रिपोर्ट बनाना

इस गाइड में, Google Analytics Data API v1 का इस्तेमाल करके, Analytics डेटा के लिए बेसिक रिपोर्ट बनाने का तरीका बताया गया है. Data API v1 की रिपोर्ट, उन रिपोर्ट की तरह ही होती हैं जिन्हें Google Analytics यूज़र इंटरफ़ेस (यूआई) के रिपोर्ट सेक्शन में जनरेट किया जा सकता है.

इस गाइड में, Data API की सामान्य रिपोर्टिंग सुविधा और कोर रिपोर्टिंग के बारे में जानकारी दी गई है. Data API v1 में खास तौर पर रीयल टाइम रिपोर्टिंग और फ़नल रिपोर्टिंग की सुविधा भी मौजूद है.

क्वेरी के लिए runReport सुझाया गया तरीका है. इस गाइड में सभी उदाहरणों में इसका इस्तेमाल किया गया है. रिपोर्टिंग के अन्य मुख्य तरीकों की खास जानकारी के लिए, ऐडवांस सुविधाएं देखें. अपनी क्वेरी की जांच करने के लिए, क्वेरी एक्सप्लोरर आज़माएं.

Reports overview

रिपोर्ट, किसी Google Analytics 4 प्रॉपर्टी के लिए इवेंट डेटा की टेबल होती हैं. हर रिपोर्ट टेबल में, आपकी क्वेरी में अनुरोध किए गए डाइमेंशन और मेट्रिक होती हैं. साथ ही, उनका डेटा अलग-अलग पंक्तियों में होता है.

सिर्फ़ किसी खास शर्त से मैच करने वाली लाइनें दिखाने के लिए, फ़िल्टर का इस्तेमाल करें. साथ ही, नतीजों के हिसाब से नेविगेट करने के लिए, पेज पर नंबर डालना इस्तेमाल करें.

यहां सैंपल के तौर पर एक रिपोर्ट टेबल दी गई है, जो एक डाइमेंशन (Country) और एक मेट्रिक (activeUsers) दिखाती है:

देश सक्रिय उपयोगकर्ता
जापान 2541
फ़्रांस 12

कोई डेटा सोर्स चुनें

हर runReport अनुरोध के लिए, आपको एक Google Analytics 4 प्रॉपर्टी आईडी बताना होगा. आपकी बताई गई Analytics प्रॉपर्टी को उस क्वेरी के लिए डेटासेट के तौर पर इस्तेमाल किया जाता है. यहां एक उदाहरण दिया गया है:

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

इस अनुरोध के जवाब में सिर्फ़ उस Analytics प्रॉपर्टी का डेटा शामिल होता है जिसे आपने GA4_PROPERTY_ID के तौर पर बताया है.

अगर Data API क्लाइंट लाइब्रेरी का इस्तेमाल किया जाता है, तो डेटा सोर्स को property पैरामीटर में properties/GA4_PROPERTY_ID के तौर पर बताएं. क्लाइंट लाइब्रेरी को इस्तेमाल करने के उदाहरणों के लिए, आसानी से सिखाने वाली गाइड देखें.

अगर आपको अपनी रिपोर्ट में मेज़रमेंट प्रोटोकॉल इवेंट शामिल करना है, तो Google Analytics को मेज़रमेंट प्रोटोकॉल इवेंट भेजना लेख देखें.

रिपोर्ट जनरेट करें

रिपोर्ट जनरेट करने के लिए, RunReportRequest ऑब्जेक्ट बनाएं. हमारा सुझाव है कि आप नीचे दिए गए पैरामीटर से शुरू करें:

  • dateRanges फ़ील्ड में एक मान्य एंट्री डाली गई है.
  • dimensions फ़ील्ड में कम से कम एक मान्य एंट्री होनी चाहिए.
  • metrics फ़ील्ड में कम से कम एक मान्य एंट्री होनी चाहिए.

यहां सुझाए गए फ़ील्ड के साथ अनुरोध का एक सैंपल दिया गया है:

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/सैंपल/RunReportSample.java
Cloud Shell में खोलें GitHub पर देखें 
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
Cloud Shell में खोलें GitHub पर देखें 
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

मेट्रिक के लिए क्वेरी

Metrics आपके इवेंट डेटा के संख्यात्मक माप होते हैं. आपको अपने runReport अनुरोधों में कम से कम एक मेट्रिक तय करनी होगी.

