Complex JSON processing

Importing Data in Java

Anthony Markham

VP Quant Developer

Complex JSON data

Nested objects and arrays
Mixed data types
Handling APIs and configuration files 🧠

Complex json data

Nested JSON objects

Nesting - objects within objects
Tablesaw can flatten simple cases automatically
Flattening - turning a column that contains lists or arrays in each row into multiple rows

{
  "customer": {
    "name": "John Doe",
    "address": {
      "street": "123 Main St",                            <- Nested information
      "city": "Boston",                                   <- Nested information
      "coordinates": {"lat": 42.3601, "lng": -71.0589}    <- Nested within nested information
    }
  }
}

JSON flattening

customer.name	customer.address.street	customer.address.city
John Doe	123 Main St	Boston

$ $

customer.address.coordinates.lat	customer.address.coordinates.lng
42.3601	-71.0589

JsonReader configuration

JsonReadOptions allows for:
- Source specification (file, URL, or string)
- Table name configuration
- Missing value handling

JsonReadOptions options = JsonReadOptions

    .builder("complex.json")

    .tableName("Products")

    .missingValueIndicator("N/A")

    .build();

Table data = new JsonReader().read(options);

missingValues = data.stringColumn("name").isMissing();

Joining tables

Use joinOn to join tables together
An inner join keeps only the rows that exist in both tables

Table phones = Table.read().csv("phones.csv");   // name, phone

Table diets  = Table.read().csv("diets.csv");    // name, diet


// Perform the inner join on the two tables
Table joined = phones.joinOn("name").inner(diets);

Many other types of joins exist

Let's practice!

Importing Data in Java