Cree un informe

En esta guía, se explica cómo crear un informe básico para tus datos de Analytics con la API de datos de Google Analytics v1. Los informes de la versión 1 de la API de datos son similares a los que puedes generar en la sección Informes de la IU de Google Analytics.

En esta guía, se abordan los informes principales, la función de informes general de la API de datos. La versión 1 de la API de datos también cuenta con informes de embudo y informes en tiempo real especializados.

runReport es el método recomendado para las consultas y se usa en todos los ejemplos de esta guía. Consulta las funciones avanzadas para obtener una descripción general de otros métodos principales de informes. Prueba el Explorador de consultas para probar tus consultas.

Reports overview

Los informes son tablas de datos de eventos de una propiedad Google Analytics 4. Cada tabla de informe tiene las dimensiones y métricas solicitadas en tu consulta, con los datos en filas individuales.

Usa los filtros para mostrar solo las filas que coincidan con una condición determinada y la paginación para navegar por los resultados.

A continuación, se incluye una tabla de informe de muestra en la que se muestra una dimensión (Country) y una métrica (activeUsers):

País Usuarios activos
Japón 2541
Francia 12

Cómo especificar una fuente de datos

Cada solicitud de runReport requiere que especifiques un ID de propiedad Google Analytics 4. La propiedad de Analytics que especifiques se usa como el conjunto de datos para esa consulta. Por ejemplo:

POST https://analyticsdata.googleapis.com/v1beta/properties/GA4_PROPERTY_ID:runReport

La respuesta de esta solicitud solo incluye los datos de la propiedad de Analytics que especificas como GA4_PROPERTY_ID.

Si usas las bibliotecas cliente de la API de datos, especifica la fuente de datos en el parámetro property con el formato properties/GA4_PROPERTY_ID. Consulta la guía de inicio rápido para obtener ejemplos del uso de las bibliotecas cliente.

Consulta Envía eventos del Protocolo de medición a Google Analytics si deseas incluir eventos del Protocolo de medición en tus informes.

Genera un informe

Para generar un informe, crea un objeto RunReportRequest. Te recomendamos comenzar con los siguientes parámetros:

  • Una entrada válida en el campo dateRanges
  • Al menos una entrada válida en el campo dimensions
  • Al menos una entrada válida en el campo metrics

Esta es una solicitud de ejemplo con los campos recomendados:

HTTP

POST https://analyticsdata.googleapis.com/v1beta/properties/GA4_PROPERTY_ID:runReport
  {
    "dateRanges": [{ "startDate": "2023-09-01"", "endDate": "2023-09-15" }],
    "dimensions": [{ "name": "country" }],
    "metrics": [{ "name": "activeUsers" }]
  }

Java

import com.google.analytics.data.v1beta.BetaAnalyticsDataClient;
import com.google.analytics.data.v1beta.DateRange;
import com.google.analytics.data.v1beta.Dimension;
import com.google.analytics.data.v1beta.DimensionHeader;
import com.google.analytics.data.v1beta.Metric;
import com.google.analytics.data.v1beta.MetricHeader;
import com.google.analytics.data.v1beta.Row;
import com.google.analytics.data.v1beta.RunReportRequest;
import com.google.analytics.data.v1beta.RunReportResponse;

/**
 * Google Analytics Data API sample application demonstrating the creation of a basic report.
 *
 * <p>See
 * https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/properties/runReport
 * for more information.
 *
 * <p>Before you start the application, please review the comments starting with "TODO(developer)"
 * and update the code to use correct values.
 *
 * <p>To run this sample using Maven:
 *
 * <pre>{@code
 * cd google-analytics-data
 * mvn compile exec:java -Dexec.mainClass="com.google.analytics.data.samples.RunReportSample"
 * }</pre>
 */
public class RunReportSample {

  public static void main(String... args) throws Exception {
    /**
     * TODO(developer): Replace this variable with your Google Analytics 4 property ID before
     * running the sample.
     */
    String propertyId = "YOUR-GA4-PROPERTY-ID";
    sampleRunReport(propertyId);
  }

  // Runs a report of active users grouped by country.
  static void sampleRunReport(String propertyId) throws Exception {

    // Using a default constructor instructs the client to use the credentials
    // specified in GOOGLE_APPLICATION_CREDENTIALS environment variable.
    try (BetaAnalyticsDataClient analyticsData = BetaAnalyticsDataClient.create()) {
      RunReportRequest request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDimensions(Dimension.newBuilder().setName("country"))
              .addMetrics(Metric.newBuilder().setName("activeUsers"))
              .addDateRanges(
                  DateRange.newBuilder().setStartDate("2020-09-01").setEndDate("2020-09-15"))
              .build();

      // Make the request.
      RunReportResponse response = analyticsData.runReport(request);
      printRunResponseResponse(response);
    }
  }

  // Prints results of a runReport call.
  static void printRunResponseResponse(RunReportResponse response) {
    System.out.printf("%s rows received%n", response.getRowsList().size());

    for (DimensionHeader header : response.getDimensionHeadersList()) {
      System.out.printf("Dimension header name: %s%n", header.getName());
    }

    for (MetricHeader header : response.getMetricHeadersList()) {
      System.out.printf("Metric header name: %s (%s)%n", header.getName(), header.getType());
    }

    System.out.println("Report result:");
    for (Row row : response.getRowsList()) {
      System.out.printf(
          "%s, %s%n", row.getDimensionValues(0).getValue(), row.getMetricValues(0).getValue());
    }
  }
}

