64 lines
2.8 KiB
Markdown
64 lines
2.8 KiB
Markdown
---
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title: DataVec Transforms
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short_title: Transforms
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description: Data wrangling and mapping from one schema to another.
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category: DataVec
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weight: 1
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---
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## Data wrangling
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One of the key tools in DataVec is transformations. DataVec helps the user map a dataset from one schema to another, and provides a list of operations to convert types, format data, and convert a 2D dataset to sequence data.
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## Building a transform process
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A transform process requires a `Schema` to successfully transform data. Both schema and transform process classes come with a helper `Builder` class which are useful for organizing code and avoiding complex constructors.
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When both are combined together they look like the sample code below. Note how `inputDataSchema` is passed into the `Builder` constructor. Your transform process will fail to compile without it.
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```java
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import org.datavec.api.transform.TransformProcess;
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TransformProcess tp = new TransformProcess.Builder(inputDataSchema)
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.removeColumns("CustomerID","MerchantID")
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.filter(new ConditionFilter(new CategoricalColumnCondition("MerchantCountryCode", ConditionOp.NotInSet, new HashSet<>(Arrays.asList("USA","CAN")))))
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.conditionalReplaceValueTransform(
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"TransactionAmountUSD", //Column to operate on
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new DoubleWritable(0.0), //New value to use, when the condition is satisfied
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new DoubleColumnCondition("TransactionAmountUSD",ConditionOp.LessThan, 0.0)) //Condition: amount < 0.0
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.stringToTimeTransform("DateTimeString","YYYY-MM-DD HH:mm:ss.SSS", DateTimeZone.UTC)
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.renameColumn("DateTimeString", "DateTime")
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.transform(new DeriveColumnsFromTimeTransform.Builder("DateTime").addIntegerDerivedColumn("HourOfDay", DateTimeFieldType.hourOfDay()).build())
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.removeColumns("DateTime")
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.build();
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```
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## Executing a transformation
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Different "backends" for executors are available. Using the `tp` transform process above, here's how you can execute it locally using plain DataVec.
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```java
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import org.datavec.local.transforms.LocalTransformExecutor;
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List<List<Writable>> processedData = LocalTransformExecutor.execute(originalData, tp);
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```
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## Debugging
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Each operation in a transform process represents a "step" in schema changes. Sometimes, the resulting transformation is not the intended result. You can debug this by printing each step in the transform `tp` with the following:
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```java
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//Now, print the schema after each time step:
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int numActions = tp.getActionList().size();
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for(int i=0; i<numActions; i++ ){
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System.out.println("\n\n==================================================");
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System.out.println("-- Schema after step " + i + " (" + tp.getActionList().get(i) + ") --");
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System.out.println(tp.getSchemaAfterStep(i));
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}
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```
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## Available transformations and conversions
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{{autogenerated}} |