Excel Tutorial: How To Make A Scatterplot In Excel


When it comes to visualizing data, scatterplots are an essential tool for identifying patterns and relationships between variables. They provide a clear and concise way to display data points on a two-dimensional graph, making it easier to spot trends and outliers. With the widespread use of Excel for data analysis and visualization, it's no surprise that creating scatterplots in Excel has become a popular choice for many professionals and students alike.

Key Takeaways

  • Scatterplots are crucial for identifying patterns and relationships between variables in data analysis
  • Excel is a popular choice for creating scatterplots and various other types of charts
  • Scatterplots are suitable for visualizing data with two variables and are useful for spotting trends and outliers
  • Organize data in columns or rows and label it appropriately for clarity when setting up in Excel
  • Customize scatterplots by adjusting axis labels, colors, styles, adding trendlines, and data labels for better visualization

Understanding the Data

A. Explain the type of data that is suitable for a scatterplot

A scatterplot is used to visualize the relationship between two sets of data. It is suitable for numerical data, and is particularly useful for identifying patterns or trends in the data. The variables should be continuous and not categorical, in order to accurately represent the relationship between them.

B. Provide examples of scenarios where a scatterplot is useful for visualizing data

  • 1. Correlation Analysis: Scatterplots are commonly used to analyze the correlation between two variables. For example, you can use a scatterplot to visualize the relationship between the amount of rainfall and crop yield, or the relationship between temperature and ice cream sales.
  • 2. Outlier Detection: Scatterplots can also be used to identify outliers or anomalies in the data. By plotting the data points, you can easily spot any values that deviate significantly from the overall pattern.
  • 3. Trend Analysis: When you want to visualize the trend or pattern between two variables, a scatterplot can help you determine if there is a positive, negative, or no correlation between the data points.

Setting up the Data in Excel

Before creating a scatterplot in Excel, it's important to set up your data in a clear and organized manner. This will not only make it easier to create the scatterplot, but also to interpret the data accurately.

A. Organize the data in columns or rows
  • Start by opening a new or existing Excel workbook and entering your data into columns or rows. Each column or row should represent a different variable or category that you want to plot on the scatterplot.
  • For example, if you are comparing the height and weight of different individuals, you would enter the heights in one column and the weights in another.

B. Label the data appropriately for clarity
  • It's important to label your data appropriately to avoid confusion when creating the scatterplot. Use clear and descriptive labels for each column or row of data.
  • For example, instead of simply labeling a column "Data 1" or "Column A," use labels like "Height (cm)" and "Weight (kg)" to clearly indicate what each set of data represents.

Creating the Scatterplot

To create a scatterplot in Excel, follow these simple steps:

A. Select the data to be used for the scatterplot
  • Open the Excel workbook that contains the data you want to use for the scatterplot.
  • Select the range of data that you want to plot on the scatterplot. This typically includes two sets of data - one for the x-axis and one for the y-axis.

B. Navigate to the "Insert" tab and choose the scatterplot option
  • Once you have selected the data, navigate to the "Insert" tab on the Excel ribbon.
  • Click on the "Scatter" option in the Charts group. This will display a drop-down menu of different scatterplot options.
  • Choose the type of scatterplot that best suits your data. Options may include a simple scatterplot, a scatterplot with straight lines, or a scatterplot with smoothed lines.
  • Click on the specific scatterplot type to insert the chart into your worksheet.

Customizing the Scatterplot

After creating a scatterplot in Excel, you may want to customize it to better convey your data and make it visually appealing. Here are some ways to customize your scatterplot:

A. Adjust the axis labels and titles
  • Horizontal and Vertical Axis Labels:

    To adjust the axis labels, right-click on the axis where you want to change the label, and select "Format Axis." From there, you can customize the labels, including the font, size, and orientation.
  • Chart Title:

    You can add or modify the chart title by clicking on the "Chart Title" and editing it as needed. This helps to give your scatterplot context and make it easier to understand at a glance.

B. Change the colors and styles of the data points for better visualization
  • Data Point Colors:

    To change the colors of the data points in your scatterplot, click on a data point to select all of them, then right-click and select "Format Data Series." From there, you can change the fill color, border color, and other visual aspects of the data points.
  • Data Point Styles:

    If you want to change the style of the data points, such as using different shapes or sizes, you can do so by accessing the "Format Data Series" menu and selecting the "Marker Options" tab. Here, you can choose from a variety of styles to customize the appearance of your data points.

By customizing the axis labels, titles, colors, and styles of your scatterplot, you can create a more visually impactful representation of your data in Excel.

Adding Trendlines and Data Labels

When creating a scatterplot in Excel, it can be beneficial to include trendlines and data labels to enhance the visual representation of the data. Trendlines help to show patterns or trends within the data points, while data labels allow for specific values to be displayed for each data point.

  • Include trendlines to show patterns in the data
  • Trendlines can be added to a scatterplot to visually represent the overall trend or pattern within the data. This can be helpful in identifying any correlations or relationships between the variables being plotted.

  • Add data labels to display specific values for each data point
  • Data labels provide a way to display the exact values for each data point on the scatterplot. This can help in making the graph more informative and easier to interpret, especially when dealing with a large number of data points.


In conclusion, scatterplots are invaluable tools in data analysis, allowing us to visually identify patterns, trends, and correlations within a dataset. By utilizing Excel to create scatterplots, we can easily analyze our data and make informed decisions. I encourage everyone to continue practicing and exploring the world of creating scatterplots in Excel, as it will undoubtedly enhance your data analysis skills and improve your ability to extract meaningful insights from your data.

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