insurance depends on various factors such as current age, BMI, smoking habits,  etc. In our sample healthcare insurance dataset, we have listed the following variables:

• Smoking Status
• Insurance Price

Travel Destination Distance Data in Excel

While deciding on a travel destination, we need to take the distance, available travel modes, travel duration, etc. factors into consideration. In our sample travel destination dataset, we have listed the following variables:

• Source City
• Source Latitude
• Source Longitude
• Destination City
• Destination Latitude
• Destination Longitude
• Distance (in km)
• Distance (in mile)
• Travel Mode

Netflix Movies Sample Data

The movie dataset provided in this section contains the following variables:

• IMDb Rating

You can preview the dataset in the image below:

Excel Sample Data: Knowledge Hub

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Seemanto Saha graduated in Industrial and Production Engineering from Bangladesh University of Engineering and Technology. He has been with ExcelDemy for a year, where he wrote 40+ articles and reviewed 50+ articles. He has also worked on the ExcelDemy Forum and solved 50+ user problems. Currently, he is working as a team leader for ExcelDemy. His role is to guide his team to write reader-friendly content. His interests are Advanced Excel, Data Analysis, Charts & Dashboards, Power Query,... Read Full Bio

Thanks for the DATA SETS !

Hello Margit ,

You are most welcome.

Regards ExcelDemy

Thank you so much

Hello Usama Jamil ,

I needed Oil parameters Offshore Foundation design 2015 excel sheet access

Hello Ameer Ahmed ,

We don’t have any dataset you asked for and your question is not clear enough. Our datasets are given in the article.

Thank you so much for the data sets.

Hello Gaurav,

Where are the solutions to these problems? Would like to check against what I did

Hello Cynthia Satterwhite ,

Neither any problem nor any solution are given. These dataset are given to practice by yourself.

Wow Great Readymade Excel Sheets, Can You provide any excel sheet to maintain monthly calibration details for internal lab

Hello Karunesh Pandey ,

As calibration details varies with lab type we can provide you the criteria. You can fill out your information and edit the list.

nice work thank you ! I need dataset for students, subjects, teachers and departments hope U help.

Hello Fulad

Thanks for your compliment! As you requested, you can use the following dataset, which contains data with your mentioned fields:

You can download the workbook from the following link:

DOWNLOAD WORKBOOK

I hope you have found the dataset you were looking for; good luck.

Regards Lutfor Rahman Shimanto ExcelDemy

ExcelDemy good work. It is difficult to get excel datasets for predictive analysis. please can I get a comprehensive CRM (customer online journey) or Supply chain dataset (Procurement-Logistics- inventory-sales) for retail industry.

Hello Amara ,

Here I’m attaching a sample dataset for CRM and Supply chain. You can modify this dataset based on your requirements. Dataset of CRM: CRM Dataset.xlsx Dataset of Supply Chain: Supply Chain Dataset.xlsx

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How to Find the Equation of a Trendline in Excel

• / How to Find the Equation of a Trendline in Excel

Adding a trendline to a chart in Excel is a powerful way to analyze data trends and make predictions. The trendline equation provides the mathematical representation of the data’s trend, which can be useful for forecasting and understanding relationships within the data.

Imagine you are analyzing sales data to predict future performance or studying the relationships between advertising spend and revenue. Finding the equation of a trendline in Excel can help you understand the underlying pattern in your data and make informed decisions based on that pattern. Whether you are a student, data analyst, or business professional, mastering this skill can significantly enhance your data analysis capabilities.

Let’s explore how to find the equation of a trendline in Excel with a detailed step-by-step process.

Step-by-Step Guide to Find the Equation of a Trendline in Excel

Step 1: create a chart, input your data :.

• Enter your data into an Excel worksheet. Ensure you have at least two columns of data that you want to analyze (e.g., time and sales).

Select Your Data :

• Highlight the data range you want to use for the chart.

Insert a Chart :

• Go to the “Insert” tab on the Ribbon.
• Choose the type of chart that best represents your data. Common options include Line, Scatter, or Column charts.

Step 2: Add a Trendline

Select the chart :.

• Click on the chart to activate it.

Add Trendline :

• Click on the “Chart Elements” button (the plus icon) next to the chart.
• Check the “Trendline” box. Excel will automatically add a linear trendline.

Customize the Trendline :

• Click the arrow next to “Trendline” to access more options.
• Select “More Options” to open the “Format Trendline” pane.

Step 3: Display the Equation on the Chart

Format trendline pane :.

• In the “Format Trendline” pane, you will see several trendline options such as Linear, Exponential, Logarithmic, Polynomial, Power, and Moving Average.

Choose the Trendline Type :

• Select the appropriate trendline type based on your data. For simplicity, we’ll use a Linear trendline.

Display Equation :

• Scroll down in the “Format Trendline” pane and check the “Display Equation on chart” box.
• The equation of the trendline will appear on the chart.

Step 4: Interpret the Equation

Understanding the equation :.

• y is the dependent variable.
• m is the slope of the line.
• x is the independent variable.
• b is the y-intercept.

Use the Equation for Predictions :

• The equation can be used to make predictions by substituting the desired value of x to find y.

Pros and Cons

• Simplifies Data Analysis : Trendlines and their equations simplify the analysis by highlighting trends and patterns.
• Predictive Power : Equations can be used for forecasting future values based on existing data.
• Visual Appeal : Trendlines enhance the visual appeal of charts, making data trends more understandable.
• Assumptions : Trendlines assume that the data follows a specific pattern (linear, exponential, etc.), which may not always be true.
• Overfitting : In some cases, complex trendline equations (like higher-order polynomials) can overfit the data, leading to misleading conclusions.
• Data Quality : The accuracy of the trendline equation depends on the quality and quantity of the data.

Importance of Trendline Equations

Data insight :.

• Understanding Relationships : Trendline equations help in understanding the relationship between variables, revealing how changes in one variable affect another.
• Identifying Trends : Equations highlight trends over time, making it easier to identify growth, decline, or cyclical patterns.

Forecasting :

• Predicting Future Values : With the trendline equation, you can predict future values by plugging in new data points, which is valuable for planning and strategy.

Simplifying Complex Data :

• Mathematical Representation : Trendline equations provide a simple mathematical representation of complex data sets, making analysis more manageable.

Conclusion:

• Finding the equation of a trendline in Excel is an essential skill for anyone involved in data analysis. It allows you to uncover patterns, make predictions, and present data in a visually appealing and easily understandable format. By following the steps outlined above, you can efficiently add and interpret trendline equations in your Excel charts. Understanding the significance, pros, and cons of trendline equations ensures you make informed decisions and leverage this powerful tool to its fullest potential.

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How to Convert Numbers to Text Fast in Excel

Learn to easily convert numbers to text in Excel. Explore TEXT function, custom formats, macros, and more... read more

#ez_toc_widget_sticky--1 .ez-toc-widget-sticky-container ul.ez-toc-widget-sticky-list li.active{ background-color: #ededed; } Steps To Follow

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Converting numbers to text in Excel can be essential for various reasons, such as maintaining formatting consistency, manipulating data, or ensuring compatibility with other applications. I’ve found that Excel offers several methods to achieve this, each with its unique advantages. Let me share with you the techniques I use to convert numbers to text in Excel, including functions, formatting options, and more.

Key Takeaways:

• Maintain Data Integrity : Converting numbers to text in Excel prevents issues like disappearing leading zeros and unwanted format changes, keeping data like ZIP codes and product codes accurate.
• Versatile Functions : Excel’s functions like TEXT , CONCATENATE , and TEXTJOIN make it easy to convert numbers to text for various data manipulations.
• Simple Methods : Use the TEXT function or combine numbers with an empty string using CONCATENATE or & for quick conversions.
• Preserve Formatting : Converting numbers to text ensures leading zeros in product codes and other data are preserved, avoiding confusion.
• Enhanced Compatibility : Converting numbers to text improves data compatibility across software and enhances report clarity and precision.

Table of Contents

Unveiling Excel’s Text Conversion Power

Why convert numbers to text.

In Excel, converting numbers to text is a routine yet powerful trick that addresses various data management needs. Maybe you’ve grappled with disappearing leading zeros in a list of phone numbers or despaired as Excel zealously changes product codes into something resembling a math problem. These pain points have led me to convert numbers to text.

When I do this, Excel stops tinkering with my data, keeping ZIP codes intact, fractions readable, and ensuring that identification numbers appear exactly as they should. This conversion is essential for accurate data representation, especially when preparing reports or importing and exporting data between different software.