Python

from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    DateRange,
    Dimension,
    Metric,
    MetricType,
    RunReportRequest,
)


def run_sample():
    """Runs the sample."""
    # TODO(developer): Replace this variable with your Google Analytics 4
    #  property ID before running the sample.
    property_id = "YOUR-GA4-PROPERTY-ID"
    run_report(property_id)


def run_report(property_id="YOUR-GA4-PROPERTY-ID"):
    """Runs a report of active users grouped by country."""
    client = BetaAnalyticsDataClient()

    request = RunReportRequest(
        property=f"properties/{property_id}",
        dimensions=[Dimension(name="country")],
        metrics=[Metric(name="activeUsers")],
        date_ranges=[DateRange(start_date="2020-09-01", end_date="2020-09-15")],
    )
    response = client.run_report(request)
    print_run_report_response(response)


def print_run_report_response(response):
    """Prints results of a runReport call."""
    print(f"{response.row_count} rows received")
    for dimensionHeader in response.dimension_headers:
        print(f"Dimension header name: {dimensionHeader.name}")
    for metricHeader in response.metric_headers:
        metric_type = MetricType(metricHeader.type_).name
        print(f"Metric header name: {metricHeader.name} ({metric_type})")

    print("Report result:")
    for rowIdx, row in enumerate(response.rows):
        print(f"\nRow {rowIdx}")
        for i, dimension_value in enumerate(row.dimension_values):
            dimension_name = response.dimension_headers[i].name
            print(f"{dimension_name}: {dimension_value.value}")

        for i, metric_value in enumerate(row.metric_values):
            metric_name = response.metric_headers[i].name
            print(f"{metric_name}: {metric_value.value}")


Cómo consultar métricas

Metrics son las mediciones cuantitativas de tus datos de eventos. Debes especificar al menos una métrica en tus solicitudes runReport.

Visita Métricas de API para obtener una lista completa de las métricas que puedes consultar.

A continuación, te mostramos una solicitud de ejemplo que muestra tres métricas, agrupadas por la dimensión date:

HTTP

POST https://analyticsdata.googleapis.com/v1beta/properties/GA4_PROPERTY_ID:runReport
  {
    "dateRanges": [{ "startDate": "7daysAgo", "endDate": "yesterday" }],
    "dimensions": [{ "name": "date" }],
    "metrics": [
      {
        "name": "activeUsers"
      },
      {
        "name": "newUsers"
      },
      {
        "name": "totalRevenue"
      }
    ],
  }

Java


import com.google.analytics.data.v1beta.BetaAnalyticsDataClient;
import com.google.analytics.data.v1beta.DateRange;
import com.google.analytics.data.v1beta.Dimension;
import com.google.analytics.data.v1beta.Metric;
import com.google.analytics.data.v1beta.RunReportRequest;
import com.google.analytics.data.v1beta.RunReportResponse;

/**
 * Google Analytics Data API sample application demonstrating the creation of a basic report.
 *
 * <p>See
 * https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/properties/runReport
 * for more information.
 *
 * <p>Before you start the application, please review the comments starting with "TODO(developer)"
 * and update the code to use correct values.
 *
 * <p>To run this sample using Maven:
 *
 * <pre>{@code
 * cd google-analytics-data
 * mvn compile exec:java -Dexec.mainClass="com.google.analytics.data.samples.RunReportWithMultipleMetricsSample"
 * }</pre>
 */
public class RunReportWithMultipleMetricsSample {

  public static void main(String... args) throws Exception {
    // TODO(developer): Replace with your Google Analytics 4 property ID before running the sample.
    String propertyId = "YOUR-GA4-PROPERTY-ID";
    sampleRunReportWithMultipleMetrics(propertyId);
  }

  // Runs a report of active users, new users and total revenue grouped by date dimension.
  static void sampleRunReportWithMultipleMetrics(String propertyId) throws Exception {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (BetaAnalyticsDataClient analyticsData = BetaAnalyticsDataClient.create()) {
      RunReportRequest request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDimensions(Dimension.newBuilder().setName("date"))
              .addMetrics(Metric.newBuilder().setName("activeUsers"))
              .addMetrics(Metric.newBuilder().setName("newUsers"))
              .addMetrics(Metric.newBuilder().setName("totalRevenue"))
              .addDateRanges(DateRange.newBuilder().setStartDate("7daysAgo").setEndDate("today"))
              .build();

      // Make the request.
      RunReportResponse response = analyticsData.runReport(request);
      // Prints the response using a method in RunReportSample.java
      RunReportSample.printRunResponseResponse(response);
    }
  }
}

Python

from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    DateRange,
    Dimension,
    Metric,
    RunReportRequest,
)

from run_report import print_run_report_response


def run_sample():
    """Runs the sample."""
    # TODO(developer): Replace this variable with your Google Analytics 4
    #  property ID before running the sample.
    property_id = "YOUR-GA4-PROPERTY-ID"
    run_report_with_multiple_metrics(property_id)


def run_report_with_multiple_metrics(property_id="YOUR-GA4-PROPERTY-ID"):
    """Runs a report of active users, new users and total revenue grouped by
    date dimension."""
    client = BetaAnalyticsDataClient()

    # Runs a report of active users grouped by three dimensions.
    request = RunReportRequest(
        property=f"properties/{property_id}",
        dimensions=[Dimension(name="date")],
        metrics=[
            Metric(name="activeUsers"),
            Metric(name="newUsers"),
            Metric(name="totalRevenue"),
        ],
        date_ranges=[DateRange(start_date="7daysAgo", end_date="today")],
    )
    response = client.run_report(request)
    print_run_report_response(response)


A continuación, verás una respuesta de ejemplo que muestra 1,135 usuarios activos, 512 usuarios nuevos y 73,0841 ingresos totales en la moneda de tu propiedad de Analytics en la fecha 20231025 (25 de octubre de 2023).

"rows": [
...
{
  "dimensionValues": [
    {
      "value": "20231025"
    }
  ],
  "metricValues": [
    {
      "value": "1135"
    },
    {
      "value": "512"
    },
    {
      "value": "73.0841"
    }
  ]
},
...
],

Leer la respuesta

La respuesta del informe contiene un encabezado y filas de datos. El encabezado consta de DimensionHeaders y MetricHeaders, que enumeran las columnas del informe. Cada fila consta de DimensionValues y MetricValues. El orden de las columnas es coherente en la solicitud, el encabezado y las filas.

