Returns the Analytics data.
batchGet(body, x__xgafv=None)
Returns the Analytics data.
Args:
body: object, The request body. (required)
The object takes the form of:
{ # The batch request containing multiple report request.
"reportRequests": [ # Requests, each request will have a separate response.
# There can be a maximum of 5 requests. All requests should have the same
# `dateRanges`, `viewId`, `segments`, `samplingLevel`, and `cohortGroup`.
{ # The main request class which specifies the Reporting API request.
"pivots": [ # The pivot definitions. Requests can have a maximum of 2 pivots.
{ # The Pivot describes the pivot section in the request.
# The Pivot helps rearrange the information in the table for certain reports
# by pivoting your data on a second dimension.
"metrics": [ # The pivot metrics. Pivot metrics are part of the
# restriction on total number of metrics allowed in the request.
{ # [Metrics](https://support.google.com/analytics/answer/1033861)
# are the quantitative measurements. For example, the metric `ga:users`
# indicates the total number of users for the requested time period.
"alias": "A String", # An alias for the metric expression is an alternate name for the
# expression. The alias can be used for filtering and sorting. This field
# is optional and is useful if the expression is not a single metric but
# a complex expression which cannot be used in filtering and sorting.
# The alias is also used in the response column header.
"expression": "A String", # A metric expression in the request. An expression is constructed from one
# or more metrics and numbers. Accepted operators include: Plus (+), Minus
# (-), Negation (Unary -), Divided by (/), Multiplied by (*), Parenthesis,
# Positive cardinal numbers (0-9), can include decimals and is limited to
# 1024 characters. Example `ga:totalRefunds/ga:users`, in most cases the
# metric expression is just a single metric name like `ga:users`.
# Adding mixed `MetricType` (E.g., `CURRENCY` + `PERCENTAGE`) metrics
# will result in unexpected results.
"formattingType": "A String", # Specifies how the metric expression should be formatted, for example
# `INTEGER`.
},
],
"maxGroupCount": 42, # Specifies the maximum number of groups to return.
# The default value is 10, also the maximum value is 1,000.
"dimensions": [ # A list of dimensions to show as pivot columns. A Pivot can have a maximum
# of 4 dimensions. Pivot dimensions are part of the restriction on the
# total number of dimensions allowed in the request.
{ # [Dimensions](https://support.google.com/analytics/answer/1033861)
# are attributes of your data. For example, the dimension `ga:city`
# indicates the city, for example, "Paris" or "New York", from which
# a session originates.
"name": "A String", # Name of the dimension to fetch, for example `ga:browser`.
"histogramBuckets": [ # If non-empty, we place dimension values into buckets after string to
# int64. Dimension values that are not the string representation of an
# integral value will be converted to zero. The bucket values have to be in
# increasing order. Each bucket is closed on the lower end, and open on the
# upper end. The "first" bucket includes all values less than the first
# boundary, the "last" bucket includes all values up to infinity. Dimension
# values that fall in a bucket get transformed to a new dimension value. For
# example, if one gives a list of "0, 1, 3, 4, 7", then we return the
# following buckets:
#
# - bucket #1: values < 0, dimension value "<0"
# - bucket #2: values in [0,1), dimension value "0"
# - bucket #3: values in [1,3), dimension value "1-2"
# - bucket #4: values in [3,4), dimension value "3"
# - bucket #5: values in [4,7), dimension value "4-6"
# - bucket #6: values >= 7, dimension value "7+"
#
# NOTE: If you are applying histogram mutation on any dimension, and using
# that dimension in sort, you will want to use the sort type
# `HISTOGRAM_BUCKET` for that purpose. Without that the dimension values
# will be sorted according to dictionary
# (lexicographic) order. For example the ascending dictionary order is:
#
# "<50", "1001+", "121-1000", "50-120"
#
# And the ascending `HISTOGRAM_BUCKET` order is:
#
# "<50", "50-120", "121-1000", "1001+"
#
# The client has to explicitly request `"orderType": "HISTOGRAM_BUCKET"`
# for a histogram-mutated dimension.
"A String",
],
},
],
"dimensionFilterClauses": [ # DimensionFilterClauses are logically combined with an `AND` operator: only
# data that is included by all these DimensionFilterClauses contributes to
# the values in this pivot region. Dimension filters can be used to restrict
# the columns shown in the pivot region. For example if you have
# `ga:browser` as the requested dimension in the pivot region, and you
# specify key filters to restrict `ga:browser` to only "IE" or "Firefox",
# then only those two browsers would show up as columns.
{ # A group of dimension filters. Set the operator value to specify how
# the filters are logically combined.
"operator": "A String", # The operator for combining multiple dimension filters. If unspecified, it
# is treated as an `OR`.
"filters": [ # The repeated set of filters. They are logically combined based on the
# operator specified.
{ # Dimension filter specifies the filtering options on a dimension.
