Interpolate in Excel: A Complete Walkthrough

What is interpolation in Excel?

Imagine you have missing values in a dataset and must estimate them accurately. What do you do? I have a solution – interpolation in Excel. It helps fill the gaps between known data points, making calculations smoother.

Interpolation reduces these risks by generating reliable estimates. You can use built-in functions, formulas, or graphing techniques. The FORECAST, TREND, and LINEST functions are helpful for linear interpolation, while more advanced users turn to cubic splines. With the right approach, missing values become less of a problem.

Businesses and researchers rely on Excel for data-driven insights. Financial analysts use interpolation to predict stock prices. Scientists apply it to weather patterns. Engineers estimate missing values in sensor data.

Interpolation also improves data visualization. Excel charts with missing values can look misleading. Filling in those gaps creates smoother trends and more accurate graphs. Whether working on sales reports, financial models, or experimental results, the ability to interpolate in Excel makes a difference.

As datasets grow, so do the challenges of maintaining accuracy. Learning how to interpolate in Excel can save time and prevent errors. With the proper methods, even incomplete data can provide clear insights.

Let me show you how…

What is Interpolation in Excel?

Definition: Interpolation in Excel estimates missing values between known data points. It helps create smoother datasets for better trend analysis in Excel.

Excel provides functions like TREND for linear interpolation and GROWTH for exponential trends. These tools improve accuracy in data visualization examples using Excel. How? Using interpolation, you can predict trends and enhance reports. It ensures smoother graphs, making insights clear.

Are you in forecasting or scientific analysis? Interpolation is a key skill for better data accuracy.

Why is Linear Interpolation in Excel Important?

When dealing with incomplete data, interpolation fills in the gaps, providing a more complete picture. It’s a powerful tool for anyone working with numbers, helping you achieve better accuracy and efficiency. Here’s how it makes a real difference:

• Improves data accuracy: Interpolation fills in missing data points, creating a more accurate dataset. It smooths out gaps, ensuring your analysis is based on reliable information.
• Enhances forecasting and analysis: When doing trend analysis in Excel, interpolation helps predict future values. It allows for more precise projections, making your forecasts more robust.
• Supports scientific and engineering applications: Accurate data is crucial in fields like engineering. Linear interpolation ensures consistent data points for scientific calculations and simulations.
• Simplifies data processing: Instead of manually estimating data, interpolation automates the process. You can quickly fill in missing values to streamline your workflow.
• Saves time and effort: No more tedious manual calculations. Interpolation makes data analysis faster and more efficient.

How Linear Interpolation Works in Excel?

Have you ever wondered how linear interpolation in Excel works? It’s not as complex as it sounds. You can effortlessly estimate missing data points and make your analysis more accurate. Here’s a quick guide on how to get it done:

1. Prepare data: Start by organizing your data in two columns—for the X and Y values. This is the foundation for interpolation. Ensure the data is clean and properly formatted.
2. Find the nearest data points: To interpolate, identify the two nearest data points surrounding the missing value. These will be the basis for your calculation, helping you estimate the unknown value.
3. Apply the interpolation formula: Use Excel’s INTERCEPT and SLOPE functions or a basic linear interpolation formula: =B2 + (E1 – A2) * (B3 – B2) / (A3 – A2). This formula estimates the missing value based on the relationship between the two known points.
4. Drag formula for multiple calculations: You can drag it across multiple rows or columns. This lets you interpolate values for entire datasets, making your data analysis in Excel quicker and more efficient.

How to Perform Interpolation in Excel?

Have you ever found yourself with missing data in Excel and wondered how to estimate it accurately? Performing interpolation in Excel can help you fill those gaps and make your analysis more reliable.

Here’s how to do it step-by-step.

• Prepare your data: Start by entering your dataset into Excel. Organize the data with the known values in a clean format, ready for interpolation.
• Select your chart: Choose the chart that best represents your data. Whether it’s a line chart or a scatter plot, this will help visualize the trend you’re about to interpolate.

• Add your chart to the sheet: Once you’ve selected your chart, click to add it to your sheet. It should now appear in your Excel workspace.

• Click on add chart element: Click on the chart to bring up the “Chart Tools” options. Then, choose “Add Chart Element” to customize your chart further.
• Add a trendline: In the chart element options, select trendline and choose Linear. This is crucial for creating a smooth line representing your data trend and helps with interpolation.

• Double-click the trendline: When you double-click on the dotted trendline, a menu will appear on the right side. Check the last two options for more specific control over the trendline’s behavior and interpolation.

• Apply the interpolation formula: Use the INTERCEPT and SLOPE functions or a custom formula to estimate the missing values. These Excel functions are key for linear interpolation, ensuring the most accurate estimates.

• See the final interpolated values: Once applied, the interpolated Y values (the ones you needed) will pop up in your chart. This is a quick and effective way to fill in those gaps, improving your data analysis in Excel.

How to Analyze Interpolation in Excel?

Have you ever tried analyzing data in Excel only to be frustrated by missing values? It’s a common issue that can make your charts look incomplete.

That’s where interpolation in Excel comes in. It estimates those missing values to complete the picture.

But here’s the catch: while Excel offers basic interpolation, its data visualization tools often fail to provide smooth, clear insights. This is where ChartExpo steps in. It enhances data visualization in Excel, turning your basic graphs into powerful, accurate representations of your data.

Let’s see how interpolation works and why ChartExpo is the key to unlocking better visualizations in Excel.

How to Install ChartExpo in Excel?