A continuación, se incluye un ejemplo de respuesta para la solicitud de muestra anterior:

{
  "dimensionHeaders": [
    {
      "name": "country"
    }
  ],
  "metricHeaders": [
    {
      "name": "activeUsers",
      "type": "TYPE_INTEGER"
    }
  ],
  "rows": [
    {
      "dimensionValues": [
        {
          "value": "Japan"
        }
      ],
      "metricValues": [
        {
          "value": "2541"
        }
      ]
    },
    {
      "dimensionValues": [
        {
          "value": "France"
        }
      ],
      "metricValues": [
        {
          "value": "12"
        }
      ]
    }
  ],
  "metadata": {},
  "rowCount": 2
}

Agrupa y filtra datos

Las dimensiones son atributos cualitativos que puedes usar para agrupar y filtrar tus datos. Por ejemplo, la dimensión city indica la ciudad, como Paris o New York, donde se originó cada evento. Las dimensiones son opcionales para las solicitudes de runReport, y puedes usar hasta nueve por solicitud.

Consulta las dimensiones de la API para obtener una lista completa de las dimensiones que puedes usar para agrupar y filtrar tus datos.

Grupo

A continuación, se incluye una solicitud de ejemplo en la que se agrupan los usuarios activos en tres dimensiones:

HTTP

POST https://analyticsdata.googleapis.com/v1beta/properties/GA4_PROPERTY_ID:runReport
  {
    "dateRanges": [{ "startDate": "7daysAgo", "endDate": "yesterday" }],
    "dimensions": [
      {
        "name": "country"
      },
      {
        "name": "region"
      },
      {
        "name": "city"
      }
    ],
    "metrics": [{ "name": "activeUsers" }]
  }
  ```

Java


import com.google.analytics.data.v1beta.BetaAnalyticsDataClient;
import com.google.analytics.data.v1beta.DateRange;
import com.google.analytics.data.v1beta.Dimension;
import com.google.analytics.data.v1beta.Metric;
import com.google.analytics.data.v1beta.RunReportRequest;
import com.google.analytics.data.v1beta.RunReportResponse;

/**
 * Google Analytics Data API sample application demonstrating the creation of a basic report.
 *
 * <p>See
 * https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/properties/runReport
 * for more information.
 *
 * <p>Before you start the application, please review the comments starting with "TODO(developer)"
 * and update the code to use correct values.
 *
 * <p>To run this sample using Maven:
 *
 * <pre>{@code
 * cd google-analytics-data
 * mvn compile exec:java -Dexec.mainClass="com.google.analytics.data.samples.RunReportWithMultipleDimensionsSample"
 * }</pre>
 */
public class RunReportWithMultipleDimensionsSample {

  public static void main(String... args) throws Exception {
    // TODO(developer): Replace with your Google Analytics 4 property ID before running the sample.
    String propertyId = "YOUR-GA4-PROPERTY-ID";
    sampleRunReportWithMultipleDimensions(propertyId);
  }

  // Runs a report of active users grouped by three dimensions.
  static void sampleRunReportWithMultipleDimensions(String propertyId) throws Exception {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (BetaAnalyticsDataClient analyticsData = BetaAnalyticsDataClient.create()) {
      RunReportRequest request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDimensions(Dimension.newBuilder().setName("country"))
              .addDimensions(Dimension.newBuilder().setName("region"))
              .addDimensions(Dimension.newBuilder().setName("city"))
              .addMetrics(Metric.newBuilder().setName("activeUsers"))
              .addDateRanges(DateRange.newBuilder().setStartDate("7daysAgo").setEndDate("today"))
              .build();

      // Make the request.
      RunReportResponse response = analyticsData.runReport(request);
      // Prints the response using a method in RunReportSample.java
      RunReportSample.printRunResponseResponse(response);
    }
  }
}

Python

from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    DateRange,
    Dimension,
    Metric,
    RunReportRequest,
)

from run_report import print_run_report_response


def run_sample():
    """Runs the sample."""
    # TODO(developer): Replace this variable with your Google Analytics 4
    #  property ID before running the sample.
    property_id = "YOUR-GA4-PROPERTY-ID"
    run_report_with_multiple_dimensions(property_id)


def run_report_with_multiple_dimensions(property_id="YOUR-GA4-PROPERTY-ID"):
    """Runs a report of active users grouped by three dimensions."""
    client = BetaAnalyticsDataClient()

    request = RunReportRequest(
        property=f"properties/{property_id}",
        dimensions=[
            Dimension(name="country"),
            Dimension(name="region"),
            Dimension(name="city"),
        ],
        metrics=[Metric(name="activeUsers")],
        date_ranges=[DateRange(start_date="7daysAgo", end_date="today")],
    )
    response = client.run_report(request)
    print_run_report_response(response)


Esta es una fila de informe de muestra correspondiente a la solicitud anterior. En esta fila, se muestra que hubo 47 usuarios activos durante el período especificado con eventos de Ciudad del Cabo, Sudáfrica.

"rows": [
...
{
  "dimensionValues": [
    {
      "value": "South Africa"
    },
    {
      "value": "Western Cape"
    },
    {
      "value": "Cape Town"
    }
  ],
  "metricValues": [
    {
      "value": "47"
    }
  ]
},
...
],

Filtro

Generas informes con datos solo para valores de dimensiones específicos. Para filtrar las dimensiones, especifica un valor FilterExpression en el campo dimensionFilter.

A continuación, se incluye un ejemplo que muestra un informe de serie temporal de eventCount, cuando eventName es first_open para cada date :

HTTP

POST https://analyticsdata.googleapis.com/v1beta/properties/GA4_PROPERTY_ID:runReport
  {
    "dateRanges": [{ "startDate": "7daysAgo", "endDate": "yesterday" }],
    "dimensions": [{ "name": "date" }],
    "metrics": [{ "name": "eventCount" }],
    "dimensionFilter": {
      "filter": {
        "fieldName": "eventName",
        "stringFilter": {
          "value": "first_open"
        }
      }
    },
  }

Java


import com.google.analytics.data.v1beta.BetaAnalyticsDataClient;
import com.google.analytics.data.v1beta.DateRange;
import com.google.analytics.data.v1beta.Dimension;
import com.google.analytics.data.v1beta.Filter;
import com.google.analytics.data.v1beta.FilterExpression;
import com.google.analytics.data.v1beta.Metric;
import com.google.analytics.data.v1beta.RunReportRequest;
import com.google.analytics.data.v1beta.RunReportResponse;

/**
 * Google Analytics Data API sample application demonstrating the usage of dimension and metric