"dimensionName": "A String", # The dimension to filter on. A DimensionFilter must contain a dimension.
"operator": "A String", # How to match the dimension to the expression. The default is REGEXP.
"expressions": [ # Strings or regular expression to match against. Only the first value of
# the list is used for comparison unless the operator is `IN_LIST`.
# If `IN_LIST` operator, then the entire list is used to filter the
# dimensions as explained in the description of the `IN_LIST` operator.
"A String",
],
"not": True or False, # Logical `NOT` operator. If this boolean is set to true, then the matching
# dimension values will be excluded in the report. The default is false.
"caseSensitive": True or False, # Should the match be case sensitive? Default is false.
},
],
},
],
"startGroup": 42, # If k metrics were requested, then the response will contain some
# data-dependent multiple of k columns in the report. E.g., if you pivoted
# on the dimension `ga:browser` then you'd get k columns for "Firefox", k
# columns for "IE", k columns for "Chrome", etc. The ordering of the groups
# of columns is determined by descending order of "total" for the first of
# the k values. Ties are broken by lexicographic ordering of the first
# pivot dimension, then lexicographic ordering of the second pivot
# dimension, and so on. E.g., if the totals for the first value for
# Firefox, IE, and Chrome were 8, 2, 8, respectively, the order of columns
# would be Chrome, Firefox, IE.
#
# The following let you choose which of the groups of k columns are
# included in the response.
},
],
"hideTotals": True or False, # If set to true, hides the total of all metrics for all the matching rows,
# for every date range. The default false and will return the totals.
"metrics": [ # The metrics requested.
# Requests must specify at least one metric. Requests can have a
# total of 10 metrics.
{ # [Metrics](https://support.google.com/analytics/answer/1033861)
# are the quantitative measurements. For example, the metric `ga:users`
# indicates the total number of users for the requested time period.
"alias": "A String", # An alias for the metric expression is an alternate name for the
# expression. The alias can be used for filtering and sorting. This field
# is optional and is useful if the expression is not a single metric but
# a complex expression which cannot be used in filtering and sorting.
# The alias is also used in the response column header.
"expression": "A String", # A metric expression in the request. An expression is constructed from one
# or more metrics and numbers. Accepted operators include: Plus (+), Minus
# (-), Negation (Unary -), Divided by (/), Multiplied by (*), Parenthesis,
# Positive cardinal numbers (0-9), can include decimals and is limited to
# 1024 characters. Example `ga:totalRefunds/ga:users`, in most cases the
# metric expression is just a single metric name like `ga:users`.
# Adding mixed `MetricType` (E.g., `CURRENCY` + `PERCENTAGE`) metrics
# will result in unexpected results.
"formattingType": "A String", # Specifies how the metric expression should be formatted, for example
# `INTEGER`.
},
],
"dimensions": [ # The dimensions requested.
# Requests can have a total of 7 dimensions.
{ # [Dimensions](https://support.google.com/analytics/answer/1033861)
# are attributes of your data. For example, the dimension `ga:city`
# indicates the city, for example, "Paris" or "New York", from which
# a session originates.
"name": "A String", # Name of the dimension to fetch, for example `ga:browser`.
"histogramBuckets": [ # If non-empty, we place dimension values into buckets after string to
# int64. Dimension values that are not the string representation of an
# integral value will be converted to zero. The bucket values have to be in
# increasing order. Each bucket is closed on the lower end, and open on the
# upper end. The "first" bucket includes all values less than the first
# boundary, the "last" bucket includes all values up to infinity. Dimension
# values that fall in a bucket get transformed to a new dimension value. For
# example, if one gives a list of "0, 1, 3, 4, 7", then we return the
# following buckets:
#
# - bucket #1: values < 0, dimension value "<0"
# - bucket #2: values in [0,1), dimension value "0"
# - bucket #3: values in [1,3), dimension value "1-2"
# - bucket #4: values in [3,4), dimension value "3"
# - bucket #5: values in [4,7), dimension value "4-6"
# - bucket #6: values >= 7, dimension value "7+"
#
# NOTE: If you are applying histogram mutation on any dimension, and using
# that dimension in sort, you will want to use the sort type
# `HISTOGRAM_BUCKET` for that purpose. Without that the dimension values
# will be sorted according to dictionary
# (lexicographic) order. For example the ascending dictionary order is:
#
# "<50", "1001+", "121-1000", "50-120"
#
# And the ascending `HISTOGRAM_BUCKET` order is:
#
# "<50", "50-120", "121-1000", "1001+"
#
# The client has to explicitly request `"orderType": "HISTOGRAM_BUCKET"`
# for a histogram-mutated dimension.
"A String",
],
},
],
"pageSize": 42, # Page size is for paging and specifies the maximum number of returned rows.
