Master Excel chart creation and customization. Learn to select types, add titles, and more with our guide.
by Mihir Kamdar / Last Updated:
This comprehensive guide on mastering excel charts in Microsoft Excel. By the end of this article, you’ll be able to:
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In today’s data-driven world, the ability to effectively visualize and communicate information is a crucial skill for professionals across all industries. Excel, a powerful tool in the Microsoft Office suite, offers a wide range of charting options to help you create compelling visual representations of your data. In this beginner’s guide to excel chart basics, we’ll walk you through the basics of Excel charts using a single Excel file example featuring a company’s sales data, empowering you to transform raw data into meaningful insights.
Data visualization is the process of translating complex data sets into visual representations, such as visual representation such as charts and graphs. By presenting data visually, you can:
Quickly identify patterns, trends, and outliers
Make data more accessible and easier to understand
Communicate insights more effectively to stakeholders
Support data-driven decision making in your organization
Excel charts are an essential tool for data visualization, allowing you to create professional-looking visuals and chart data with just a few clicks. Whether you’re working in marketing, finance, human resources, or any other field, mastering the art of Excel charts will help you communicate your message more effectively and drive better business outcomes.
Excel offers a wide variety of chart types to help you visualize your data effectively. Each chart type has its own strengths and weaknesses, and choosing the right one depends on the nature of your data and the message you want selected chart to convey. Let’s take a closer look at some of the most common types of Excel charts and when to use them.
Column charts display data using vertical bars, while bar charts use horizontal bars. They are best used for comparing discrete categories or values, such as sales by product or revenue by region.
Stacked column or bar charts can be used to show the composition of each category, such as the breakdown of sales by product type within each region.
Clustered column or bar charts can be used to compare multiple data series side-by-side, such as sales by product for different months.
Line charts connect data points with lines, showing trends or changes over time. They are best used for displaying continuous data, such as sales, stock prices, temperature readings, or website traffic.
Area charts are similar to line charts but fill the area below the line with color or shading, emphasizing the magnitude of change.
Stacked area charts can be used to show the composition of a total value over time, such as the breakdown of product sales over time.
Pie charts display data as slices of a circular pie, representing parts of a whole. They are best used when you have a small number of categories (ideally 4-6) that add up to 100%.
Doughnut charts are similar to pie charts but have a hole in the center, which can be used to display additional information or create a more visually appealing design.
Scatter charts plot data points on a horizontal and vertical axis, showing the relationship between two variables.
They are best used when you want to visualize the correlation or distribution of data points, such as the relationship between a product’s sales over time.
Combination charts allow you to display multiple chart types in a single chart, such as a column chart with a line chart overlay.
They are best used when you want to compare different data series with different scales or units, such as sales revenue (columns) and advertise expense (line) over time.
Histograms are a type of column chart that display the distribution of a dataset across a range of values. They are best used when you want to visualize the frequency or density of data points within certain intervals, such as the distribution of customer profit range.
Box and whisker charts, also known as box plots, display the distribution of a dataset using quartiles and outliers. They are best used when you want to compare the distribution of multiple datasets side-by-side, such as the performance of different sales regions or product categories.
Treemaps display hierarchical data using nested rectangles of varying sizes and colors.
They are best used when you want to visualize the composition and relative sizes of different categories or segments, such as the market share of different countries within an region.
When choosing to create a chart of type, consider the following factors:
The type of data you have (e.g., categorical, continuous, hierarchical)
The relationship between your data variables (e.g., comparison, distribution, composition)
The message or insight you want to convey to your audience
The clarity and readability of the chart for your intended audience
By understanding the strengths and weaknesses of each chart type and matching them to your data and communication goals, you’ll be able to make new chart and create effective and impactful visualizations in Excel.
Let’s dive into creating a chart, using our sample Excel file containing a company’s monthly sales data for different product categories.