 * filters in a report.
 *
 * <p>See
 * https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/properties/runReport#body.request_body.FIELDS.dimension_filter
 * for more information.
 *
 * <p>Before you start the application, please review the comments starting with "TODO(developer)"
 * and update the code to use correct values.
 *
 * <p>To run this sample using Maven:
 *
 * <pre>{@code
 * cd google-analytics-data
 * mvn compile exec:java -Dexec.mainClass="com.google.analytics.data.samples.RunReportWithDimensionFilterSample"
 * }</pre>
 */
public class RunReportWithDimensionFilterSample {

  public static void main(String... args) throws Exception {
    // TODO(developer): Replace with your Google Analytics 4 property ID before running the sample.
    String propertyId = "YOUR-GA4-PROPERTY-ID";
    sampleRunReportWithDimensionFilter(propertyId);
  }

  // Runs a report using a dimension filter. The call returns a time series report of `eventCount`
  // when `eventName` is `first_open` for each date.
  // This sample uses relative date range values.
  // See https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/DateRange
  // for more information.
  static void sampleRunReportWithDimensionFilter(String propertyId) throws Exception {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (BetaAnalyticsDataClient analyticsData = BetaAnalyticsDataClient.create()) {
      RunReportRequest request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDimensions(Dimension.newBuilder().setName("date"))
              .addMetrics(Metric.newBuilder().setName("eventCount"))
              .addDateRanges(
                  DateRange.newBuilder().setStartDate("7daysAgo").setEndDate("yesterday"))
              .setDimensionFilter(
                  FilterExpression.newBuilder()
                      .setFilter(
                          Filter.newBuilder()
                              .setFieldName("eventName")
                              .setStringFilter(
                                  Filter.StringFilter.newBuilder().setValue("first_open"))))
              .build();

      // Make the request.
      RunReportResponse response = analyticsData.runReport(request);
      // Prints the response using a method in RunReportSample.java
      RunReportSample.printRunResponseResponse(response);
    }
  }
}

Python

from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    DateRange,
    Dimension,
    Filter,
    FilterExpression,
    Metric,
    RunReportRequest,
)

from run_report import print_run_report_response


def run_sample():
    """Runs the sample."""
    # TODO(developer): Replace this variable with your Google Analytics 4
    #  property ID before running the sample.
    property_id = "YOUR-GA4-PROPERTY-ID"
    run_report_with_dimension_filter(property_id)


def run_report_with_dimension_filter(property_id="YOUR-GA4-PROPERTY-ID"):
    """Runs a report using a dimension filter. The call returns a time series
    report of `eventCount` when `eventName` is `first_open` for each date.

    This sample uses relative date range values. See https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/DateRange
    for more information.
    """

    client = BetaAnalyticsDataClient()

    request = RunReportRequest(
        property=f"properties/{property_id}",
        dimensions=[Dimension(name="date")],
        metrics=[Metric(name="eventCount")],
        date_ranges=[DateRange(start_date="7daysAgo", end_date="yesterday")],
        dimension_filter=FilterExpression(
            filter=Filter(
                field_name="eventName",
                string_filter=Filter.StringFilter(value="first_open"),
            )
        ),
    )
    response = client.run_report(request)
    print_run_report_response(response)


Este es otro ejemplo de FilterExpression, en el que andGroup incluye solo los datos que cumplen con todos los criterios de la lista de expresiones. Este dimensionFilter selecciona para cuando browser es Chrome y countryId es US:

HTTP

...
"dimensionFilter": {
  "andGroup": {
    "expressions": [
      {
        "filter": {
          "fieldName": "browser",
          "stringFilter": {
            "value": "Chrome"
          }
        }
      },
      {
        "filter": {
          "fieldName": "countryId",
          "stringFilter": {
            "value": "US"
          }
        }
      }
    ]
  }
},
...

Java


import com.google.analytics.data.v1beta.BetaAnalyticsDataClient;
import com.google.analytics.data.v1beta.DateRange;
import com.google.analytics.data.v1beta.Dimension;
import com.google.analytics.data.v1beta.Filter;
import com.google.analytics.data.v1beta.FilterExpression;
import com.google.analytics.data.v1beta.FilterExpressionList;
import com.google.analytics.data.v1beta.Metric;
import com.google.analytics.data.v1beta.RunReportRequest;
import com.google.analytics.data.v1beta.RunReportResponse;

/**
 * Google Analytics Data API sample application demonstrating the usage of dimension and metric
 * filters in a report.
 *
 * <p>See
 * https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/properties/runReport#body.request_body.FIELDS.dimension_filter
 * for more information.
 *
 * <p>Before you start the application, please review the comments starting with "TODO(developer)"
 * and update the code to use correct values.
 *
 * <p>To run this sample using Maven:
 *
 * <pre>{@code
 * cd google-analytics-data
 * mvn compile exec:java -Dexec.mainClass="com.google.analytics.data.samples.RunReportWithMultipleDimensionFiltersSample"
 * }</pre>
 */
public class RunReportWithMultipleDimensionFiltersSample {

  public static void main(String... args) throws Exception {
    // TODO(developer): Replace with your Google Analytics 4 property ID before running the sample.
    String propertyId = "YOUR-GA4-PROPERTY-ID";
    sampleRunReportWithMultipleDimensionFilters(propertyId);
  }

  // Runs a report using multiple dimension filters joined as `and_group` expression. The filter
  // selects for when both `browser` is `Chrome` and `countryId` is `US`.
  // This sample uses relative date range values.
  // See https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/DateRange
  // for more information.
  static void sampleRunReportWithMultipleDimensionFilters(String propertyId) throws Exception {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (BetaAnalyticsDataClient analyticsData = BetaAnalyticsDataClient.create()) {
      RunReportRequest request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDimensions(Dimension.newBuilder().setName("browser"))
