Master Excel charts with pro tips and techniques for impactful data visualization, driving your career forward!
by Mihir Kamdar / Last Updated:
This comprehensive guide on Excel Charts. By the end of this article, you’ll be able to:
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In today’s data-driven world, efficiently analyzing and drawing meaningful insights from large datasets is a crucial skill for professionals across industries. Microsoft Excel’s pivot tables are one of the most powerful tools for transforming raw data into actionable information. Whether you’re a business analyst, sales manager, or data enthusiast, mastering pivot tables will help you save time, uncover hidden trends, and make informed decisions to drive your organization’s success.
In this ultimate guide, we’ll take you on a journey through the world of pivot tables, from the fundamentals to advanced techniques and real-world applications. You’ll learn how to prepare your data, create and customize pivot tables, write powerful calculations, and build interactive dashboards to communicate your findings effectively. We’ll also share best practices, common mistakes to avoid, and tips for your pivot tables for maximum performance and impact.
Before diving into chart design tab and creation, it’s essential to understand and prepare your data. This step lays the foundation for effective data visualization and ensures that your charts accurately represent the underlying information.
1. Cleaning and organizing data: Start by reviewing your data for any errors, inconsistencies, or formatting issues. Remove duplicates, fix typos, and ensure that your data is structured in a logical manner. A clean dataset will make the charting process smoother and more accurate.
2. Choosing the right data range: Select the data range that you want to visualize in your chart. This typically includes the data series (the values you want to plot) and the associated labels or categories. Be sure to exclude any irrelevant data that may clutter your chart or distort the insights you want to convey.
3. Handling missing or inconsistent data: Decide how to handle missing or inconsistent data points. You may choose to exclude them from your chart, interpolate values based on surrounding data, or use a special formatting to indicate missing data. Consistency in your approach will help maintain the integrity of your visualizations.
Choosing the right chart type is crucial for effectively communicating your data story. Excel offers a variety of chart types, each suited for different types of data and insights:
1. Column charts: Use column charts to compare values across categories. They are ideal for showing differences in magnitude or frequency among discrete groups. For example, a column chart could display sales figures by product category or monthly website traffic.
2. Line charts: Line charts are best for visualizing trends or changes over time. They connect data points with lines to emphasize the progression of values. Use line charts to track metrics like stock prices, revenue growth, or customer acquisition rates.
3. Pie charts: Pie charts display the proportions of a whole, with each slice representing a category’s share of the total. They are useful for showing the composition of a dataset, such as market share by competitor or budget allocation by department. However, be cautious when using pie charts, as they can be difficult to interpret when there are many categories or small differences in proportions.
4. Scatter plots: Scatter plots are used to explore relationships between two variables. Each data point represents a pair of values, with its position determined by the x and y coordinates. Scatter plots can reveal patterns, correlations, or outliers in your data. They are commonly used in scientific or financial analyses to identify trends or clusters.
5. Bar charts: Similar to column charts, bar charts compare values across categories. However, bar charts use horizontal bars instead of vertical columns. They are a good choice when category labels are long or when you want to emphasize the ranking of values.
6. Area charts: Area charts are similar to line charts but with the area under the line filled in with color. They are useful for showing changes in proportions over time, such as market share trends or the composition of a portfolio. Stacked area charts can display the relative contributions of multiple categories to a total value.
7. Radar charts: Also known as spider charts, radar charts compare multiple variables across several axes that radiate from a central point. They are useful for comparing performance or characteristics across different dimensions or criteria. For example, a radar chart could display a product’s ratings on various attributes like price, quality, and customer satisfaction.
When selecting a chart type, consider the nature of your data and the key insights you want to highlight. Think about whether you’re comparing categories, showing trends over time, displaying proportions, or exploring relationships between variables. Choose a chart style and type that effectively communicates your message and aligns with your audience’s expectations and familiarity with data visualization.
Before creating your chart, it’s important to define your purpose and consider your target audience:
1. Identifying the key message you want to convey: Clearly articulate the main insight or takeaway you want your audience to gain from your chart. This could be highlighting a significant trend, comparing performance across categories, or showcasing the impact of a particular variable. Keep your key message focused and concise.