# Page size should be >= 0. A query returns the default of 1,000 rows.
# The Analytics Core Reporting API returns a maximum of 10,000 rows per
# request, no matter how many you ask for. It can also return fewer rows
# than requested, if there aren't as many dimension segments as you expect.
# For instance, there are fewer than 300 possible values for `ga:country`,
# so when segmenting only by country, you can't get more than 300 rows,
# even if you set `pageSize` to a higher value.
"includeEmptyRows": True or False, # If set to false, the response does not include rows if all the retrieved
# metrics are equal to zero. The default is false which will exclude these
# rows.
"filtersExpression": "A String", # Dimension or metric filters that restrict the data returned for your
# request. To use the `filtersExpression`, supply a dimension or metric on
# which to filter, followed by the filter expression. For example, the
# following expression selects `ga:browser` dimension which starts with
# Firefox; `ga:browser=~^Firefox`. For more information on dimensions
# and metric filters, see
# [Filters reference](https://developers.google.com/analytics/devguides/reporting/core/v3/reference#filters).
"viewId": "A String", # The Analytics
# [view ID](https://support.google.com/analytics/answer/1009618)
# from which to retrieve data. Every [ReportRequest](#ReportRequest)
# within a `batchGet` method must contain the same `viewId`.
"hideValueRanges": True or False, # If set to true, hides the minimum and maximum across all matching rows.
# The default is false and the value ranges are returned.
"orderBys": [ # Sort order on output rows. To compare two rows, the elements of the
# following are applied in order until a difference is found. All date
# ranges in the output get the same row order.
{ # Specifies the sorting options.
"orderType": "A String", # The order type. The default orderType is `VALUE`.
"fieldName": "A String", # The field which to sort by. The default sort order is ascending. Example:
# `ga:browser`.
# Note, that you can only specify one field for sort here. For example,
# `ga:browser, ga:city` is not valid.
"sortOrder": "A String", # The sorting order for the field.
},
],
"cohortGroup": { # Defines a cohort group. # Cohort group associated with this request. If there is a cohort group
# in the request the `ga:cohort` dimension must be present.
# Every [ReportRequest](#ReportRequest) within a `batchGet` method must
# contain the same `cohortGroup` definition.
# For example:
#
# "cohortGroup": {
# "cohorts": [{
# "name": "cohort 1",
# "type": "FIRST_VISIT_DATE",
# "dateRange": { "startDate": "2015-08-01", "endDate": "2015-08-01" }
# },{
# "name": "cohort 2"
# "type": "FIRST_VISIT_DATE"
# "dateRange": { "startDate": "2015-07-01", "endDate": "2015-07-01" }
# }]
# }
"cohorts": [ # The definition for the cohort.
{ # Defines a cohort. A cohort is a group of users who share a common
# characteristic. For example, all users with the same acquisition date
# belong to the same cohort.
"dateRange": { # A contiguous set of days: startDate, startDate + 1 day, ..., endDate. # This is used for `FIRST_VISIT_DATE` cohort, the cohort selects users
# whose first visit date is between start date and end date defined in the
# DateRange. The date ranges should be aligned for cohort requests. If the
# request contains `ga:cohortNthDay` it should be exactly one day long,
# if `ga:cohortNthWeek` it should be aligned to the week boundary (starting
# at Sunday and ending Saturday), and for `ga:cohortNthMonth` the date range
# should be aligned to the month (starting at the first and ending on the
# last day of the month).
# For LTV requests there are no such restrictions.
# You do not need to supply a date range for the
# `reportsRequest.dateRanges` field.
# The start and end dates are specified in
# [ISO8601](https://en.wikipedia.org/wiki/ISO_8601) date format `YYYY-MM-DD`.
"startDate": "A String", # The start date for the query in the format `YYYY-MM-DD`.
"endDate": "A String", # The end date for the query in the format `YYYY-MM-DD`.
},
"type": "A String", # Type of the cohort. The only supported type as of now is
# `FIRST_VISIT_DATE`. If this field is unspecified the cohort is treated
# as `FIRST_VISIT_DATE` type cohort.
"name": "A String", # A unique name for the cohort. If not defined name will be auto-generated
# with values cohort_[1234...].
},
],
"lifetimeValue": True or False, # Enable Life Time Value (LTV). LTV measures lifetime value for users
# acquired through different channels.
# Please see:
# [Cohort Analysis](https://support.google.com/analytics/answer/6074676) and
# [Lifetime Value](https://support.google.com/analytics/answer/6182550)
# If the value of lifetimeValue is false:
#
# - The metric values are similar to the values in the web interface cohort
# report.
# - The cohort definition date ranges must be aligned to the calendar week
# and month. i.e. while requesting `ga:cohortNthWeek` the `startDate` in
# the cohort definition should be a Sunday and the `endDate` should be the
# following Saturday, and for `ga:cohortNthMonth`, the `startDate`
# should be the 1st of the month and `endDate` should be the last day
# of the month.
#
# When the lifetimeValue is true:
#
# - The metric values will correspond to the values in the web interface
# LifeTime value report.
# - The Lifetime Value report shows you how user value (Revenue) and
# engagement (Appviews, Goal Completions, Sessions, and Session Duration)
# grow during the 90 days after a user is acquired.
# - The metrics are calculated as a cumulative average per user per the time
# increment.
# - The cohort definition date ranges need not be aligned to the calendar
# week and month boundaries.
# - The `viewId` must be an
# [app view ID](https://support.google.com/analytics/answer/2649553#WebVersusAppViews)
},
"dateRanges": [ # Date ranges in the request. The request can have a maximum of 2 date
# ranges. The response will contain a set of metric values for each
# combination of the dimensions for each date range in the request. So, if
# there are two date ranges, there will be two set of metric values, one for
# the original date range and one for the second date range.
# The `reportRequest.dateRanges` field should not be specified for cohorts
# or Lifetime value requests.
# If a date range is not provided, the default date range is (startDate:
# current date - 7 days, endDate: current date - 1 day). Every
# [ReportRequest](#ReportRequest) within a `batchGet` method must
# contain the same `dateRanges` definition.
{ # A contiguous set of days: startDate, startDate + 1 day, ..., endDate.
# The start and end dates are specified in
# [ISO8601](https://en.wikipedia.org/wiki/ISO_8601) date format `YYYY-MM-DD`.
"startDate": "A String", # The start date for the query in the format `YYYY-MM-DD`.
"endDate": "A String", # The end date for the query in the format `YYYY-MM-DD`.
},
],
"pageToken": "A String", # A continuation token to get the next page of the results. Adding this to
# the request will return the rows after the pageToken. The pageToken should
# be the value returned in the nextPageToken parameter in the response to
# the GetReports request.
"samplingLevel": "A String", # The desired report
# [sample](https://support.google.com/analytics/answer/2637192) size.
# If the the `samplingLevel` field is unspecified the `DEFAULT` sampling
# level is used. Every [ReportRequest](#ReportRequest) within a
# `batchGet` method must contain the same `samplingLevel` definition. See
# [developer guide](/analytics/devguides/reporting/core/v4/basics#sampling)
# for details.
"dimensionFilterClauses": [ # The dimension filter clauses for filtering Dimension Values. They are
# logically combined with the `AND` operator. Note that filtering occurs
# before any dimensions are aggregated, so that the returned metrics
# represent the total for only the relevant dimensions.
{ # A group of dimension filters. Set the operator value to specify how
# the filters are logically combined.
"operator": "A String", # The operator for combining multiple dimension filters. If unspecified, it
# is treated as an `OR`.
"filters": [ # The repeated set of filters. They are logically combined based on the
# operator specified.
{ # Dimension filter specifies the filtering options on a dimension.
"dimensionName": "A String", # The dimension to filter on. A DimensionFilter must contain a dimension.
"operator": "A String", # How to match the dimension to the expression. The default is REGEXP.
"expressions": [ # Strings or regular expression to match against. Only the first value of
# the list is used for comparison unless the operator is `IN_LIST`.
# If `IN_LIST` operator, then the entire list is used to filter the
# dimensions as explained in the description of the `IN_LIST` operator.
"A String",
],
"not": True or False, # Logical `NOT` operator. If this boolean is set to true, then the matching
# dimension values will be excluded in the report. The default is false.
"caseSensitive": True or False, # Should the match be case sensitive? Default is false.