              .addMetrics(Metric.newBuilder().setName("activeUsers"))
              .addDateRanges(
                  DateRange.newBuilder().setStartDate("7daysAgo").setEndDate("yesterday"))
              .setDimensionFilter(
                  FilterExpression.newBuilder()
                      .setAndGroup(
                          FilterExpressionList.newBuilder()
                              .addExpressions(
                                  FilterExpression.newBuilder()
                                      .setFilter(
                                          Filter.newBuilder()
                                              .setFieldName("browser")
                                              .setStringFilter(
                                                  Filter.StringFilter.newBuilder()
                                                      .setValue("Chrome"))))
                              .addExpressions(
                                  FilterExpression.newBuilder()
                                      .setFilter(
                                          Filter.newBuilder()
                                              .setFieldName("countryId")
                                              .setStringFilter(
                                                  Filter.StringFilter.newBuilder()
                                                      .setValue("US"))))))
              .build();

      // Make the request.
      RunReportResponse response = analyticsData.runReport(request);
      // Prints the response using a method in RunReportSample.java
      RunReportSample.printRunResponseResponse(response);
    }
  }
}

Python

from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    DateRange,
    Dimension,
    Filter,
    FilterExpression,
    FilterExpressionList,
    Metric,
    RunReportRequest,
)

from run_report import print_run_report_response


def run_sample():
    """Runs the sample."""
    # TODO(developer): Replace this variable with your Google Analytics 4
    #  property ID before running the sample.
    property_id = "YOUR-GA4-PROPERTY-ID"
    run_report_with_multiple_dimension_filters(property_id)


def run_report_with_multiple_dimension_filters(property_id="YOUR-GA4-PROPERTY-ID"):
    """Runs a report using multiple dimension filters joined as `and_group`
    expression. The filter selects for when both `browser` is `Chrome` and
    `countryId` is `US`.

    This sample uses relative date range values. See https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/DateRange
    for more information.
    """
    client = BetaAnalyticsDataClient()

    request = RunReportRequest(
        property=f"properties/{property_id}",
        dimensions=[Dimension(name="browser")],
        metrics=[Metric(name="activeUsers")],
        date_ranges=[DateRange(start_date="7daysAgo", end_date="yesterday")],
        dimension_filter=FilterExpression(
            and_group=FilterExpressionList(
                expressions=[
                    FilterExpression(
                        filter=Filter(
                            field_name="browser",
                            string_filter=Filter.StringFilter(value="Chrome"),
                        )
                    ),
                    FilterExpression(
                        filter=Filter(
                            field_name="countryId",
                            string_filter=Filter.StringFilter(value="US"),
                        )
                    ),
                ]
            )
        ),
    )
    response = client.run_report(request)
    print_run_report_response(response)


Un orGroup incluye datos que cumplen con cualquiera de los criterios de la lista de expresiones.

Una notExpression excluye los datos que coinciden con su expresión interna. A continuación, se incluye un objeto dimensionFilter que muestra datos solo cuando pageTitle no es My Homepage. El informe muestra datos de eventos para cada pageTitle que no sea My Homepage:

HTTP

...
"dimensionFilter": {
  "notExpression": {
    "filter": {
      "fieldName": "pageTitle",
      "stringFilter": {
        "value": "My Homepage"
      }
    }
  }
},
...

Java


import com.google.analytics.data.v1beta.BetaAnalyticsDataClient;
import com.google.analytics.data.v1beta.DateRange;
import com.google.analytics.data.v1beta.Dimension;
import com.google.analytics.data.v1beta.Filter;
import com.google.analytics.data.v1beta.FilterExpression;
import com.google.analytics.data.v1beta.Metric;
import com.google.analytics.data.v1beta.RunReportRequest;
import com.google.analytics.data.v1beta.RunReportResponse;

/**
 * Google Analytics Data API sample application demonstrating the usage of dimension and metric
 * filters in a report.
 *
 * <p>See
 * https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/properties/runReport#body.request_body.FIELDS.dimension_filter
 * for more information.
 *
 * <p>Before you start the application, please review the comments starting with "TODO(developer)"
 * and update the code to use correct values.
 *
 * <p>To run this sample using Maven:
 *
 * <pre>{@code
 * cd google-analytics-data
 * mvn compile exec:java -Dexec.mainClass="com.google.analytics.data.samples.RunReportWithDimensionExcludeFilterSample"
 * }</pre>
 */
public class RunReportWithDimensionExcludeFilterSample {

  public static void main(String... args) throws Exception {
    // TODO(developer): Replace with your Google Analytics 4 property ID before running the sample.
    String propertyId = "YOUR-GA4-PROPERTY-ID";
    sampleRunReportWithDimensionExcludeFilter(propertyId);
  }

  // Runs a report using a filter with `not_expression`. The dimension filter selects for when
  // `pageTitle` is not `My Homepage`.
  // This sample uses relative date range values.
  // See https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/DateRange
  // for more information.
  static void sampleRunReportWithDimensionExcludeFilter(String propertyId) throws Exception {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (BetaAnalyticsDataClient analyticsData = BetaAnalyticsDataClient.create()) {
      RunReportRequest request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDimensions(Dimension.newBuilder().setName("pageTitle"))
              .addMetrics(Metric.newBuilder().setName("sessions"))
              .addDateRanges(
                  DateRange.newBuilder().setStartDate("7daysAgo").setEndDate("yesterday"))
              .setDimensionFilter(
                  FilterExpression.newBuilder()
                      .setNotExpression(
                          FilterExpression.newBuilder()
                              .setFilter(
                                  Filter.newBuilder()
                                      .setFieldName("pageTitle")
                                      .setStringFilter(
                                          Filter.StringFilter.newBuilder()
                                              .setValue("My Homepage")))))
              .build();

      // Make the request.
      RunReportResponse response = analyticsData.runReport(request);
      // Prints the response using a method in RunReportSample.java
      RunReportSample.printRunResponseResponse(response);
    }
  }
}

Python

from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    DateRange,
    Dimension,
    Filter,
    FilterExpression,
    Metric,
    RunReportRequest,
)

from run_report import print_run_report_response


def run_sample():
    """Runs the sample."""
    # TODO(developer): Replace this variable with your Google Analytics 4
    #  property ID before running the sample.
    property_id = "YOUR-GA4-PROPERTY-ID"
    run_report_with_dimension_exclude_filter(property_id)


def run_report_with_dimension_exclude_filter(property_id="YOUR-GA4-PROPERTY-ID"):
    """Runs a report using a filter with `not_expression`. The dimension filter
    selects for when `pageTitle` is not `My Homepage`.

    This sample uses relative date range values. See https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/DateRange
    for more information.
    """
    client = BetaAnalyticsDataClient()

    request = RunReportRequest(
        property=f"properties/{property_id}",
        dimensions=[Dimension(name="pageTitle")],
        metrics=[Metric(name="sessions")],
        date_ranges=[DateRange(start_date="7daysAgo", end_date="yesterday")],
        dimension_filter=FilterExpression(
            not_expression=FilterExpression(
                filter=Filter(
                    field_name="pageTitle",
                    string_filter=Filter.StringFilter(value="My Homepage"),
                )
            )
        ),
    )
    response = client.run_report(request)
    print_run_report_response(response)


Un elemento inListFilter coincide con los datos de cualquiera de los valores de la lista. Este es un objeto dimensionFilter que muestra datos de eventos, en los que eventName es cualquiera de los valores de purchase, in_app_purchase y app_store_subscription_renew:

HTTP

...
"dimensionFilter": {
    "filter": {
      "fieldName": "eventName",
      "inListFilter": {
        "values": ["purchase",
        "in_app_purchase",
        "app_store_subscription_renew"]
      }
    }
  },
...

Java


import com.google.analytics.data.v1beta.BetaAnalyticsDataClient;
import com.google.analytics.data.v1beta.DateRange;
import com.google.analytics.data.v1beta.Dimension;
import com.google.analytics.data.v1beta.Filter;
import com.google.analytics.data.v1beta.FilterExpression;
import com.google.analytics.data.v1beta.Metric;
import com.google.analytics.data.v1beta.RunReportRequest;
import com.google.analytics.data.v1beta.RunReportResponse;
import java.util.ArrayList;

/**
 * Google Analytics Data API sample application demonstrating the usage of dimension and metric
 * filters in a report.
 *
 * <p>See
 * https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/properties/runReport#body.request_body.FIELDS.dimension_filter
 * for more information.
 *
 * <p>Before you start the application, please review the comments starting with "TODO(developer)"
 * and update the code to use correct values.
 *
 * <p>To run this sample using Maven:
 *
 * <pre>{@code
 * cd google-analytics-data
 * mvn compile exec:java -Dexec.mainClass="com.google.analytics.data.samples.RunReportWithDimensionInListFilterSample"
 * }</pre>
 */
public class RunReportWithDimensionInListFilterSample {

  public static void main(String... args) throws Exception {
    // TODO(developer): Replace with your Google Analytics 4 property ID before running the sample.
    String propertyId = "YOUR-GA4-PROPERTY-ID";
    sampleRunReportWithDimensionInListFilter(propertyId);
  }

  // Runs a report using a dimension filter with `in_list_filter` expression. The filter selects for
  // when `eventName` is set to one of three event names specified in the query.
  // This sample uses relative date range values.
  // See https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/DateRange
  // for more information.
  static void sampleRunReportWithDimensionInListFilter(String propertyId) throws Exception {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (BetaAnalyticsDataClient analyticsData = BetaAnalyticsDataClient.create()) {
      RunReportRequest request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDimensions(Dimension.newBuilder().setName("eventName"))
              .addMetrics(Metric.newBuilder().setName("sessions"))
              .addDateRanges(
                  DateRange.newBuilder().setStartDate("7daysAgo").setEndDate("yesterday"))
              .setDimensionFilter(
                  FilterExpression.newBuilder()
                      .setFilter(
                          Filter.newBuilder()
                              .setFieldName("eventName")
                              .setInListFilter(
                                  Filter.InListFilter.newBuilder()
                                      .addAllValues(
                                          new ArrayList<String>() {
                                            {
                                              add("purchase");
                                              add("in_app_purchase");
                                              add("app_store_subscription_renew");
                                            }
                                          })
                                      .build())))
              .build();

      // Make the request.
      RunReportResponse response = analyticsData.runReport(request);
      // Prints the response using a method in RunReportSample.java
      RunReportSample.printRunResponseResponse(response);
    }
  }
}

Python

from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    DateRange,
    Dimension,
    Filter,
    FilterExpression,
    Metric,
    RunReportRequest,
)

from run_report import print_run_report_response


def run_sample():
    """Runs the sample."""
    # TODO(developer): Replace this variable with your Google Analytics 4
    #  property ID before running the sample.
    property_id = "YOUR-GA4-PROPERTY-ID"
    run_report_with_dimension_in_list_filter(property_id)


def run_report_with_dimension_in_list_filter(property_id="YOUR-GA4-PROPERTY-ID"):
    """Runs a report using a dimension filter with `in_list_filter` expression.
    The filter selects for when `eventName` is set to one of three event names
    specified in the query.

    This sample uses relative date range values. See https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/DateRange
    for more information.
    """
    client = BetaAnalyticsDataClient()

    request = RunReportRequest(
        property=f"properties/{property_id}",
        dimensions=[Dimension(name="eventName")],
        metrics=[Metric(name="sessions")],
        date_ranges=[DateRange(start_date="7daysAgo", end_date="yesterday")],
        dimension_filter=FilterExpression(
            filter=Filter(
                field_name="eventName",
                in_list_filter=Filter.InListFilter(
                    values=[
                        "purchase",
                        "in_app_purchase",
                        "app_store_subscription_renew",
                    ]
                ),
            )
        ),
    )
    response = client.run_report(request)
    print_run_report_response(response)


Cómo navegar por los informes extensos

De forma predeterminada, el informe contiene solo las primeras 10,000 filas de datos de eventos. Para ver hasta 1,000,000 filas en un informe, puedes incluir "limit": 100000 en RunReportRequest.

En el caso de los informes con más de 100,000 filas, debes enviar una serie de solicitudes y paginar los resultados. Por ejemplo, esta es una solicitud para las primeras 100,000 filas:

HTTP

POST https://analyticsdata.googleapis.com/v1beta/properties/GA4_PROPERTY_ID:runReport
  {
    ...
    "limit": 100000,
    "offset": 0
  }

Java


import com.google.analytics.data.v1beta.BetaAnalyticsDataClient;
import com.google.analytics.data.v1beta.DateRange;
import com.google.analytics.data.v1beta.Dimension;
import com.google.analytics.data.v1beta.Metric;
import com.google.analytics.data.v1beta.RunReportRequest;
import com.google.analytics.data.v1beta.RunReportResponse;

/**
 * Google Analytics Data API sample application demonstrating the use of pagination to retrieve
 * large result sets.
 *
 * <p>See
 * https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/properties/runReport#body.request_body.FIELDS.offset
 * for more information.
 *
 * <p>Before you start the application, please review the comments starting with "TODO(developer)"
 * and update the code to use correct values.
 *
 * <p>To run this sample using Maven:
 *
 * <pre>{@code
 * cd google-analytics-data
 * mvn compile exec:java -Dexec.mainClass="com.google.analytics.data.samples.RunReportWithPaginationSample"
 * }</pre>
 */
public class RunReportWithPaginationSample {

  public static void main(String... args) throws Exception {
    // TODO(developer): Replace with your Google Analytics 4 property ID before running the sample.
    String propertyId = "YOUR-GA4-PROPERTY-ID";
    sampleRunReportWithPagination(propertyId);
  }

  // Runs a report several times, each time retrieving a portion of result using pagination.
  static void sampleRunReportWithPagination(String propertyId) throws Exception {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (BetaAnalyticsDataClient analyticsData = BetaAnalyticsDataClient.create()) {
      RunReportRequest request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDateRanges(
                  DateRange.newBuilder().setStartDate("365daysAgo").setEndDate("yesterday"))
              .addDimensions(Dimension.newBuilder().setName("firstUserSource"))
              .addDimensions(Dimension.newBuilder().setName("firstUserMedium"))
              .addDimensions(Dimension.newBuilder().setName("firstUserCampaignName"))
              .addMetrics(Metric.newBuilder().setName("sessions"))
              .addMetrics(Metric.newBuilder().setName("conversions"))
              .addMetrics(Metric.newBuilder().setName("totalRevenue"))
              .setLimit(100000)
              .setOffset(0)
              .build();

      // Make the request.
      RunReportResponse response = analyticsData.runReport(request);
      RunReportSample.printRunResponseResponse(response);

      // Run the same report with a different offset value to retrieve the second page of a
      // response.
      request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDateRanges(
                  DateRange.newBuilder().setStartDate("365daysAgo").setEndDate("yesterday"))
              .addDimensions(Dimension.newBuilder().setName("firstUserSource"))
              .addDimensions(Dimension.newBuilder().setName("firstUserMedium"))
              .addDimensions(Dimension.newBuilder().setName("firstUserCampaignName"))
              .addMetrics(Metric.newBuilder().setName("sessions"))
              .addMetrics(Metric.newBuilder().setName("conversions"))
              .addMetrics(Metric.newBuilder().setName("totalRevenue"))
              .setLimit(100000)
              .setOffset(100000)
              .build();

      // Make the request.
      response = analyticsData.runReport(request);
      // Prints the response using a method in RunReportSample.java
      RunReportSample.printRunResponseResponse(response);
    }
  }
}

Python

    request = RunReportRequest(
        property=f"properties/{property_id}",
        date_ranges=[DateRange(start_date="365daysAgo", end_date="yesterday")],
        dimensions=[
            Dimension(name="firstUserSource"),
            Dimension(name="firstUserMedium"),
            Dimension(name="firstUserCampaignName"),
        ],
        metrics=[
            Metric(name="sessions"),
            Metric(name="conversions"),
            Metric(name="totalRevenue"),
        ],
        limit=100000,
        offset=0,
    )
    response = client.run_report(request)

El parámetro rowCount de la respuesta indica el número total de filas, independientemente de los valores limit y offset de la solicitud. Por ejemplo, si la respuesta muestra "rowCount": 272345, necesitas tres solicitudes de 100,000 filas cada una para recuperar todos los datos.

Esta es una solicitud de ejemplo para las próximas 100,000 filas. Todos los demás parámetros, como dateRange, dimensions y metrics, deben ser iguales a la primera solicitud.

HTTP

POST https://analyticsdata.googleapis.com/v1beta/properties/GA4_PROPERTY_ID:runReport
  {
    ...
    "limit": 100000,
    "offset": 100000
  }

Java

      request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDateRanges(
                  DateRange.newBuilder().setStartDate("365daysAgo").setEndDate("yesterday"))