क्वेरी की जा सकने वाली मेट्रिक की पूरी सूची के लिए, एपीआई मेट्रिक देखें.

यहां अनुरोध का एक नमूना दिया गया है, जिसमें तीन मेट्रिक दिखाई गई हैं. ये मेट्रिक, डाइमेंशन के हिसाब से ग्रुप में रखी गई हैं 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/sample/RunReportWith सुंदर मेट्रिक्ससैंपल.जावा
Cloud Shell में खोलें GitHub पर देखें 

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
Cloud Shell में खोलें GitHub पर देखें 
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

यहां जवाब का एक सैंपल दिया गया है, जिसमें 20231025 (25 अक्टूबर, 2023) को आपकी Analytics प्रॉपर्टी की मुद्रा में 1,135 सक्रिय उपयोगकर्ता, 512 नए उपयोगकर्ता, और 73.0841 कुल आय दिखती है.

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

जवाब पढ़ें

रिपोर्ट रिस्पॉन्स में एक हेडर और डेटा की लाइनें होती हैं. हेडर में DimensionHeaders और MetricHeaders होते हैं, जो रिपोर्ट में कॉलम की सूची बनाते हैं. हर लाइन में, DimensionValues और MetricValues शामिल हैं. कॉलम का क्रम अनुरोध, हेडर, और पंक्तियों में एक जैसा होता है.

सैंपल के लिए पिछले अनुरोध का सैंपल यहां दिया गया है:

{
  "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
}

डेटा को ग्रुप और फ़िल्टर करना

डाइमेंशन क्वालिटी वाले एट्रिब्यूट होते हैं. इनका इस्तेमाल डेटा को ग्रुप में बांटने और फ़िल्टर करने के लिए किया जा सकता है. उदाहरण के लिए, city डाइमेंशन से उस शहर का पता चलता है जहां से हर इवेंट शुरू हुआ था, जैसे कि Paris या New York से. runReport अनुरोधों के लिए डाइमेंशन ज़रूरी नहीं हैं. साथ ही, हर अनुरोध में ज़्यादा से ज़्यादा नौ डाइमेंशन इस्तेमाल किए जा सकते हैं.

उन डाइमेंशन की पूरी सूची देखने के लिए एपीआई डाइमेंशन देखें जिनका इस्तेमाल करके, डेटा का ग्रुप बनाया जा सकता है और उसे फ़िल्टर किया जा सकता है.

ग्रुप

यहां अनुरोध का एक उदाहरण दिया गया है, जो सक्रिय उपयोगकर्ताओं को तीन डाइमेंशन में ग्रुप करता है:

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

Cloud Shell में खोलें GitHub पर देखें 

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
Cloud Shell में खोलें GitHub पर देखें 
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

यहां पिछले अनुरोध के लिए, सैंपल रिपोर्ट लाइन दी गई है. इस लाइन में पता चलता है कि तारीख की तय सीमा के दौरान, दक्षिण अफ़्रीका के केप टाउन में इवेंट के दौरान 47 सक्रिय उपयोगकर्ता थे.

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

फ़िल्टर करें

सिर्फ़ खास डाइमेंशन वैल्यू के लिए, डेटा वाली रिपोर्ट जनरेट की जा सकती हैं. डाइमेंशन को फ़िल्टर करने के लिए, dimensionFilter फ़ील्ड में FilterExpression डालें.

यहां एक उदाहरण दिया गया है, जो eventCount की टाइम सीरीज़ रिपोर्ट दिखाता है, जब eventName हर date के लिए first_open होता है :

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

Cloud Shell में खोलें GitHub पर देखें 

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
Cloud Shell में खोलें GitHub पर देखें 
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

यहां FilterExpression का एक और उदाहरण दिया गया है. इसमें andGroup में सिर्फ़ ऐसा डेटा शामिल है जो एक्सप्रेशन की सूची की सभी शर्तों को पूरा करता है. यह dimensionFilter तब चुनता है, जब browser, Chrome और countryId, दोनों US हों:

HTTP

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

Java

Cloud Shell में खोलें GitHub पर देखें 

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
Cloud Shell में खोलें GitHub पर देखें 
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

orGroup में ऐसा डेटा शामिल होता है जो एक्सप्रेशन सूची की किसी भी शर्त को पूरा करता है.