2. Tailoring your chart to your target audience: Consider the background and expertise of your audience when designing your chart. What level of detail or complexity will they expect? Are they familiar with the data or context, or will you need to provide additional explanations? Tailor your chart’s design, labels, and annotations to ensure that your audience can easily understand and interpret the information.
By understanding your data, selecting the appropriate chart type, and considering your purpose and audience, you’ll be well-prepared to create effective and impactful Excel charts.
Now that you’ve prepared your data and chosen the right chart type, let’s dive into creating basic charts in Excel. We’ll use a sample dataset to illustrate the process and highlight key features and customization options.
1. Select the data range you want to chart, including the headers (A1:H301 in our example).
2. Select existing worksheet and choose Processed Data in cell A1. Press OK.
3. Drag Region in Rows area and Total Revenue in Value area.
4. Go to the Insert tab on the Excel ribbon, click on Pivot Chart and click on the Column chart icon in the Charts group. Choose the desired column chart subtype (e.g., Clustered Column).
5. Excel will create a basic column chart with default formatting and place it on your worksheet. Add the title, axis title, data labels, gridlines and hide all the field buttons on chart. Also, include the chart and axis title.
6. You can change the color of bars by selecting the bar Choose Shape Fill → More Fill Colors → Enter the HEX Code #1B263B → Press OK.
1. Select the data range you want to chart, including the headers (A1:H301 in our example).
2. Select existing worksheet and choose Processed Data in cell A23. Press OK.
3. Drag Order Date in Rows area and Total Revenue in Value area.
4. Go to the Insert tab on the Excel ribbon, click on Pivot Chart, and click on the line chart icon in the Charts group. Choose the line chart.
5. Excel will create a basic line chart with default formatting and place it on your worksheet. Add the title, axis title, data labels, gridlines and hide all the field buttons on chart. Also, include the chart and axis title.
6. You can change the color of bars by selecting the line. Choose Shape Fill → More Fill Colors → Enter the HEX Code #1B263B → Press OK.
1. Select the data range you want to chart, including the headers (A1:H301 in our example).
2. Select existing worksheet and choose Processed Data in cell G1. Press OK.
3. Drag Sales Channel in Rows area and Total Revenue in Value area.
4. Go to the Insert tab on the Excel ribbon, click on Pivot Chart, and click on the pie chart icon in the Charts group. Choose the pie chart.
5. Excel will create a basic pie chart with default formatting and place it on your worksheet. Add the title, data labels, and hide all the field buttons on chart.
6. You can change the color of pie by selecting the shape.
1. Select the data range you want to chart, including the headers (A1:H301 in our example).
2. Select existing worksheet and choose Processed Data in cell G17. Press OK.
3. Drag Item Type in Rows area and Total Revenue in Value area.
4. Go to the Insert tab on the Excel ribbon, click on Pivot Chart, and click on the bar chart icon in the Charts group. Choose the bar chart.
5. Excel will create a basic pie chart with default formatting and place it on your worksheet. Add the title, data labels, and hide all the field buttons on chart.
6. You can change the color of bars by selecting the line. Choose Shape Fill → More Fill Colors → Enter the HEX Code #1B263B → Press OK.
While pivot tables are powerful data analysis tools, their true impact lies in how effectively you can present and communicate your findings. In this section, we’ll explore the principles of good pivot table design, layout choices, and styling options to help you create visually appealing and impactful reports.
1. Use a color palette that aligns with your brand guidelines or the tone of your presentation. Consistent color use helps create a professional and cohesive look.
2. Choose colors that are easily distinguishable from one another, especially when displaying multiple data series. Avoid using too many colors, as this can be visually overwhelming.
3. Ensure that your color choices are accessible and easily visible for all viewers, including those with color vision deficiencies.
4. Select fonts that are clear, legible, and appropriate for your audience. Use font sizes that are large enough to read easily, especially when presenting charts on a screen or in a large room.
1. Create a descriptive and concise chart title that clearly communicates the main takeaway or purpose of your chart. Position the title prominently, usually centered above the chart.
2. Label your axes clearly and accurately, including units of measurement where applicable. Avoid using abbreviations or jargon that may be unfamiliar to your audience.