1. Open the Excel file with the sales data.
2. Ensure the data is organized in a clear and consistent format, with headers and labels.
3. In this example, the data should be structured with years in the first column and sales in second column.
1. Select the data range, including the headers, that you want to include in your chart.
2. In this case, highlight the cells containing the months and the sales figures.
1. Navigate to the “Insert” tab on the Excel ribbon.
2. In the “Charts” group, click on the “Recommended Charts” icon to see a list of chart types that Excel suggests based on your data.
3. For our sales data, a column chart would be appropriate to display trends and changes over time. Click on the “Column” chart icon and choose a cluster column chart.
4. Click “OK” to insert the chart onto your worksheet.
1. Excel will generate a basic column chart based on your selected data.
2. Click on the chart title and modify it to clearly describe the information presented, e.g., “Monthly Sales.”
3. Adjust the axis labels to ensure they are readable and relevant, such as adding a currency symbol to the values on the vertical axis.
4. Add data labels to provide additional context and make values easier to read by right-clicking on a data point and selecting “Add Data Labels.”
5. Resize and reposition the chart on your worksheet as needed.
Now that you’ve created your column chart below, let’s explore how to format it for maximum impact.
1. Format the chart title to make it stand out:
2. Format the axis title clarity:
1. Click on the chart to select it.
2. Navigate to the “Design” tab on the Excel ribbon.
3. In the “Chart Styles” group, browse through the pre-built styles and hover over each to preview how it would look on your chart.
4. Choose a style that complements your data and enhances readability, such as a style with a light background and contrasting column colors.
1. Right-click on the chart and select “Add Chart Element” from the context menu.
2. Hover over “Gridlines” and select “Primary Major Horizontal” to add gridlines for the y-axis.
3. Adjust the gridline color to a light gray to ensure they are visible without overpowering the data.
4. Optionally, add vertical gridlines by selecting “Primary Major Vertical” from the “Gridlines” menu.
Excel charts are versatile tools that can be applied to a wide range of business scenarios. Here are a few real-world examples and use cases:
Visualize product metrics, such as segment and product to identify trends and optimize your marketing strategies.
Visualize employee count by position and performance rating which would help to identify areas for improvement.
The best chart to use in Excel depends on the type of data you have and the message you want to convey. Some common chart types include column, line, pie, bar, area, scatter, and combination charts. Consider the nature of your data and the relationship between variables when selecting a chart type.
While Excel offers many chart types, four commonly used types are:
1. Column charts
2. Line charts
3. Pie charts
4. Bar charts
To create a chart in Excel:
1. Select the data you want to chart.
2. Go to the Insert tab on the ribbon.
3. In the Charts group, click on the desired chart type.
4. Choose a specific chart subtype from the options.
5. Customize the chart elements, such as titles, labels, and legends.
Excel can produce a wide variety of charts, including column, line, pie, bar, area, scatter, bubble, stock, surface, radar, treemap, sunburst, histogram, box & whisker, waterfall, funnel, and combination charts.
Excel supports many chart types, but five commonly used ones are:
1. Column charts
2. Line charts
3. Pie charts
4. Bar charts
5. Area charts
Three basic types of Excel charts are:
1. Column charts (for comparing categorical data)
2. Line charts (for showing trends over time)
3. Pie charts (for displaying parts of a whole)
Excel offers 16 main chart types:
1. Column
2. Line
3. Pie
4. Bar
5. Area
6. X Y (Scatter)
7. Stock
8. Surface
9. Radar
10. Treemap
11. Sunburst
12. Histogram
13. Box & Whisker
14. Waterfall
15. Funnel
16. Combo (Combination)
The best way to visualize data in Excel depends on your specific data and goals, but some general tips include:
1. Choose the right chart type for your data and message.
2. Keep charts simple and uncluttered.
3. Use meaningful titles, labels, and legends.
4. Highlight key insights with data labels, trendlines, or annotations.
5. Use colors and formatting to make the chart visually appealing and easy to understand.
In this beginner’s guide, we’ve covered the basics of creating, customizing, and formatting Excel charts using a single Excel file example of a company’s sales data. You’ve learned how to select the chart below:
You’ve learned how to:
By mastering these skills, you’ll be well-equipped to create compelling visuals that drive understanding and action in your professional life.
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