notExpression अपने इनर एक्सप्रेशन से मैच करने वाला डेटा शामिल नहीं करता. यह dimensionFilter ऐसा है जो सिर्फ़ तब डेटा दिखाता है, जब pageTitle My Homepage न हो. इस रिपोर्ट में, My Homepage के अलावा हर pageTitle के लिए इवेंट डेटा दिखता है:

HTTP

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

Java

Cloud Shell में खोलें GitHub पर देखें 

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
Cloud Shell में खोलें GitHub पर देखें 
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

inListFilter, सूची की किसी भी वैल्यू के डेटा का मिलान करता है. यहां दिया गया dimensionFilter इवेंट डेटा दिखाता है, जहां eventName, purchase, in_app_purchase, और app_store_subscription_renew में से कोई एक है:

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/RunReportWithElementInListFilterTemplate.java
Cloud Shell में खोलें GitHub पर देखें 

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
Cloud Shell में खोलें GitHub पर देखें 
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

लंबी रिपोर्ट पर जाना

डिफ़ॉल्ट रूप से, रिपोर्ट में इवेंट डेटा की सिर्फ़ पहली 10,000 लाइनें होती हैं. रिपोर्ट में ज़्यादा से ज़्यादा 1,00,000 लाइनें देखने के लिए, "limit": 100000 को RunReportRequest में शामिल किया जा सकता है.

अगर रिपोर्ट में 1,00,000 से ज़्यादा लाइनें हैं, तो आपको नतीजों की सीरीज़ में कई अनुरोध भेजने होंगे और पेजों को शामिल करना होगा. उदाहरण के लिए, यहां शुरुआती 1,00,000 लाइनों के लिए अनुरोध दिया गया है:

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/सैंपल/RunReportWithPagnationSample.java
Cloud Shell में खोलें GitHub पर देखें 

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
Cloud Shell में खोलें GitHub पर देखें 
    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

रिस्पॉन्स में मौजूद rowCount पैरामीटर, लाइनों की कुल संख्या दिखाता है. यह अनुरोध में शामिल limit और offset की वैल्यू पर निर्भर नहीं करता है. उदाहरण के लिए, अगर जवाब में "rowCount": 272345 दिखता है, तो सारा डेटा फिर से पाने के लिए आपको 1,00,000 लाइनों के तीन अनुरोधों की ज़रूरत होगी.

यहां अगली 1,00,000 लाइनों के लिए अनुरोध का सैंपल दिया गया है. dateRange, dimensions, और metrics जैसे दूसरे सभी पैरामीटर पर दिए गए पहले अनुरोध जैसे ही होना चाहिए.

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/सैंपल/RunReportWithPagnationSample.java
Cloud Shell में खोलें GitHub पर देखें 
      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
Cloud Shell में खोलें GitHub पर देखें 
    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

बाद के नतीजे फिर से पाने के लिए, offset वैल्यू का इस्तेमाल किया जा सकता है, जैसे कि 200000 या 300000. dateRange, dimensions, और metrics जैसे दूसरे सभी पैरामीटर और पहले अनुरोध एक जैसे होने चाहिए.

एक से ज़्यादा तारीख की सीमाओं का इस्तेमाल करना

रिपोर्ट के एक ही अनुरोध से, एक से ज़्यादा dateRanges का डेटा वापस लाया जा सकता है. उदाहरण के लिए, इस रिपोर्ट में अगस्त 2022 और 2023 के पहले दो हफ़्तों की तुलना की गई है:

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
Cloud Shell में खोलें GitHub पर देखें 

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
Cloud Shell में खोलें GitHub पर देखें 
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

जब किसी अनुरोध में एक से ज़्यादा dateRanges शामिल किए जाते हैं, तो जवाब में dateRange कॉलम अपने-आप जुड़ जाता है. जब dateRange कॉलम date_range_0 पर सेट होता है, तो उस लाइन का डेटा तारीख की पहली सीमा के लिए होता है. जब dateRange कॉलम date_range_1 होता है, तो उस लाइन का डेटा, तारीख की दूसरी सीमा के लिए होता है.

यहां दो तारीख सीमाओं के लिए जवाब का सैंपल दिया गया है:

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

अगले चरण

Data API v1 की ज़्यादा बेहतर रिपोर्टिंग वाली सुविधाओं की खास जानकारी पाने के लिए, बेहतर सुविधाएं और रीयलटाइम रिपोर्टिंग देखें.