3. Use data labels sparingly to highlight key data points or values. Too many data labels can clutter your chart and make it difficult to read.
4. Include a legend to identify the different data series or categories in your chart. Position the legend in a way that doesn’t obstruct the main chart area, such as to the right or below the chart.
1. Identify the key messages or takeaways you want to convey with your data. These should align with the overall narrative or purpose of your presentation.
2. Select charts that effectively illustrate your key points and provide evidence to support your arguments. Avoid using charts that are not directly relevant to your narrative.
3. Arrange your charts in a logical sequence that builds your story and guides your audience through your insights. Consider using a storyboarding approach to plan the flow of your narrative.
1. Define the purpose and audience for your dashboard. This will help you determine which metrics and charts to include and how to organize them.
2. Select a limited number of key metrics or data points to feature in your dashboard. Too many charts can overwhelm your audience and dilute your message.
3. Choose chart types that are appropriate for each metric and provide a clear and concise view of the data. Avoid using overly complex or unfamiliar chart types that may confuse your audience.
4. Arrange your charts in a logical and visually appealing layout. Group related charts together and use consistent formatting to create a cohesive look.
5. Use white space effectively to separate different sections of your dashboard and make it easier for your audience to navigate and understand the information.
1. Identify the dimensions or categories that your audience may want to explore or filter in your data. These could include time periods, geographic regions, product categories, or customer segments.
2. Create slicers or filters for these dimensions using the PivotChart and PivotTable tools in Excel. Slicers provide a visual and intuitive way for users to interact with your charts and explore different subsets of the data.
In our case, we will choose Country as the filter. Select any cell in the PivotTable → Go to Insert → Go to Slicer.
3. We need to build a Report Connection so all the PivotTable can be connected where all the Slicers can filter through all the visuals.
4. Copy paste the slicer into the Dashboard tab and resize it. Format your slicers so it can be visually appealing and easy to use.
Also, change the columns to two and change the color to grey.
Test your interactive charts to ensure that they are functioning properly and providing meaningful insights. Make sure that the interactions are intuitive and do not lead to confusion or misinterpretation of the data.
To create effective and impactful charts, it’s essential to follow best practices and avoid common mistakes. In this section, we’ll discuss top tips for creating compelling charts, highlight common pitfalls to avoid, and explore alternatives to charts for presenting data.
1. Keep it simple and focused: Avoid cluttering your charts with unnecessary elements or data points. Focus on the key insights you want to convey and remove any distractions.
2. Choose the right chart type: Select a chart type that accurately represents your data and effectively communicates your message. Consider the nature of your data (e.g., trends over time, comparisons, proportions) and the purpose of your visualization.
3. Use clear and concise labels: Ensure that your chart title, axis labels, and legend are clear, accurate, and easy to understand. Avoid using jargon or abbreviations that may confuse your audience.
4. Maintain consistency: Use consistent formatting, colors, and styles across related charts to create a cohesive and professional look. This helps your audience focus on the data rather than being distracted by inconsistencies.
1. Misleading or confusing chart types: Avoid using chart types that distort the relationship between data points or make it difficult to interpret the information accurately. For example, using a 3D pie chart can make it harder to compare slice sizes accurately.
2. Overcrowding your charts: Too much information on a single chart can overwhelm your audience and make it difficult to discern the key insights. Be selective about the data you include and consider breaking complex data into multiple charts if necessary.
3. Failing to provide context: Without proper context, your audience may struggle to understand the significance of your data. Provide background information, benchmarks, or explanations to help your viewers interpret the data accurately.
The four main types of charts in Excel are:
To create a chart in Excel:
Excel charts are used for:
To create a trend chart in Excel:
To create a chart with multiple data series:
Line charts are the most commonly used type of Excel chart for displaying trends over time. They connect data points with lines to show the progression of values, making it easy to identify patterns and changes in your data. Alternatively, Area charts can be used to show trends while also representing the magnitude of values over time.
Throughout this comprehensive guide, we’ve explored the world of Excel charts, from the fundamentals to advanced techniques, and best practices. By mastering the concepts and tools covered in these chapters, you’ll be well-equipped to harness the power of Excel charts and unlock valuable insights from your data.
You’ve learned how to:
