Bericht erstellen

In diesem Leitfaden wird erläutert, wie Sie mit der Google Analytics Data API Version 1 einen einfachen Bericht für Ihre Analytics-Daten erstellen. Die Berichte aus der Data API Version 1 ähneln den Berichten, die Sie auf der Google Analytics-Benutzeroberfläche im Abschnitt Berichte erstellen können.

In diesem Leitfaden werden die wichtigsten Berichte – die allgemeine Berichtsfunktion der Data API – behandelt. Version 1 der Data API bietet außerdem spezielle Echtzeitberichte und Trichterberichte.

runReport ist die empfohlene Methode für Abfragen und wird in allen Beispielen in diesem Leitfaden verwendet. Einen Überblick über weitere grundlegende Berichtsmethoden finden Sie unter Erweiterte Funktionen. Testen Sie Ihre Abfragen mit dem Abfrage-Explorer.

Berichte und Messwerte

Berichte sind Tabellen mit Ereignisdaten für eine Google Analytics 4-Property. Jede Berichtstabelle enthält die Dimensionen und Messwerte, die in der Abfrage angefordert werden. Die Daten werden in einzelnen Zeilen dargestellt.

Verwenden Sie Filter, um nur Zeilen zurückzugeben, die einer bestimmten Bedingung entsprechen, und Paginierung, um durch die Ergebnisse zu navigieren.

Hier sehen Sie ein Beispiel für eine Berichtstabelle mit einer Dimension (Country) und einem Messwert (activeUsers):

Land Aktive Nutzer
Japan 2541
Frankreich 12

Datenquelle angeben

Für jede runReport-Anfrage müssen Sie eine Google Analytics 4-Property-ID angeben. Die angegebene Analytics-Property wird als Dataset für diese Abfrage verwendet. Beispiel:

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

Die Antwort auf diese Anfrage enthält nur Daten aus der Analytics-Property, die Sie als GA4_PROPERTY_ID angeben.

Wenn Sie die Data API-Clientbibliotheken verwenden, geben Sie die Datenquelle im Parameter property im Format properties/GA4_PROPERTY_ID an. Beispiele für die Verwendung der Clientbibliotheken finden Sie in der Kurzanleitung.

Wenn Sie Measurement Protocol-Ereignisse in Ihre Berichte aufnehmen möchten, finden Sie entsprechende Informationen unter Measurement Protocol-Ereignisse an Google Analytics senden.

Bericht generieren

Erstellen Sie ein RunReportRequest-Objekt, um einen Bericht zu generieren. Wir empfehlen, mit den folgenden Parametern zu beginnen:

  • Ein gültiger Eintrag im Feld dateRanges.
  • Das Feld dimensions enthält mindestens einen gültigen Eintrag.
  • Das Feld metrics muss mindestens einen gültigen Eintrag enthalten.

Hier ist eine Beispielanfrage mit den empfohlenen Feldern:

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

google-analytics-data/src/main/java/com/google/analytics/data/sample/RunReportSample.java
In Cloud Shell öffnen Auf GitHub ansehen 
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());
    }
  }
}
RunReportSample.java

Python

google-analytics-data/run_report.py
In Cloud Shell öffnen Auf GitHub ansehen 
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}")


run_report.py

Messwerte abfragen

Metrics sind die quantitativen Messungen Ihrer Ereignisdaten. Sie müssen in Ihren runReport-Anfragen mindestens einen Messwert angeben.

Eine vollständige Liste der abfragenden Messwerte finden Sie unter API-Messwerte.

In der folgenden Beispielanfrage werden drei Messwerte gruppiert nach der Dimension date angezeigt:

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

google-analytics-data/src/main/java/com/google/analytics/data/sample/RunReportWithMultipleMetricsSample.java
In Cloud Shell öffnen Auf GitHub ansehen 

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);
    }
  }
}
RunReportWithMultipleMetricsSample.java

Python

google-analytics-data/run_report_with_multiple_metrics.py
In Cloud Shell öffnen Auf GitHub ansehen 
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)


run_report_with_multiple_metrics.py

Die folgende Beispielantwort zeigt 1.135 aktive Nutzer, 512 neue Nutzer und 73,0841 Gesamtumsatz in der Währung Ihrer Analytics-Property für den 20231025 (25. Oktober 2023).

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

Antwort lesen

Die Berichtsantwort enthält eine Kopfzeile und Datenzeilen. Der Header besteht aus DimensionHeaders und MetricHeaders, die die Spalten des Berichts aufführen. Jede Zeile besteht aus DimensionValues und MetricValues. Die Reihenfolge der Spalten in der Anfrage, im Header und in den Zeilen ist einheitlich.

Hier eine Beispielantwort für die vorherige Beispielanfrage:

{
  "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
}

Daten gruppieren und filtern

Dimensionen sind qualitative Attribute, mit denen Sie Ihre Daten gruppieren und filtern können. Die Dimension city gibt beispielsweise die Stadt an, von der das Ereignis stammt, z. B. Paris oder New York. Dimensionen sind für runReport-Anfragen optional und Sie können bis zu neun Dimensionen pro Anfrage verwenden.

Eine vollständige Liste der Dimensionen zum Gruppieren und Filtern Ihrer Daten finden Sie unter API-Dimensionen.

Gruppe

In der folgenden Beispielanfrage werden aktive Nutzer in drei Dimensionen gruppiert:

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

google-analytics-data/src/main/java/com/google/analytics/data/sample/RunReportWithMultipleDimensionsSample.java
In Cloud Shell öffnen Auf GitHub ansehen 

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);
    }
  }
}
RunReportWithMultipleDimensionsSample.java

Python

google-analytics-data/run_report_with_multiple_dimensions.py
In Cloud Shell öffnen Auf GitHub ansehen 
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)


run_report_with_multiple_dimensions.py

Hier sehen Sie eine Beispielberichtszeile für die vorherige Anfrage. In dieser Zeile sehen Sie, dass es im angegebenen Zeitraum 47 aktive Nutzer mit Ereignissen aus Kapstadt in Südafrika gab.

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

Filtern

Berichte können nur mit Daten für bestimmte Dimensionswerte erstellt werden. Geben Sie zum Filtern von Dimensionen einen FilterExpression im Feld dimensionFilter an.

In diesem Beispiel wird ein Zeitachsenbericht von eventCount zurückgegeben, wobei eventName für jeden date den Wert first_open hat :

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

google-analytics-data/src/main/java/com/google/analytics/data/sample/RunReportWithDimensionFilterSample.java
In Cloud Shell öffnen Auf GitHub ansehen 

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);
    }
  }
}
RunReportWithDimensionFilterSample.java

Python

google-analytics-data/run_report_with_dimension_filter.py
In Cloud Shell öffnen Auf GitHub ansehen 
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)


run_report_with_dimension_filter.py

Hier ein weiteres FilterExpression-Beispiel, in dem andGroup nur Daten enthält, die allen Kriterien in der Ausdrucksliste entsprechen. Dies dimensionFilter wählt aus, wenn sowohl browser Chrome als auch countryId US ist:

HTTP

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

Java

google-analytics-data/src/main/java/com/google/analytics/data/sample/RunReportWithMultipleDimensionFiltersSample.java
In Cloud Shell öffnen Auf GitHub ansehen 

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);
    }
  }
}
RunReportWithMultipleDimensionFiltersSample.java

Python

google-analytics-data/run_report_with_multiple_dimension_filters.py
In Cloud Shell öffnen Auf GitHub ansehen 
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)


run_report_with_multiple_dimension_filters.py

Ein orGroup enthält Daten, die einem der Kriterien in der Ausdrucksliste entsprechen.

Ein notExpression schließt Daten aus, die mit seinem inneren Ausdruck übereinstimmen. Hier ist ein dimensionFilter, das nur dann Daten zurückgibt, wenn pageTitle nicht My Homepage ist. Der Bericht enthält Ereignisdaten für alle pageTitle außer My Homepage:

HTTP

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

Java

google-analytics-data/src/main/java/com/google/analytics/data/sample/RunReportWithDimensionExtractFilterSample.java
In Cloud Shell öffnen Auf GitHub ansehen 

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);
    }
  }
}
RunReportWithDimensionExcludeFilterSample.java