},
],
},
],
"metricFilterClauses": [ # The metric filter clauses. They are logically combined with the `AND`
# operator. Metric filters look at only the first date range and not the
# comparing date range. Note that filtering on metrics occurs after the
# metrics are aggregated.
{ # Represents a group of metric filters.
# Set the operator value to specify how the filters are logically combined.
"operator": "A String", # The operator for combining multiple metric filters. If unspecified, it is
# treated as an `OR`.
"filters": [ # The repeated set of filters. They are logically combined based on the
# operator specified.
{ # MetricFilter specifies the filter on a metric.
"operator": "A String", # Is the metric `EQUAL`, `LESS_THAN` or `GREATER_THAN` the
# comparisonValue, the default is `EQUAL`. If the operator is
# `IS_MISSING`, checks if the metric is missing and would ignore the
# comparisonValue.
"not": True or False, # Logical `NOT` operator. If this boolean is set to true, then the matching
# metric values will be excluded in the report. The default is false.
"comparisonValue": "A String", # The value to compare against.
"metricName": "A String", # The metric that will be filtered on. A metricFilter must contain a metric
# name. A metric name can be an alias earlier defined as a metric or it can
# also be a metric expression.
},
],
},
],
"segments": [ # Segment the data returned for the request. A segment definition helps look
# at a subset of the segment request. A request can contain up to four
# segments. Every [ReportRequest](#ReportRequest) within a
# `batchGet` method must contain the same `segments` definition. Requests
# with segments must have the `ga:segment` dimension.
{ # The segment definition, if the report needs to be segmented.
# A Segment is a subset of the Analytics data. For example, of the entire
# set of users, one Segment might be users from a particular country or city.
"dynamicSegment": { # Dynamic segment definition for defining the segment within the request. # A dynamic segment definition in the request.
# A segment can select users, sessions or both.
"sessionSegment": { # SegmentDefinition defines the segment to be a set of SegmentFilters which # Session Segment to select sessions to include in the segment.
# are combined together with a logical `AND` operation.
"segmentFilters": [ # A segment is defined by a set of segment filters which are combined
# together with a logical `AND` operation.
{ # SegmentFilter defines the segment to be either a simple or a sequence
# segment. A simple segment condition contains dimension and metric conditions
# to select the sessions or users. A sequence segment condition can be used to
# select users or sessions based on sequential conditions.
"not": True or False, # If true, match the complement of simple or sequence segment.
# For example, to match all visits not from "New York", we can define the
# segment as follows:
#
# "sessionSegment": {
# "segmentFilters": [{
# "simpleSegment" :{
# "orFiltersForSegment": [{
# "segmentFilterClauses":[{
# "dimensionFilter": {
# "dimensionName": "ga:city",
# "expressions": ["New York"]
# }
# }]
# }]
# },
# "not": "True"
# }]
# },
"simpleSegment": { # A Simple segment conditions consist of one or more dimension/metric # A Simple segment conditions consist of one or more dimension/metric
# conditions that can be combined
# conditions that can be combined.
"orFiltersForSegment": [ # A list of segment filters groups which are combined with logical `AND`
# operator.
{ # A list of segment filters in the `OR` group are combined with the logical OR
# operator.
"segmentFilterClauses": [ # List of segment filters to be combined with a `OR` operator.
{ # Filter Clause to be used in a segment definition, can be wither a metric or
# a dimension filter.
"not": True or False, # Matches the complement (`!`) of the filter.
"dimensionFilter": { # Dimension filter specifies the filtering options on a dimension. # Dimension Filter for the segment definition.
"minComparisonValue": "A String", # Minimum comparison values for `BETWEEN` match type.
"maxComparisonValue": "A String", # Maximum comparison values for `BETWEEN` match type.
"dimensionName": "A String", # Name of the dimension for which the filter is being applied.
"caseSensitive": True or False, # Should the match be case sensitive, ignored for `IN_LIST` operator.
"operator": "A String", # The operator to use to match the dimension with the expressions.
"expressions": [ # The list of expressions, only the first element is used for all operators
"A String",
],
},
"metricFilter": { # Metric filter to be used in a segment filter clause. # Metric Filter for the segment definition.
