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# MLHandPoseClassifier.DataSource.labeledKeypointsDataFrame(_:sessionIdColumn:labelColumn:featureColumn:)

Creates a data source from a data frame of hand pose observations
that each contain the locations of each hand joint and an
annotation.

```
case labeledKeypointsDataFrame(DataFrame, sessionIdColumn: String = __Defaults.sessionIdColumnName, labelColumn: String = __Defaults.labelColumnName, featureColumn: String = __Defaults.featureColumnName)
```

## Discussion

- dataFrame: A data frame that contains the hand-joint locations and
  annotations for a set of hand poses.
- sessionIdColumn: The name of the column in the data frame that
  contains the hand pose session identifiers.
- labelColumn: The name of the column in the data frame that
  contains the hand pose label names.
- featureColumn: The name of the column in the data frame that
  contains the hand-joint location data. Each entry in the column must
  be a
  <doc://com.apple.documentation/documentation/TabularData/ShapedData>
  instance that contains three dimensions:
  - The first dimension has a size of one.
- The second dimension has three channels: the x-coordinate, the
  y-coordinate, and the confidence value, respectively. - The third
  dimension has 21 channels, one for each hand joint.

---

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