              .addDimensions(Dimension.newBuilder().setName("firstUserSource"))
              .addDimensions(Dimension.newBuilder().setName("firstUserMedium"))
              .addDimensions(Dimension.newBuilder().setName("firstUserCampaignName"))
              .addMetrics(Metric.newBuilder().setName("sessions"))
              .addMetrics(Metric.newBuilder().setName("conversions"))
              .addMetrics(Metric.newBuilder().setName("totalRevenue"))
              .setLimit(100000)
              .setOffset(100000)
              .build();

      // Make the request.
      response = analyticsData.runReport(request);
      // Prints the response using a method in RunReportSample.java
      RunReportSample.printRunResponseResponse(response);

Python

    request = RunReportRequest(
        property=f"properties/{property_id}",
        date_ranges=[DateRange(start_date="365daysAgo", end_date="yesterday")],
        dimensions=[
            Dimension(name="firstUserSource"),
            Dimension(name="firstUserMedium"),
            Dimension(name="firstUserCampaignName"),
        ],
        metrics=[
            Metric(name="sessions"),
            Metric(name="conversions"),
            Metric(name="totalRevenue"),
        ],
        limit=100000,
        offset=100000,
    )
    response = client.run_report(request)

Puedes usar valores offset, por ejemplo, 200000 o 300000, para recuperar los resultados posteriores. Todos los demás parámetros, como dateRange, dimensions y metrics, deben ser iguales a la primera solicitud.

Utiliza varios períodos

Una solicitud de informe puede recuperar datos de varios dateRanges. Por ejemplo, en este informe, se comparan las dos primeras semanas de agosto de 2022 y de 2023:

HTTP

POST https://analyticsdata.googleapis.com/v1beta/properties/GA4_PROPERTY_ID:runReport
  {
    "dateRanges": [
      {
        "startDate": "2022-08-01",
        "endDate": "2022-08-14"
      },
      {
        "startDate": "2023-08-01",
        "endDate": "2023-08-14"
      }
    ],
    "dimensions": [{ "name": "platform" }],
    "metrics": [{ "name": "activeUsers" }]
  }

Java


import com.google.analytics.data.v1beta.BetaAnalyticsDataClient;
import com.google.analytics.data.v1beta.DateRange;
import com.google.analytics.data.v1beta.Dimension;
import com.google.analytics.data.v1beta.Metric;
import com.google.analytics.data.v1beta.RunReportRequest;
import com.google.analytics.data.v1beta.RunReportResponse;

/**
 * Google Analytics Data API sample application demonstrating the usage of date ranges in a report.
 *
 * <p>See
 * https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/properties/runReport#body.request_body.FIELDS.date_ranges
 * for more information.
 *
 * <p>Before you start the application, please review the comments starting with "TODO(developer)"
 * and update the code to use correct values.
 *
 * <p>To run this sample using Maven:
 *
 * <pre>{@code
 * cd google-analytics-data
 * mvn compile exec:java -Dexec.mainClass="com.google.analytics.data.samples.RunReportWithDateRangesSample"
 * }</pre>
 */
public class RunReportWithDateRangesSample {

  public static void main(String... args) throws Exception {
    // TODO(developer): Replace with your Google Analytics 4 property ID before running the sample.
    String propertyId = "YOUR-GA4-PROPERTY-ID";
    sampleRunReportWithDateRanges(propertyId);
  }

  // Runs a report using two date ranges.
  static void sampleRunReportWithDateRanges(String propertyId) throws Exception {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (BetaAnalyticsDataClient analyticsData = BetaAnalyticsDataClient.create()) {
      RunReportRequest request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDateRanges(
                  DateRange.newBuilder().setStartDate("2019-08-01").setEndDate("2019-08-14"))
              .addDateRanges(
                  DateRange.newBuilder().setStartDate("2020-08-01").setEndDate("2020-08-14"))
              .addDimensions(Dimension.newBuilder().setName("platform"))
              .addMetrics(Metric.newBuilder().setName("activeUsers"))
              .build();

      // Make the request.
      RunReportResponse response = analyticsData.runReport(request);
      // Prints the response using a method in RunReportSample.java
      RunReportSample.printRunResponseResponse(response);
    }
  }
}

Python

from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    DateRange,
    Dimension,
    Metric,
    RunReportRequest,
)

from run_report import print_run_report_response


def run_sample():
    """Runs the sample."""
    # TODO(developer): Replace this variable with your Google Analytics 4
    #  property ID before running the sample.
    property_id = "YOUR-GA4-PROPERTY-ID"
    run_report_with_date_ranges(property_id)


def run_report_with_date_ranges(property_id="YOUR-GA4-PROPERTY-ID"):
    """Runs a report using two date ranges."""
    client = BetaAnalyticsDataClient()

    request = RunReportRequest(
        property=f"properties/{property_id}",
        date_ranges=[
            DateRange(start_date="2019-08-01", end_date="2019-08-14"),
            DateRange(start_date="2020-08-01", end_date="2020-08-14"),
        ],
        dimensions=[Dimension(name="platform")],
        metrics=[Metric(name="activeUsers")],
    )
    response = client.run_report(request)
    print_run_report_response(response)


Cuando incluyes varios dateRanges en una solicitud, se agrega automáticamente una columna dateRange a la respuesta. Cuando la columna dateRange es date_range_0, los datos de esa fila corresponden al primer período. Cuando la columna dateRange es date_range_1, los datos de esa fila corresponden al segundo período.

A continuación, se incluye un ejemplo de respuesta para dos períodos:

{
  "dimensionHeaders": [
    {
      "name": "platform"
    },
    {
      "name": "dateRange"
    }
  ],
  "metricHeaders": [
    {
      "name": "activeUsers",
      "type": "TYPE_INTEGER"
    }
  ],
  "rows": [
    {
      "dimensionValues": [
        {
          "value": "iOS"
        },
        {
          "value": "date_range_0"
        }
      ],
      "metricValues": [
        {
          "value": "774"
        }
      ]
    },
    {
      "dimensionValues": [
        {
          "value": "Android"
        },
        {
          "value": "date_range_1"
        }
      ],
      "metricValues": [
        {
          "value": "335"
        }
      ]
    },
    ...
  ],
}

Próximos pasos

Consulta las funciones avanzadas y los informes en tiempo real para obtener una descripción general de las funciones de informes más avanzadas de la versión 1 de la API de datos.