How to Connect Data Points in Excel

Transforming rows of data into a clear visual story is one of Excel's superpowers, and connecting your data points is the best way to do it. Simply plotting dots is fine, but drawing a line between them reveals trends, patterns, and insights you'd otherwise miss. This tutorial will walk you through exactly how to connect data points in Excel, from creating a basic line chart to using scatter plots with insightful trendlines.

Why Connect Data Points in Excel?

While a table of numbers is precise, it's not very intuitive. The human brain is much better at spotting patterns visually. When you connect data points on a graph, you're not just showing individual values, you're illustrating the relationship between them. This simple act transforms isolated numbers into a coherent narrative about your business.

For example, you can instantly see:

• Trends over time: Is your website traffic growing month-over-month? Connecting the data points for each month on a line chart will immediately show you the upward (or downward) trajectory.
• Relationships between variables: Does spending more on advertising lead to more sales? A scatter plot connecting points can reveal a positive or negative correlation.
• Outliers and anomalies: Did sales suddenly spike in March? A sharp peak in your connected line chart will make this stand out, prompting you to investigate the cause.

Connecting data points adds context, making your reports more digestible and your insights more impactful. It's the difference between presenting raw data and telling a compelling story with it.

Connecting Points by Creating a Basic Line Chart

The most direct way to connect dots is with a line chart. This graph type is perfect for tracking a metric over a sequential period, like days, months, or years. Think of tracking monthly sales, weekly website visits, or daily user sign-ups.

Step 1: Set Up Your Data Correctly

Before you create any chart, your data needs to be organized. For a line chart, you need at least two columns:

• Column 1 (X-axis): This contains your sequential labels, typically time-based like dates, months, or quarters.
• Column 2 (Y-axis): This contains the numeric values you want to measure, like revenue, units sold, or user count.

Make sure your data is clean, with the first row acting as a clear header for each column. Here’s a simple example tracking quarterly sales:

Step 2: Graph the Data and Create the Line Chart

Once your data is ready, creating the chart takes just a few clicks.

1. Click and drag to highlight the entire data range you want to plot, including the headers.
2. Navigate to the Insert tab on the Excel ribbon.
3. In the Charts section, click on the icon that looks like a line chart (it’s labeled 'Insert Line or Area Chart').
4. A dropdown will appear. For this purpose, choose a 2-D Line chart. The "Line with Markers" option is often the best choice because it places a distinct dot on each data point while also connecting them with a line, giving you the best of both worlds.

Excel will instantly generate a chart and place it on your worksheet. You will see your quarters along the bottom (X-axis) and sales values along the side (Y-axis), with each data point connected by a line.

Step 3: Customize for Clarity

A default chart is a good start, but a great chart is clear and easy to understand at a glance.

• Add a Chart Title: Click on "Chart Title" at the top and give it a descriptive name like "Quarterly Sales Performance."
• Label Your Axes: To add labels, click on your chart, look for the green plus (+) sign on the upper-right corner. Check the box next to "Axis Titles." Then you can edit the value axis title to "Sales ($)" and the category axis to "Quarter."

Using Scatter Plots to Connect Related Data

Sometimes your data isn't sequential. Instead, you might want to see if there's a relationship between two different numerical variables - for example, how does daily temperature affect ice cream sales? Or how does ad spend impact website clicks? In these cases, a Scatter Plot is your best tool.

Step 1: Graph Your Paired Variable Data

Just like with a line chart, your data structure is key. For a scatter plot, you'll need two columns of numerical data. Unlike a line chart, the X-axis doesn't have to be a time series. Each row represents a single paired observation.

Let's use an example of monthly ad spend versus website traffic:

Step 2: Generate the Scatter Chart

1. Select your two columns of data, including the headers.
2. Go to the Insert tab.
3. In the Charts group, click the icon for Insert XY (Scatter) or Bubble Chart.
4. Choose the first option, the basic Scatter chart.

This will create a chart displaying individual points. Each point represents one month, with its position determined by its Ad Spend (X-axis) and Website Sessions (Y-axis). At this stage, the dots are not connected.

