Because of various reasons, we can have datasets with missing data points. It is possible to estimate an approximate value of that data point using many useful interpolation techniques.Â If you are curious to know how you can interpolate missing data in Excel, then this article may come in handy for you. In this article, we discuss how you can interpolate missing data in Excel with elaborate explanations.

**Interpolate** **Missing** Data in Excel: 4 Easy Ways

We are going to use the dataset below, where we have the product id and those products’ quantities. But at the same time, we also have Missing data points here. By applying various kinds of interpolation methods, we can estimate the approximate value of that Missing cell.

### 1. Use of Linear Trend Method

The linear trend means whether a dataset has variables that follow constant relationship relationships with each other. And at the rate at which the variables change their values almost follow a linear pattern.

**Formula:**

Here,

**(x1, y1)** = The First coordinate of the interpolation process.

**(x2,y2)** = Second point of the interpolation process.

**x **= Known value.

**y **=Unknown value.

The dataset that we are going to use has this linear pattern, although it has some of its data missing, as seen in the image. The missing data point can be demonstrated by the discontinuities in the line.

If your dataset follows this pattern, then you can use the below method to extract the missing value.

**Steps**

- We have the below dataset where we have the cell data
**C7**and**C9**missing. - Using the surrounding values, we need to estimate the quantity values in those cells.

- Next, select the range of cells
**D6:D8**, and then go to the**Home**tab >**Editing**group. - Right after that, go to
**Fill**>**Series**.

- In the
**Series**window, click on the**Columns**in the**Series in**option and select**Linear**in the**Type**option. - You can see that the
**Step**values are now set to 2.5 by default. You can edit these values for your needs.

- You can also calculate the step value using the following formula in the cell
**C18**:

`=(C16-C15)/(C17+1)`

- Repeat the same process for the
**D9**cell. - In order to get the missing value of the
**D9**cell, select the range of cells**D8:D10**,Â and then go to the**Home**tab >**Editing**group. - Right after that, go to
**Fill**>**Series**. - In the
**Series**window, click on the**Columns**in the**Series in**option and select**Linear**in the**Type**option. - You can see that the
**Step**values are now set to 2.5 by default. You can edit these values for your need. - Click
**OK**after this.

- After clicking
**OK**, we can see that the cell with the missing values now has the values retrieved by using the**Linear Trend**.

### 2. Utilizing Growth Trend Method

When predicting future growth based on past data, growth trend interpolation in Excel can be useful. Linear growth suggests a constant extra increase throughout time, resulting in a straight path on a graph. This means that the annual percentage increase is decreasing slightly with each passing year.

**Steps**

- We have the below dataset where we have the cell data
**C7**and**C9**missing. - Using the surrounding values, we need to estimate the quantity values in those cells.

- Next, select the range of cells
**D6:D8**, and then go to the**Home**tab >**Editing**group. - Right after then, go to
**Fill**>**Series**.

- In the
**Series**window, click on the**Columns**in the**Series in**option and select**Growth**in the**Type**option. - Tick the
**Trend**check box and click**OK**.

- Repeat the same process for the second missing value in cell
**D9**. - Next, select the range of cells
**D8:D10**, and then go to the**Home**tab >**Editing**group. - Right after then, go to
**Fill**>**Series**.

- In the
**Series**window, click on the**Columns**in the**Series****in**option and select**Growth**in the**Type**option. - Tick the
**Trend**check box and click**OK**.

- After clicking
**OK**,Â you will see that both cells**D9**and**D7**now have the missing value.

### 3. Implementing Weighted Moving Average Formula

Here, we will interpolate missing values by implementing the Weighted Moving Average formula.

I am using another dataset with two columns, Named **Month** and **Sales Quantity**, with range **B4:C13** like the following image. I am considering **10** as the total weight (**Wt**) and distributing the Wt among the previous month in such a way that recent data gets more weight. As you can see, I have data only for **January, February,** and **March.** We will interpolate the **Sales Quantity** for the rest of the months.

