Crea un report

Questa guida spiega come creare un report di base per i dati di Analytics utilizzando l'API di dati di Google Analytics v1. I report dell'API di dati v1 sono simili ai report che puoi generare nella sezione Report dell'interfaccia utente di Google Analytics.

Questa guida illustra i principali report, la funzionalità generale di generazione dei report dell'API di dati. L'API di dati v1 dispone anche di report In tempo reale e report di canalizzazione specializzati.

runReport è il metodo consigliato per le query ed è utilizzato in tutti gli esempi della presente guida. Consulta le funzionalità avanzate per una panoramica degli altri metodi principali di generazione dei report. Prova a utilizzare Explorer query per testare le tue query.

Panoramica dei rapporti

I report sono tabelle di dati sugli eventi per una proprietà Google Analytics 4. Ogni tabella del report contiene le dimensioni e le metriche richieste nella query, con i dati in singole righe.

Utilizza i filtri per restituire solo le righe che corrispondono a una determinata condizione e la paginazione per spostarti tra i risultati.

Ecco una tabella di report di esempio che mostra una dimensione (Country) e una metrica (activeUsers):

Paese	Utenti attivi
Giappone	2541
Francia	12

Specifica un'origine dati

Ogni richiesta di runReport richiede di specificare un ID proprietà Google Analytics 4. La proprietà Analytics specificata viene utilizzata come set di dati per la query. Esempio:

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

La risposta di questa richiesta include solo i dati della proprietà Analytics specificata come GA4_PROPERTY_ID.

Se utilizzi le librerie client dell'API di dati, specifica l'origine dati nel parametro property, nel formato properties/GA4_PROPERTY_ID. Consulta la guida rapida per alcuni esempi di utilizzo delle librerie client.

Consulta Inviare eventi Measurement Protocol a Google Analytics se vuoi includere eventi Measurement Protocol nei report.

Generare un report

Per generare un report, crea un oggetto RunReportRequest. Ti consigliamo di iniziare con i seguenti parametri:

• Una voce valida nel campo dateRanges.
• Almeno una voce valida nel campo dimensions.
• Almeno una voce valida nel campo metrics.

Ecco una richiesta di esempio con i campi consigliati:

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/samples/RunReportSample.java

Apri in Cloud Shell Visualizza su GitHub

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

Apri in Cloud Shell Visualizza su GitHub

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

Query sulle metriche

Metrics sono le misurazioni quantitative dei dati degli eventi. Devi specificare almeno una metrica nelle richieste runReport.

Consulta Metriche API per un elenco completo delle metriche su cui puoi eseguire query.

Ecco una richiesta di esempio che mostra tre metriche, raggruppate per dimensione 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

google-analytics-data/src/main/java/com/google/analytics/data/samples/RunReportWithMultipleMetricsSample.java

Apri in Cloud Shell Visualizza su GitHub

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

Apri in Cloud Shell Visualizza su GitHub

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

Ecco una risposta di esempio che mostra 1135 utenti attivi, 512 nuovi utenti e 73,0841 entrate totali nella valuta della proprietà Analytics alla data 20231025 (25 ottobre 2023).

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

Leggi la risposta

La risposta al report contiene un'intestazione e righe di dati. L'intestazione è composta da DimensionHeaders e MetricHeaders, che elencano le colonne nel report. Ogni riga è composta da DimensionValues e MetricValues. L'ordine delle colonne è coerente nella richiesta, nell'intestazione e nelle righe.

Di seguito è riportato un esempio di risposta per la precedente richiesta di esempio:

{
  "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
}

Raggruppa e filtra i dati

Le dimensioni sono attributi qualitativi che puoi utilizzare per raggruppare e filtrare i dati. Ad esempio, la dimensione city indica la città, come Paris o New York, da cui ha avuto origine ogni evento. Le dimensioni sono facoltative per le richieste runReport e puoi utilizzare fino a nove dimensioni per richiesta.

Consulta Dimensioni API per un elenco completo delle dimensioni che puoi utilizzare per raggruppare e filtrare i dati.

Gruppo

Ecco una richiesta di esempio che raggruppa gli utenti attivi in tre dimensioni:

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/samples/RunReportWithMultipleDimensioniSample.java

Apri in Cloud Shell Visualizza su GitHub

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

Apri in Cloud Shell Visualizza su GitHub

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

Di seguito è riportato un esempio di riga del report per la richiesta precedente. Questa riga mostra che erano presenti 47 utenti attivi durante l'intervallo di date specificato con eventi a Città del Capo, in Sudafrica.

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

Filtro

Genera report con dati solo per valori di dimensione specifici. Per filtrare le dimensioni, specifica un FilterExpression nel campo dimensionFilter.

Ecco un esempio che restituisce un report sulle serie temporali di eventCount, quando eventName è first_open per ogni 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

google-analytics-data/src/main/java/com/google/analytics/data/samples/RunReportWithDimensionFilterSample.java

Apri in Cloud Shell Visualizza su GitHub

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

Apri in Cloud Shell Visualizza su GitHub

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

Ecco un altro esempio di FilterExpression, in cui andGroup include solo i dati che soddisfano tutti i criteri nell'elenco delle espressioni. Questo dimensionFilter seleziona quando entrambi browser è Chrome e countryId è US:

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/samples/RunReportWithMultipleDimensioneFiltriSample.java

Apri in Cloud Shell Visualizza su GitHub

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

Apri in Cloud Shell Visualizza su GitHub

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

Un elemento orGroup include i dati che soddisfano uno qualsiasi dei criteri nell'elenco delle espressioni.

Un elemento notExpression esclude i dati che corrispondono alla sua espressione interna. Ecco un dimensionFilter che restituisce i dati solo quando pageTitle non è My Homepage. Il report mostra i dati sugli eventi per ogni pageTitle diverso da My Homepage:

HTTP

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

Java

google-analytics-data/src/main/java/com/google/analytics/data/samples/RunReportWithSizeEscludiFilterSample.java

Apri in Cloud Shell Visualizza su GitHub

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

Apri in Cloud Shell Visualizza su GitHub

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

Un elemento inListFilter corrisponde ai dati di qualsiasi valore nell'elenco. Ecco un dimensionFilter che restituisce i dati sugli eventi in cui eventName è uno di purchase, in_app_purchase e app_store_subscription_renew:

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/samples/RunReportWithDimensioneInListFilterSample.java

Apri in Cloud Shell Visualizza su GitHub

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

Apri in Cloud Shell Visualizza su GitHub

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

Esplorare i report lunghi

Per impostazione predefinita, il report contiene solo le prime 10.000 righe di dati sugli eventi. Per visualizzare fino a 100.000 righe nel report, puoi includere "limit": 100000 in RunReportRequest.

Per i report con più di 100.000 righe, devi inviare una serie di richieste e sfogliare i risultati. Ad esempio, ecco una richiesta per le prime 100.000 righe:

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/samples/RunReportWithPaginationSample.java

Apri in Cloud Shell Visualizza su GitHub

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

Apri in Cloud Shell Visualizza su GitHub

    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

Il parametro rowCount nella risposta indica il numero totale di righe, indipendentemente dai valori limit e offset nella richiesta. Ad esempio, se la risposta mostra "rowCount": 272345, devi avere tre richieste con 100.000 righe,ognuna per recuperare tutti i dati.

Ecco una richiesta di esempio per le prossime 100.000 righe. Tutti gli altri parametri, come dateRange, dimensions e metrics, devono essere uguali a quelli della prima richiesta.

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/samples/RunReportWithPaginationSample.java

Apri in Cloud Shell Visualizza su GitHub

      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

Apri in Cloud Shell Visualizza su GitHub

    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

Puoi utilizzare i valori offset, ad esempio 200000 o 300000, per recuperare i risultati successivi. Tutti gli altri parametri, come dateRange, dimensions e metrics, devono essere uguali a quelli della prima richiesta.

Nota: la logica di impaginazione dell'API di dati è diversa dal semplice pattern di progettazione della paginazione di altre API di Google, a causa del formato tabulare delle risposte dell'API di dati.

Utilizzare più intervalli di date

Una richiesta di report può recuperare i dati per più dateRanges. Ad esempio, questo report mette a confronto le prime due settimane di agosto 2022 e 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

google-analytics-data/src/main/java/com/google/analytics/data/samples/RunReportWithDateRangesSample.java

Apri in Cloud Shell Visualizza su GitHub

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

Apri in Cloud Shell Visualizza su GitHub

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

Quando includi più dateRanges in una richiesta, alla risposta viene aggiunta automaticamente una colonna dateRange. Quando la colonna dateRange è date_range_0, i dati della riga si riferiscono al primo intervallo di date. Quando la colonna dateRange è date_range_1, i dati della riga si riferiscono al secondo intervallo di date.

Di seguito è riportato un esempio di risposta per due intervalli di date:

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

Passaggi successivi

Consulta le funzionalità avanzate e i report in tempo reale per una panoramica delle funzionalità di reporting più avanzate dell'API di dati v1.