The Transformation Ability of Excel Functions

Excel functions are nothing short of magicians when it comes to transforming data. They can take seemingly ordinary numbers and revamp them to serve a myriad of purposes. With just a few clicks, these functions allow me to achieve tasks ranging from simple conversions, like changing numbers to text, to complex data manipulations involving searches, summing based on conditions, and even sophisticated array operations.

They truly expand the realm of possibilities, making Excel an indispensable tool not just for data analysts, but for anyone who needs to manipulate and present data effectively.

Step-by-Step Guide for Quick Conversion

Method 1 – using the text function.

The TEXT function is a versatile tool for converting numbers to text while applying specific formatting. The syntax is:

TEXT(value, format_text)

• value : The number you want to convert.
• format_text : The format you want to apply.

If we want to convert the number 1234.56 to text with two decimal places:

=TEXT(1234.56, “0.00”)

The ISTEXT function in Excel is used to check whether a given value is text. It returns TRUE if the value is text and FALSE if it is not. text or not.

Method 2 – Using the CONCATENATE Function

The CONCATENATE function (or & operator) helps me convert numbers to text by combining them with an empty string.

To convert the number 1234 to text, I can use:

=CONCATENATE(A2, “”)

Or with the & operator:

=A2 & “”

Method 3 – Using the TEXTJOIN

For Excel 2016 and later versions, I’ve found TEXTJOIN function offers more flexible options for joining and converting numbers to text.

=TEXTJOIN(“”, TRUE, A2)

Real-World Scenarios and Solutions

Preserving leading zeroes in product codes.

When managing product codes, preserving leading zeroes is less about aesthetics and more about maintaining the unique identity of each item. Leading zeroes might seem insignificant, but in the world of inventory management, they play a crucial role in differentiating products. Lose them, and you’re in a whirlwind of confusion.

Thankfully, Excel comes to the rescue, empowering you with several methods to keep those zeroes intact. You could format the cells as ‘Text’ before entering data or apply the aforementioned TEXT function, ensuring every code retains its rightful form—zeros included. This meticulous attention to detail is what makes or breaks the seamless tracking and identification of products.

Converting Data for Compatibility and Reporting

Ensuring compatibility and precision in reports is a dance with data, where every step must be perfectly executed. When you convert data in Excel, particularly numbers to text, you’re essentially choreographing this dance to the tune of various systems’ requirements. It’s a vital step for interoperability, ensuring that when data waltzes from Excel to other programs, it retains its character—literally.

Additionally, reports flourish with clarity when figures are formatted correctly, making them more accessible and comprehensible to stakeholders. So whether you’re aiming to align cells in a report or make your data play nice with other applications, conversion is the key to harmonious data relations.

FAQ: Your Questions, Answered

How do i convert numbers to text in excel automatically.

To convert numbers to text automatically in Excel, you can pre-format the target cells as ‘Text’ before typing or pasting in the numbers. Alternatively, use the TEXT function by typing =TEXT(value, format_text) into a cell, where value is the number you want to convert and format_text specifies the number format.

What is the formula to convert a number to text?

The formula to convert a number to text in Excel is the TEXT function: =TEXT(B5,"0") . Replace “B5” with the cell containing the number you wish to convert. The quotes can contain a variety of formatting options such as “0” for a simple conversion while maintaining numerical value.

Can Numbers Be Converted to Words in Excel?

Excel doesn’t natively convert numbers to words, but you can add this functionality with a VBA macro function. By creating a custom SpellNumber function in Visual Basic for Applications, Excel can translate numbers into English words, perfect for financial reports or checks.

How Do I Prevent Excel from Changing Numbers to Scientific Notation?

To prevent Excel from changing large numbers to scientific notation, you can format the cells as ‘Text’ before inputting your data or use the ‘Number’ format with zero decimal places, ensuring Excel treats and displays the content exactly as entered.

Why convert text to numbers in Excel?

Converting text to numbers in Excel is critical when you want to crunch those digits. Say goodbye to error messages in your sum formulas and ditch the manual counting. Excel needs those numbers in number format to perform calculations, sort numerically, or pivot that data into insightful charts. It’s about making sure your spreadsheet is not just data-rich, but also ready to bow to your every analytical command.

John Michaloudis

John Michaloudis is a former accountant and finance analyst at General Electric, a Microsoft MVP since 2020, an Amazon #1 bestselling author of 4 Microsoft Excel books and teacher of Microsoft Excel & Office over at his flagship MyExcelOnline Academy Online Course .

