# Impute missing values

This task is to replace missing data in the data with estimated values based on selected method.

<figure><img src="https://1384254481-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FJVEESmJAPppJ3ijFq5aR%2Fuploads%2Fgit-blob-bffe1f71df592c93ebd14fd0bf7abec1cc31e0e0%2Fimage2023-8-28_15-51-25.png?alt=media" alt=""><figcaption><p>Figure 1. Select methods to replace missing values in the data</p></figcaption></figure>

First select the computation is based on samples/cells or features, and click **Finish** to replace missing values. Some functions will generate the same results no matter which transform option is selected, e.g. constant value. Others will generate different results:

* Constant values: specify a value to replace the missing data
* Maximum: use maximum value of samples/cells or features to replace missing data depends transform option
* Mean: use mean value of samples/cells or features to replace missing data depends transform option
* Median: use median value of samples/cells or features to replace missing data depends transform option
* Minimum: use minimum value of samples/cells or features to replace missing data depends transform option
* K-nearest neighbor (mean): specify number of neighbors (N), Euclidean metric is used to compute neighbors, use mean of (N) neighbors to replace missing data
* K-nearest neighbor (median): specify number of neighbors (N), Euclidean metric is used to compute neighbors, use median of (N) neighbors to replace missing data

## Additional Assistance

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