"operator": "A String", # Specifies is the operation to perform to compare the metric. The default
# is `EQUAL`.
"scope": "A String", # Scope for a metric defines the level at which that metric is defined. The
# specified metric scope must be equal to or greater than its primary scope
# as defined in the data model. The primary scope is defined by if the
# segment is selecting users or sessions.
"comparisonValue": "A String", # The value to compare against. If the operator is `BETWEEN`, this value is
# treated as minimum comparison value.
"maxComparisonValue": "A String", # Max comparison value is only used for `BETWEEN` operator.
"metricName": "A String", # The metric that will be filtered on. A `metricFilter` must contain a
# metric name.
},
},
],
},
],
},
"sequenceSegment": { # Sequence conditions consist of one or more steps, where each step is defined # Sequence conditions consist of one or more steps, where each step is
# defined by one or more dimension/metric conditions. Multiple steps can
# be combined with special sequence operators.
# by one or more dimension/metric conditions. Multiple steps can be combined
# with special sequence operators.
"segmentSequenceSteps": [ # The list of steps in the sequence.
{ # A segment sequence definition.
"matchType": "A String", # Specifies if the step immediately precedes or can be any time before the
# next step.
"orFiltersForSegment": [ # A sequence is specified with a list of Or grouped filters which are
# combined with `AND` operator.
{ # A list of segment filters in the `OR` group are combined with the logical OR
# operator.
"segmentFilterClauses": [ # List of segment filters to be combined with a `OR` operator.
{ # Filter Clause to be used in a segment definition, can be wither a metric or
# a dimension filter.
"not": True or False, # Matches the complement (`!`) of the filter.
"dimensionFilter": { # Dimension filter specifies the filtering options on a dimension. # Dimension Filter for the segment definition.
"minComparisonValue": "A String", # Minimum comparison values for `BETWEEN` match type.
"maxComparisonValue": "A String", # Maximum comparison values for `BETWEEN` match type.
"dimensionName": "A String", # Name of the dimension for which the filter is being applied.
"caseSensitive": True or False, # Should the match be case sensitive, ignored for `IN_LIST` operator.
"operator": "A String", # The operator to use to match the dimension with the expressions.
"expressions": [ # The list of expressions, only the first element is used for all operators
"A String",
],
},
"metricFilter": { # Metric filter to be used in a segment filter clause. # Metric Filter for the segment definition.
"operator": "A String", # Specifies is the operation to perform to compare the metric. The default
# is `EQUAL`.
"scope": "A String", # Scope for a metric defines the level at which that metric is defined. The
# specified metric scope must be equal to or greater than its primary scope
# as defined in the data model. The primary scope is defined by if the
# segment is selecting users or sessions.
"comparisonValue": "A String", # The value to compare against. If the operator is `BETWEEN`, this value is
# treated as minimum comparison value.
"maxComparisonValue": "A String", # Max comparison value is only used for `BETWEEN` operator.
"metricName": "A String", # The metric that will be filtered on. A `metricFilter` must contain a
# metric name.
},
},
],
},
],
},
],
"firstStepShouldMatchFirstHit": True or False, # If set, first step condition must match the first hit of the visitor (in
# the date range).
},
},
],
},
"name": "A String", # The name of the dynamic segment.
"userSegment": { # SegmentDefinition defines the segment to be a set of SegmentFilters which # User Segment to select users to include in the segment.
# are combined together with a logical `AND` operation.
"segmentFilters": [ # A segment is defined by a set of segment filters which are combined
# together with a logical `AND` operation.
{ # SegmentFilter defines the segment to be either a simple or a sequence
# segment. A simple segment condition contains dimension and metric conditions
# to select the sessions or users. A sequence segment condition can be used to
# select users or sessions based on sequential conditions.
"not": True or False, # If true, match the complement of simple or sequence segment.
# For example, to match all visits not from "New York", we can define the
# segment as follows:
#
# "sessionSegment": {
# "segmentFilters": [{
# "simpleSegment" :{
# "orFiltersForSegment": [{
# "segmentFilterClauses":[{
# "dimensionFilter": {
# "dimensionName": "ga:city",
# "expressions": ["New York"]
# }
# }]
# }]
# },
# "not": "True"
# }]
# },
"simpleSegment": { # A Simple segment conditions consist of one or more dimension/metric # A Simple segment conditions consist of one or more dimension/metric
# conditions that can be combined
# conditions that can be combined.
"orFiltersForSegment": [ # A list of segment filters groups which are combined with logical `AND`
# operator.
{ # A list of segment filters in the `OR` group are combined with the logical OR
# operator.
"segmentFilterClauses": [ # List of segment filters to be combined with a `OR` operator.
