{
"test_id": "math_log",
"pyspark_version": "3.5",
"generated_at": "2025-10-27T14:13:12.244896",
"input_data": [
{
"id": 1,
"name": "Alice",
"age": 25,
"salary": 50000.0,
"active": true,
"email": "alice@example.com"
},
{
"id": 2,
"name": "Bob",
"age": 30,
"salary": 60000.0,
"active": false,
"email": "bob@test.com"
},
{
"id": 3,
"name": "Charlie",
"age": 35,
"salary": 70000.0,
"active": true,
"email": "charlie@company.org"
}
],
"operation": "DataFrame operation: math_log",
"expected_output": {
"schema": {
"field_count": 1,
"field_names": [
"ln(salary)"
],
"field_types": [
"double"
],
"fields": [
{
"name": "ln(salary)",
"type": "double",
"nullable": true
}
]
},
"data": [
{
"ln(salary)": 10.819778284410283
},
{
"ln(salary)": 11.002099841204238
},
{
"ln(salary)": 11.156250521031495
}
],
"row_count": 3
}
}