1. Open your Excel application.
2. Open the worksheet and click the “Insert” menu.
3. You’ll see the “My Apps” option.
4. In the Office Add-ins window, click “Store” and search for ChartExpo on the My Apps Store.
5. Click the “Add” button to install ChartExpo in your Excel.

ChartExpo charts are available both in Google Sheets and Microsoft Excel. Please use the following CTAs to install the tool of your choice and create beautiful visualizations with a few clicks in your favorite tool.

Example

Let’s learn how to add a chart in Excel using ChartExpo and glean valuable insights from it:

Months	Meta (Facebook)	Instagram	X (Twitter)	LinkedIn
1	4000	1800	2800	2300
2	4100	1900	2900	2200
3	4200	2000	3000	2400
4	4300	2100	3100	2600
5	4400	2400	3500	2100
6	4700	2500	3600	2700
7	4800	2600	3400	2800
8	4900	2700	3700	2900
9	5000	2800	3800	3000
10	5100	2900	3900	3100
11	5200	3000	3950	3200
12	Interpolated	Interpolated	Interpolated	Interpolated

• Predict missing data: Use the GROWTH function to estimate the 12th-month values based on the existing trend.

• Apply & generate data: Enter =GROWTH(C2:C12,$A$2:$A$12,$A$13,TRUE) for each column to calculate the missing values.

• Our data will look like the one below:

Months	Meta (Facebook)	Instagram	X (Twitter)	LinkedIn
1	4000	1800	2800	2300
2	4100	1900	2900	2200
3	4200	2000	3000	2400
4	4300	2100	3100	2600
5	4400	2400	3500	2100
6	4700	2500	3600	2700
7	4800	2600	3400	2800
8	4900	2700	3700	2900
9	5000	2800	3800	3000
10	5100	2900	3900	3100
11	5200	3000	3950	3200
12	5424	3290	4214	3318

• Visualize with a chart: Use ChartExpo to compare trends across different data points.
• To get started with ChartExpo, install ChartExpo in Excel.
• Now, click on My Apps from the INSERT menu.

• Choose ChartExpo from My Apps, then click Insert.

• Once it loads, scroll through the charts list to locate and choose the “Multi Series Line Chart”.

• You will see a Multi-series Line Chart on the screen.

• Click the “Create Chart Manually” button after selecting the data from the sheet.

• Select four series and one dimension, as shown in the image below, and click the “Create Chart” button.

• ChartExpo will generate the visualization below for you.

• If you want to add anything to the chart, click the Edit Chart button:

• Click the pencil icon next to the Chart Header to change the title.
• It will open the properties dialog. Under the Text section, you can add a heading in Line 1 and enable Show.
• Give the appropriate title of your chart and click the Apply button.

• Change the legend shape to Line and Circle as follows. You need to set this property for each one individually.

• Click the “Save Changes” button to persist the changes made to the chart.

• Your final Multi-series Line Chart will look like the one below.

Insights

• Top reach: Meta (Facebook)
• Second place: X (Twitter)
• Third place: LinkedIn (declined in the fifth month)
• Lowest reach: Instagram
• Trend: All channels show a trending pattern

Benefits of Excel Forecast Linear Interpolation

Have you ever wondered how Excel’s forecast linear interpolation can make your data work for you? It’s a helpful tool, especially when dealing with incomplete datasets. Estimating missing values helps create smoother, more accurate trends.

Let’s explore the reasons why using linear interpolation in Excel can boost your data analysis:

• Automates interpolation: Excel automates the interpolation process, saving you time. You won’t need to fill in missing data points manually anymore.
• Improves accuracy: The interpolation is precise with built-in formulas, leading to more reliable analysis. This means you can trust your data to be spot on.
• Handles large datasets: Excel can process large datasets efficiently. It makes interpolating large volumes of data a breeze.
• Simplifies trend analysis: By filling in gaps, linear interpolation simplifies trend analysis and provides a clearer view of how the data behaves over time.
• Reduces human error: Manual calculations can lead to mistakes. Excel’s interpolation minimizes human error, ensuring accuracy in every estimate.
• Versatile across industries: From finance to engineering, interpolation is versatile. You can apply it in any field for better decision-making.

FAQs

How do you interpolate nonlinear data in Excel?

1. Use the GROWTH or LOGEST function for exponential trends.
2. Apply the TREND function for polynomial data with a higher-order equation.
3. Create a scatter plot, add a trendline, and use its equation for accurate estimates.

How to extrapolate between two numbers in Excel?

1. Use the FORECAST function: =FORECAST(new_x, known_y, known_x).
2. Apply the TREND function for linear projections and the GROWTH function for exponential trends.
3. Plot a trendline to visualize and verify the extrapolated values.

Wrap Up

Interpolation in Excel means estimating missing values within a dataset. It helps smooth out data for better analysis. This is useful for trend analysis in Excel and predicting unknown values between known data points.

Excel offers several functions for interpolation. The TREND function estimates linear data, while GROWTH works for exponential trends. These Excel functions for data analysis ensure accuracy.

Polynomial interpolation can be applied to complex data. A scatter plot with a trendline is a great way to visualize these estimates. You can also use Excel plug-ins for advanced interpolation techniques.

Interpolation is widely used in data visualization. It helps create smoother graphs by filling gaps in datasets and improving insights when working with charts.

After interpolating, you can convert Excel data to graphs for better understanding. Using cool Excel charts and graphs makes your findings more impactful.

Mastering interpolation boosts data analysis in Excel. Whether predicting values or enhancing visuals, knowing how to interpolate ensures accurate and precise reports.

Do not hesitate; Install ChartExpo to create easy-to-read, insightful charts.