**Definition:**

**The weighted moving average (WMA) is a useful metric that gives more weight to the latest data points and less weight to datasets from a long time ago.**

**Formula:**

**Here,**

**A1, A2, A3, A4** â€¦.., is the data point of the datasets.

**W1, W2, W3, W4**â€¦â€¦ are the weight assigned to each data point.

**Wt **is the summation of all weights.

Let’s apply the above theory to our dataset.

**Follow these steps**:

**Step 1**: Select cell **C8** => Insert the given formula.

`=((C7*$F$10)+(C6*$F$9)+(C5*$F$8))/$E$5`

**Step 2**: Hit **Enter** to see the result.

**Step 3**:Â Hover over the cursor to the bottom right corner of cell **C8** to see the **Fill Handle** icon.

**Step 4**: Drag the **Fill Handle** icon to cell **C13** to copy the formula.

### 4. Using Simple Moving Average Formula

**Definition:**

**Simple moving averages compute the average of a price range over a given number of periods.**

**Formula:**

Here,

**A1, A2, A3, A4……An **is the data point of the datasets.

**N **= Denotes the number of data points.

A simple moving average is a measurement tool that can help predict if an asset price will maintain or if it falls into reverse bull even in a bear trend. Here, in this method, we will consider the dataset of the first two methods and use the** AVERAGE **and **IF **function alongside the weighted moving average to estimate the missing value.

**Steps**

- In the beginning, we need to choose the span range. here we choose span 3.
- In this method, we have to average the value, which will be done in a spanwise row.
- For example, we have a missing value in cell
**C7**. And the formula span of this cell would be**E6:E8.**

- For example, we have a missing value in cell
**C9**. And the formula span of this cell would be**E8:E10**.

- We first select cell
**E5**and enter the following formula:

`=IF(C5="",D5,C5)`

- Then repeat the same formula in the cell
**E6**and enter the following formula:

`=IF(C6="",D6,C6)`

- Now, select cell
**E11**and enter the following formula:

`=IF(C11="",D11,C11)`

- Drag the
**Fill Handle**to cell**E13**.

- After that, select cell
**E7**and enter the following formula:

`=IF(C7="",AVERAGE(D5:D9),C7)`

- Drag the
**Fill Handle**to cell**E10**. - Doing this will fill the range of cell
**E8:E10**with a**Simple Moving Average Value** - At the same time, our cell E9 now also has the missing value presented of cell
**C9**.

**Download Practice Workbook**

Download this practice workbook below.

## Conclusion

To sum it up, the issue of how we can interpolate missing data in Excel is answered here by 4 different examples. For this problem, a workbook is available to download where you can practice these methods.

Feel free to ask any questions or feedback through the comment section.

## Related Articles

- How to Do Linear Interpolation in Excel
- How to Do Interpolation with GROWTH & TREND Functions in Excel
- How to Do VLOOKUP and Interpolate in Excel
- How to Interpolate Between Two Values in Excel
- How to Perform Bilinear Interpolation in Excel
- How to Use Non Linear Interpolation in Excel
- How to Interpolate in Excel Graph
- How to Do Linear Interpolation Excel VBA

**<< Go Back to Excel Interpolation | Excel for StatisticsÂ |Â Learn Excel**

How do you determine the value of the weight for method 3?

Hello

CYNTHIAThanks for visiting our blogs and sharing your queries. You want to know how to initialize the weight in the method 3. When investigating your problem, we found that the dataset we previously used does not suit the weighted moving average formula. So, we have modified the article (method 3) for better understanding.

When implementing a weighted moving average formula, it is better to fix the total weight first and distribute the weights among durations. So, please go to method 3 of this article again. Hopefully, you will not have any doubts. Good luck!

Regards

Lutfor Rahman ShimantoExcelDemy