{ # Filter Clause to be used in a segment definition, can be wither a metric or
# a dimension filter.
"not": True or False, # Matches the complement (`!`) of the filter.
"dimensionFilter": { # Dimension filter specifies the filtering options on a dimension. # Dimension Filter for the segment definition.
"minComparisonValue": "A String", # Minimum comparison values for `BETWEEN` match type.
"maxComparisonValue": "A String", # Maximum comparison values for `BETWEEN` match type.
"dimensionName": "A String", # Name of the dimension for which the filter is being applied.
"caseSensitive": True or False, # Should the match be case sensitive, ignored for `IN_LIST` operator.
"operator": "A String", # The operator to use to match the dimension with the expressions.
"expressions": [ # The list of expressions, only the first element is used for all operators
"A String",
],
},
"metricFilter": { # Metric filter to be used in a segment filter clause. # Metric Filter for the segment definition.
"operator": "A String", # Specifies is the operation to perform to compare the metric. The default
# is `EQUAL`.
"scope": "A String", # Scope for a metric defines the level at which that metric is defined. The
# specified metric scope must be equal to or greater than its primary scope
# as defined in the data model. The primary scope is defined by if the
# segment is selecting users or sessions.
"comparisonValue": "A String", # The value to compare against. If the operator is `BETWEEN`, this value is
# treated as minimum comparison value.
"maxComparisonValue": "A String", # Max comparison value is only used for `BETWEEN` operator.
"metricName": "A String", # The metric that will be filtered on. A `metricFilter` must contain a
# metric name.
},
},
],
},
],
},
"sequenceSegment": { # Sequence conditions consist of one or more steps, where each step is defined # Sequence conditions consist of one or more steps, where each step is
# defined by one or more dimension/metric conditions. Multiple steps can
# be combined with special sequence operators.
# by one or more dimension/metric conditions. Multiple steps can be combined
# with special sequence operators.
"segmentSequenceSteps": [ # The list of steps in the sequence.
{ # A segment sequence definition.
"matchType": "A String", # Specifies if the step immediately precedes or can be any time before the
# next step.
"orFiltersForSegment": [ # A sequence is specified with a list of Or grouped filters which are
# combined with `AND` operator.
{ # A list of segment filters in the `OR` group are combined with the logical OR
# operator.
"segmentFilterClauses": [ # List of segment filters to be combined with a `OR` operator.
{ # Filter Clause to be used in a segment definition, can be wither a metric or
# a dimension filter.
"not": True or False, # Matches the complement (`!`) of the filter.
"dimensionFilter": { # Dimension filter specifies the filtering options on a dimension. # Dimension Filter for the segment definition.
"minComparisonValue": "A String", # Minimum comparison values for `BETWEEN` match type.
"maxComparisonValue": "A String", # Maximum comparison values for `BETWEEN` match type.
"dimensionName": "A String", # Name of the dimension for which the filter is being applied.
"caseSensitive": True or False, # Should the match be case sensitive, ignored for `IN_LIST` operator.
"operator": "A String", # The operator to use to match the dimension with the expressions.
"expressions": [ # The list of expressions, only the first element is used for all operators
"A String",
],
},
"metricFilter": { # Metric filter to be used in a segment filter clause. # Metric Filter for the segment definition.
"operator": "A String", # Specifies is the operation to perform to compare the metric. The default
# is `EQUAL`.
"scope": "A String", # Scope for a metric defines the level at which that metric is defined. The
# specified metric scope must be equal to or greater than its primary scope
# as defined in the data model. The primary scope is defined by if the
# segment is selecting users or sessions.
"comparisonValue": "A String", # The value to compare against. If the operator is `BETWEEN`, this value is
# treated as minimum comparison value.
"maxComparisonValue": "A String", # Max comparison value is only used for `BETWEEN` operator.
"metricName": "A String", # The metric that will be filtered on. A `metricFilter` must contain a
# metric name.
},
},
],
},
],
},
],
"firstStepShouldMatchFirstHit": True or False, # If set, first step condition must match the first hit of the visitor (in
# the date range).
},
},
],
},
},
"segmentId": "A String", # The segment ID of a built-in or custom segment, for example `gaid::-3`.
},
],
},
],
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The main response class which holds the reports from the Reporting API
# `batchGet` call.
"reports": [ # Responses corresponding to each of the request.
{ # The data response corresponding to the request.
"nextPageToken": "A String", # Page token to retrieve the next page of results in the list.
"data": { # The data part of the report. # Response data.
