AI-generated Key Takeaways
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Data is structured in rows, each containing dimension values and metric values.
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Dimension values represent categorical data like eventName or countryId, stored as strings.
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Metric values represent quantitative data like eventCount, also stored as strings, with their type specified in the MetricHeader.
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Rows align with requested dimensions and metrics defined in the RunReportRequest.
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PivotReports only include dimension values for pivoted dimensions.
Report data for each row. For example if RunReportRequest contains:
"dimensions": [
{
"name": "eventName"
},
{
"name": "countryId"
}
],
"metrics": [
{
"name": "eventCount"
}
]
One row with 'in_app_purchase' as the eventName, 'JP' as the countryId, and 15 as the eventCount, would be:
"dimensionValues": [
{
"value": "in_app_purchase"
},
{
"value": "JP"
}
],
"metricValues": [
{
"value": "15"
}
]
JSON representation |
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{ "dimensionValues": [ { object ( |
Fields | |
---|---|
dimension |
List of requested dimension values. In a PivotReport, dimensionValues are only listed for dimensions included in a pivot. |
metric |
List of requested visible metric values. |
DimensionValue
The value of a dimension.
JSON representation |
---|
{ // Union field |
Fields | |
---|---|
Union field one_value . One kind of dimension value one_value can be only one of the following: |
|
value |
Value as a string if the dimension type is a string. |
MetricValue
The value of a metric.
JSON representation |
---|
{ // Union field |
Fields | |
---|---|
Union field one_value . One of metric value one_value can be only one of the following: |
|
value |
Measurement value. See MetricHeader for type. |