Python

google-analytics-data/run_report_with_dimension_exclude_filter.py
In Cloud Shell öffnen Auf GitHub ansehen 
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)


run_report_with_dimension_exclude_filter.py

Ein inListFilter gleicht Daten für einen der Werte in der Liste ab. Hier sehen Sie ein dimensionFilter, das Ereignisdaten zurückgibt, wobei eventName entweder purchase, in_app_purchase oder app_store_subscription_renew ist:

HTTP

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

Java

google-analytics-data/src/main/java/com/google/analytics/data/sample/RunReportWithDimensionInListFilterSample.java
In Cloud Shell öffnen Auf GitHub ansehen 

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);
    }
  }
}
RunReportWithDimensionInListFilterSample.java

Python

google-analytics-data/run_report_with_dimension_in_list_filter.py
In Cloud Shell öffnen Auf GitHub ansehen 
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)


run_report_with_dimension_in_list_filter.py

Zwischen langen Berichten wechseln

Standardmäßig enthält der Bericht nur die ersten 10.000 Zeilen mit Ereignisdaten. Wenn der Bericht bis zu 100.000 Zeilen enthalten soll, können Sie "limit": 100000 in die RunReportRequest einfügen.

Bei Berichten mit mehr als 100.000 Zeilen müssen Sie eine Reihe von Anfragen senden und durch die Ergebnisse blättern. Hier ist beispielsweise eine Anfrage für die ersten 100.000 Zeilen:

HTTP

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

Java

google-analytics-data/src/main/java/com/google/analytics/data/sample/RunReportWithPaginationSample.java
In Cloud Shell öffnen Auf GitHub ansehen 

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);
    }
  }
}
RunReportWithPaginationSample.java

Python

google-analytics-data/run_report_with_pagination.py
In Cloud Shell öffnen Auf GitHub ansehen 
    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)
run_report_with_pagination.py

Der Parameter rowCount in der Antwort gibt die Gesamtzahl der Zeilen unabhängig von den Werten limit und offset in der Anfrage an. Wenn in der Antwort beispielsweise "rowCount": 272345 angezeigt wird, benötigen Sie drei Anfragen mit jeweils 100.000 Zeilen, um alle Daten abzurufen.

Hier ist eine Beispielanfrage für die nächsten 100.000 Zeilen. Alle anderen Parameter wie dateRange, dimensions und metrics sollten mit der ersten Anfrage übereinstimmen.

HTTP

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

Java

google-analytics-data/src/main/java/com/google/analytics/data/sample/RunReportWithPaginationSample.java
In Cloud Shell öffnen Auf GitHub ansehen 
      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);
RunReportWithPaginationSample.java

Python

google-analytics-data/run_report_with_pagination.py
In Cloud Shell öffnen Auf GitHub ansehen 
    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)
run_report_with_pagination.py

Sie können offset-Werte wie 200000 oder 300000 verwenden, um nachfolgende Ergebnisse abzurufen. Alle anderen Parameter wie dateRange, dimensions und metrics sollten mit der ersten Anfrage übereinstimmen.

Mehrere Zeiträume verwenden

Mit einer Berichtsanfrage können Daten für mehrere dateRanges abgerufen werden. In diesem Bericht werden beispielsweise die ersten beiden Wochen für August 2022 und 2023 verglichen:

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

google-analytics-data/src/main/java/com/google/analytics/data/sample/RunReportWithDateRangesSample.java
In Cloud Shell öffnen Auf GitHub ansehen 

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);
    }
  }
}
RunReportWithDateRangesSample.java

Python

google-analytics-data/run_report_with_date_ranges.py
In Cloud Shell öffnen Auf GitHub ansehen 
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)


run_report_with_date_ranges.py

Wenn Sie mehrere dateRanges in eine Anfrage einbeziehen, wird der Antwort automatisch eine dateRange-Spalte hinzugefügt. Wenn die Spalte dateRange den Wert date_range_0 hat, beziehen sich die Daten in dieser Zeile auf den ersten Zeitraum. Wenn die Spalte dateRange den Wert date_range_1 hat, beziehen sich die Daten dieser Zeile auf den zweiten Zeitraum.

Hier ist eine Beispielantwort für zwei Zeiträume:

{
  "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"
        }
      ]
    },
    ...
  ],
}

Nächste Schritte

Einen Überblick über die erweiterten Berichtsfunktionen der Data API Version 1 finden Sie unter Erweiterte Funktionen und Echtzeitberichte.