Step 3: Connecting the Dots with a Trendline

The way we connect dots in a scatter plot is by adding a trendline. This line shows the general trend or correlation in the data, it doesn't connect each dot individually like a line chart, but instead draws a "line of best fit." This line is crucial for quickly understanding whether there is a positive (as X increases, Y also increases), negative (as Y increases, X decreases), or no relationship between your variables.

1. Right-click on one of the data points in your chart.
2. In the context menu that appears, select Add Trendline.

Excel will immediately add a straight (linear) trendline to your plot and open the 'Format Trendline' pane on the right.

Choosing the Right Trendline Type

In the 'Format Trendline' pane, you can choose different types based on how your data behaves:

• Linear: The default and most common option. Use this when you believe the relationship is fairly consistent - a straight line. For example, sales demand and revenue.
• Logarithmic: Use this if your data increases or decreases quickly and then levels off, like the effect of diminishing returns.
• Polynomial: Use this for data that has curves, peaks, and valleys. You can choose the degree (order) of the curve for a more precise fit.
• Moving Average: Use this to smooth out fluctuations in data to reveal overall trends more clearly. It’s helpful for noisy stock prices or website traffic.

For example, a linear trendline will show a clear positive correlation: as you spend more on ads, your website sessions tend to increase.

Advanced Formatting: Smoothing Lines in Excel Charts

Both line charts and scatter plots with connected lines can be further refined with a "smoothed line." This option can make your chart look less angular and more polished for presentation, but it's important not to overuse smoothing as it can misrepresent the data.

How to Smooth Lines in Excel

To smooth a line in your chart:

1. Right-click on the data series (the line itself) to highlight all the points.
2. In the context menu, find and select Format Data Series (the paint brush icon in the 'Format' pane).
3. At the bottom of options, check the box labeled "Smoothed Line."

Excel will immediately convert your hard line into a gently curving line, smoothing out consistent changes. This works for both line charts and scatter plots that have lines connecting the data points (like a Scatter with Straight Lines chart type).

When to Use Smoothed Lines (and When Not to)

Smoothed lines can be excellent for visualizing general trends and making charts appear more professional and visually pleasing, but you should use them cautiously. Smoothed lines can sometimes misrepresent precise data points by averaging the spread.

• Use smoothed lines: When showing general trends in an executive summary, where the overall picture matters more than the exact value of each dot.
• Avoid smoothed lines: When you need to present exact, unaltered data points for analysis, for example, in scientific graphs or financial reports. A straight line with markers is often more precise than smoothed.

Tips for Making Your Connected Data Points Tell a Clear Story

Creating a chart is one thing, making it effective is another. Here are some quick tips to improve the clarity of your charts:

• Use Markers: In line charts with markers (dots or squares), make it easier to pinpoint the exact location of each data point, making them more precise.
• Don’t overcrowd with data: It's tempting to add multiple lines to one chart to compare different metrics (like quarterly sales for different products). But too much at once creates a “spaghetti chart” that’s hard to read. Consider splitting the data into multiple charts.
• Mind Your Axes: Ensure your axis scale starts at zero or the lowest value relevant for what they are representing (e.g., sales revenue). Starting at a higher value can exaggerate changes and make them seem more significant than they are.
• Use Clear Labels: This cannot be stressed enough. Always include a descriptive title, axis labels (both X and Y), and a legend if you have multiple data series. Ensure anyone looking at the chart can understand exactly what it shows without having to ask you for explanation.

Final Thoughts

Knowing how to connect data points in Excel turns your spreadsheets into dynamic insights. By using line charts, scatter plots, and trendlines, you can visually relate trends, discover relationships, and communicate the story in your data with clarity and impact.

While manually creating these charts is an essential skill for any data professional, discovering that the time-consuming process of exporting, formatting, and building these charts can be automated for greater efficiency. Leverage Graphed to automate this and streamline your reporting processes so you can skip the manual work and get straight to the insights. Because connected directly to your data sources like Google Analytics or Salesforce, you can get to elevated dashboards without opening another Excel chart again.