> For the complete documentation index, see [llms.txt](https://george-jen.gitbook.io/data-science-and-apache-spark/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://george-jen.gitbook.io/data-science-and-apache-spark/indextostring.md).

# IndexToString

Symmetrically to StringIndexer, IndexToString maps a column of label indices back to a column containing the original labels as strings. A common use case is to produce indices from labels with StringIndexer, train a model with those indices and retrieve the original labels from the column of predicted indices with IndexToString. However, you are free to supply your own labels.

Examples

Building on the StringIndexer example, let’s assume we have the following DataFrame with columns id and categoryIndex:

| id | categoryIndex |
| -- | ------------- |
| 0  | 0.0           |
| 1  | 2.0           |
| 2  | 1.0           |
| 3  | 0.0           |
| 4  | 0.0           |
| 5  | 1.0           |

Applying IndexToString with categoryIndex as the input column, originalCategory as the output column, we are able to retrieve our original labels (they will be inferred from the columns’ metadata):

| id | categoryIndex | originalCategory |
| -- | ------------- | ---------------- |
| 0  | 0.0           | a                |
| 1  | 2.0           | b                |
| 2  | 1.0           | c                |
| 3  | 0.0           | a                |
| 4  | 0.0           | a                |
| 5  | 1.0           | c                |

```
import org.apache.spark.ml.attribute.Attribute
import org.apache.spark.ml.feature.{IndexToString, StringIndexer}

val df = spark.createDataFrame(Seq(
  (0, "a"),
  (1, "b"),
  (2, "c"),
  (3, "a"),
  (4, "a"),
  (5, "c")
)).toDF("id", "category")

val indexer = new StringIndexer()
  .setInputCol("category")
  .setOutputCol("categoryIndex")
  .fit(df)
val indexed = indexer.transform(df)

println(s"Transformed string column '${indexer.getInputCol}' " +
    s"to indexed column '${indexer.getOutputCol}'")
indexed.show()

val inputColSchema = indexed.schema(indexer.getOutputCol)
println(s"StringIndexer will store labels in output column metadata: " +
    s"${Attribute.fromStructField(inputColSchema).toString}\n")

val converter = new IndexToString()
  .setInputCol("categoryIndex")
  .setOutputCol("originalCategory")

val converted = converter.transform(indexed)

println(s"Transformed indexed column '${converter.getInputCol}' back to original string " +
    s"column '${converter.getOutputCol}' using labels in metadata")
converted.select("id", "categoryIndex", "originalCategory").show()

/*
Output:

Transformed string column 'category' to indexed column 'categoryIndex'
+---+--------+-------------+
| id|category|categoryIndex|
+---+--------+-------------+
|  0|       a|          0.0|
|  1|       b|          2.0|
|  2|       c|          1.0|
|  3|       a|          0.0|
|  4|       a|          0.0|
|  5|       c|          1.0|
+---+--------+-------------+

StringIndexer will store labels in output column metadata: {"vals":["a","c","b"],"type":"nominal","name":"categoryIndex"}

Transformed indexed column 'categoryIndex' back to original string column 'originalCategory' using labels in metadata
+---+-------------+----------------+
| id|categoryIndex|originalCategory|
+---+-------------+----------------+
|  0|          0.0|               a|
|  1|          2.0|               b|
|  2|          1.0|               c|
|  3|          0.0|               a|
|  4|          0.0|               a|
|  5|          1.0|               c|
+---+-------------+----------------+

*/
```


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://george-jen.gitbook.io/data-science-and-apache-spark/indextostring.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.