# Impute missing values

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

<div align="left"><figure><img src="https://580316046-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FWMxqQAMFOJtu98OBk9KN%2Fuploads%2Fgit-blob-4bda0911e9bb87bad821656813bd549611620037%2Fimage%20(83).png?alt=media" alt="" width="563"><figcaption></figcaption></figure></div>

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