"rows": [ # There's one ReportRow for every unique combination of dimensions.
{ # A row in the report.
"metrics": [ # List of metrics for each requested DateRange.
{ # Used to return a list of metrics for a single DateRange / dimension
# combination
"values": [ # Each value corresponds to each Metric in the request.
"A String",
],
"pivotValueRegions": [ # The values of each pivot region.
{ # The metric values in the pivot region.
"values": [ # The values of the metrics in each of the pivot regions.
"A String",
],
},
],
},
],
"dimensions": [ # List of requested dimensions.
"A String",
],
},
],
"maximums": [ # Minimum and maximum values seen over all matching rows. These are both
# empty when `hideValueRanges` in the request is false, or when
# rowCount is zero.
{ # Used to return a list of metrics for a single DateRange / dimension
# combination
"values": [ # Each value corresponds to each Metric in the request.
"A String",
],
"pivotValueRegions": [ # The values of each pivot region.
{ # The metric values in the pivot region.
"values": [ # The values of the metrics in each of the pivot regions.
"A String",
],
},
],
},
],
"minimums": [ # Minimum and maximum values seen over all matching rows. These are both
# empty when `hideValueRanges` in the request is false, or when
# rowCount is zero.
{ # Used to return a list of metrics for a single DateRange / dimension
# combination
"values": [ # Each value corresponds to each Metric in the request.
"A String",
],
"pivotValueRegions": [ # The values of each pivot region.
{ # The metric values in the pivot region.
"values": [ # The values of the metrics in each of the pivot regions.
"A String",
],
},
],
},
],
"isDataGolden": True or False, # Indicates if response to this request is golden or not. Data is
# golden when the exact same request will not produce any new results if
# asked at a later point in time.
"samplingSpaceSizes": [ # If the results are
# [sampled](https://support.google.com/analytics/answer/2637192),
# this returns the total number of
# samples present, one entry per date range. If the results are not sampled
# this field will not be defined. See
# [developer guide](/analytics/devguides/reporting/core/v4/basics#sampling)
# for details.
"A String",
],
"totals": [ # For each requested date range, for the set of all rows that match
# the query, every requested value format gets a total. The total
# for a value format is computed by first totaling the metrics
# mentioned in the value format and then evaluating the value
# format as a scalar expression. E.g., The "totals" for
# `3 / (ga:sessions + 2)` we compute
# `3 / ((sum of all relevant ga:sessions) + 2)`.
# Totals are computed before pagination.
{ # Used to return a list of metrics for a single DateRange / dimension
# combination
"values": [ # Each value corresponds to each Metric in the request.
"A String",
],
"pivotValueRegions": [ # The values of each pivot region.
{ # The metric values in the pivot region.
"values": [ # The values of the metrics in each of the pivot regions.
"A String",
],
},
],
},
],
"rowCount": 42, # Total number of matching rows for this query.
"dataLastRefreshed": "A String", # The last time the data in the report was refreshed. All the hits received
# before this timestamp are included in the calculation of the report.
"samplesReadCounts": [ # If the results are
# [sampled](https://support.google.com/analytics/answer/2637192),
# this returns the total number of samples read, one entry per date range.
# If the results are not sampled this field will not be defined. See
# [developer guide](/analytics/devguides/reporting/core/v4/basics#sampling)
# for details.
"A String",
],
},
"columnHeader": { # Column headers. # The column headers.
"dimensions": [ # The dimension names in the response.
"A String",
],
"metricHeader": { # The headers for the metrics. # Metric headers for the metrics in the response.
"metricHeaderEntries": [ # Headers for the metrics in the response.
{ # Header for the metrics.
"type": "A String", # The type of the metric, for example `INTEGER`.
"name": "A String", # The name of the header.
},
],
"pivotHeaders": [ # Headers for the pivots in the response.
{ # The headers for each of the pivot sections defined in the request.
"totalPivotGroupsCount": 42, # The total number of groups for this pivot.
"pivotHeaderEntries": [ # A single pivot section header.
{ # The headers for the each of the metric column corresponding to the metrics
# requested in the pivots section of the response.
"dimensionValues": [ # The values for the dimensions in the pivot.
"A String",
],
"dimensionNames": [ # The name of the dimensions in the pivot response.
"A String",
],
"metric": { # Header for the metrics. # The metric header for the metric in the pivot.
"type": "A String", # The type of the metric, for example `INTEGER`.
"name": "A String", # The name of the header.
},
},
],
},
],
},
},
},
],
}