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Data summarization using pivot in Google Sheet

Introduction

Pivot tables are powerful tools in Excel that enable users to summarise, analyse, and manipulate large datasets efficiently. Whether you’re a beginner or an advanced user, understanding pivot tables and their capabilities can significantly enhance your data analysis skills. This comprehensive guide will walk you through everything you need to know about data summarization using pivot tables, including detailed explanations of query functions and various pivot table functionalities.

Understanding Pivot Tables

What are Pivot Tables?

Pivot tables are interactive tables in Excel that allow you to summarise and analyse large datasets. They provide a flexible way to rearrange and aggregate data dynamically without complex formulas.

Key Benefits of Pivot Tables:

• Summarization: Quickly summarise large datasets into concise, meaningful reports.
• Analysis: Analyse data by different categories, such as product, region, or time.
• Visualisation: Create charts and graphs based on pivot table summaries for visual representation of data trends.

Creating a Pivot Table

Step-by-Step Guide to Creating a Pivot Table:

• Select Your Data: Highlight the dataset you want to analyse.

• Insert Pivot Table: Go to the Insert tab, click on PivotTable, and choose the data range.

• Configure Your Pivot Table: Drag fields into the Rows, Columns, Values, and Filters areas to organise and summarise your data.

Query Functions for Advanced Data Analysis

Using QUERY Function:

The QUERY function in Excel allows you to retrieve specific data from a dataset based on defined criteria, similar to SQL queries.

• Syntax: =QUERY(data, query, [headers])
• Example: =QUERY(A1:E100, “SELECT A, SUM(E) WHERE B = ‘Category 1’ GROUP BY A LABEL A ‘Product’, SUM(E) ‘Total Sales’”, TRUE)

Key Features of QUERY Function:

• Filtering: Retrieve data based on specific conditions using WHERE clause.
• Aggregation: Summarise data with SUM, COUNT, or other aggregate functions.
• Grouping: Group data by specific fields with GROUP BY clause.

Different Types of Pivot Table Functions

1. Summarising Data:

• Sum: Adds numeric values together.
• Count: Counts the number of entries in a field.
• Average: Calculates the average of numeric data.
• Min/Max: Finds the minimum or maximum value in a field.

2 . Calculated Fields and Items:

• Calculated Fields: Create new fields with custom formulas based on existing data.
• Calculated Items: Apply calculations within existing fields.

3. Sorting and Filtering:

• Sorting: Arrange data in ascending or descending order.
• Filtering: Display specific data subsets using filters.

4. Pivot Charts and Conditional Formatting:

• Pivot Charts: Create visual representations of pivot table data.
• Conditional Formatting: Highlight cells based on specified conditions for better data visualisation.

Advanced Pivot Table Techniques

1. Slicers and Timelines:

• Slicers: Interactive filters to slice and dice data dynamically.
• Timelines: Filter date-based data easily with interactive timelines.

2. Grouping and Ungrouping Data:

• Grouping: Combine data into manageable groups, e.g., by month or quarter.
• Ungrouping: Expand grouped data back to its original detail level.

3. Data Drill-Down:

• Drill Down: Double-click on summarised data to view underlying details, aiding in root cause analysis.

Best Practices for Pivot Table Usage

1. Data Preparation:

• Ensure data is clean, organised, and free from errors before creating pivot tables.

2. Dynamic Updates:

• Pivot tables update automatically when source data changes, ensuring analysis remains current.

3. Formatting and Visualization:

• Use pivot charts, colours, and conditional formatting to enhance data presentation and readability.

Pivot tables are indispensable tools for data summarization and analysis in Excel, offering robust functionalities to explore and derive insights from complex datasets. By mastering pivot tables, you can streamline data analysis tasks, uncover trends, and make informed decisions based on comprehensive data summaries. Whether you’re analysing sales figures, tracking project progress, or evaluating performance metrics, pivot tables provide a versatile framework for transforming raw data into actionable insights.

Frequently Asked Questions

Select your dataset, go to the Insert tab, click on PivotTable, and follow the prompts to configure your pivot table.

Yes, pivot tables are designed to process and summarise large datasets efficiently, provided the data is well-structured.

Advanced features include calculated fields, pivot charts, slicers, timelines, and conditional formatting.