Update occurrences of data frame terminology

[lcawl]

The term "data frames" was used interchangeably with "transforms" and this must be corrected across the library (going back to 7.2):

• Verify that the shared attributes are up-to-date
• Update the occurrences (that don't use shared attributes) in the stack-docs repo: [DOCS] Changes wording to move away from data frame terminology in Stack Docs #534
• Update the occurrences (that don't use shared attributes) in the elasticsearch repo: [DOCS] Changes wording to move away from data frame terminology in the ES repo elasticsearch#47093
• Update the occurrences (that don't use shared attributes) in the kibana repo: no need to modify anything.

[szabosteve]

List of occurrences in the Stack docs repo:

Istvan-MacBook-Pro:stack-docs[master]$ find docs -name '*.asciidoc' | xargs egrep 'data frame'
Istvan-MacBook-Pro:stack-docs[master]$ find docs -name '*.asciidoc' | xargs egrep 'dataframe'
docs/en/stack/redirects.asciidoc:* <<dataframe-limitations>>
docs/en/stack/ml/df-analytics/ecommerce-outliers.asciidoc:For more details about creating {transforms}, see <<ecommerce-dataframes>>.
docs/en/stack/ml/df-analytics/dfanalytics-limitations.asciidoc:=== Deleting a {dfanalytics-job} does not delete the {dataframe} destination index
docs/en/stack/ml/df-analytics/dfanalytics-limitations.asciidoc:the {dataframe} destination index. That index must be deleted separately.
docs/en/stack/ml/df-analytics/dfanalytics-limitations.asciidoc:[[dfa-dataframe-size-limitations]]
docs/en/stack/ml/df-analytics/dfanalytics-limitations.asciidoc:=== {dataframe-cap} memory limitation
docs/en/stack/ml/df-analytics/dfanalytics-limitations.asciidoc:{dfanalytics-cap} can analyze {dataframes} that fit into the memory limit 
docs/en/stack/ml/df-analytics/index.asciidoc:{stack-ov}/ml-dataframes.html[{dataframe}]. 
docs/en/stack/ml/df-analytics/index.asciidoc:{dataframes} which can be used as the source for {dfanalytics}.
docs/en/stack/ml/df-analytics/evaluatedf-api.asciidoc:{dataframe} row with the ground truth. For example, in case of {oldetection}, 
Istvan-MacBook-Pro:stack-docs[master]$ 

PR: #534

[szabosteve]

List of occurrences in the ES repo:

Istvan-MacBook-Pro:elasticsearch[master]$ find docs -name '*.asciidoc' | xargs egrep 'data frame'
docs/java-rest/high-level/transform/stop_transform.asciidoc:<1> If true wait for the data frame task to stop before responding
docs/reference/settings/ml-settings.asciidoc:`20`. In this context, jobs include both anomaly detector jobs and data frame
docs/reference/transform/overview.asciidoc:image::images/ml-dataframepivot.jpg["Example of a data frame pivot in {kib}"]

Istvan-MacBook-Pro:elasticsearch[master]$ find docs -name '*.asciidoc' | xargs egrep 'dataframe'
docs/java-rest/redirects.asciidoc:[role="exclude",id="java-rest-high-dataframe-get-data-frame-transform"]
docs/java-rest/redirects.asciidoc:[role="exclude",id="java-rest-high-dataframe-get-data-frame-transform-stats"]
docs/java-rest/redirects.asciidoc:[role="exclude",id="java-rest-high-dataframe-put-data-frame-transform"]
docs/java-rest/redirects.asciidoc:[role="exclude",id="java-rest-high-dataframe-update-data-frame-transform"]
docs/java-rest/redirects.asciidoc:[role="exclude",id="java-rest-high-dataframe-delete-data-frame-transform"]
docs/java-rest/redirects.asciidoc:[role="exclude",id="java-rest-high-dataframe-preview-data-frame-transform"]
docs/java-rest/redirects.asciidoc:[role="exclude",id="java-rest-high-dataframe-start-data-frame-transform"]
docs/java-rest/redirects.asciidoc:[role="exclude",id="java-rest-high-dataframe-stop-data-frame-transform"]
docs/java-rest/high-level/ml/evaluate-data-frame.asciidoc:Evaluates the {ml} algorithm that ran on a {dataframe}.
docs/java-rest/high-level/ml/estimate-memory-usage.asciidoc:<1> Constructing a new request containing a {dataframe-analytics-config} for which memory usage estimation should be performed
docs/reference/data-rollup-transform.asciidoc:* {stack-ov}/ml-dataframes.html[Transforming your data]
docs/reference/ml/df-analytics/apis/estimate-memory-usage-dfanalytics.asciidoc:Estimates memory usage for the given {dataframe-analytics-config}.
docs/reference/ml/df-analytics/apis/estimate-memory-usage-dfanalytics.asciidoc:This API estimates memory usage for the given {dataframe-analytics-config} before the {dfanalytics-job} is even created.
docs/reference/ml/df-analytics/apis/evaluateresources.asciidoc:the probability that each {dataframe} row belongs to a certain class. For 
docs/reference/ml/df-analytics/apis/dfanalyticsresources.asciidoc:  (Required, string) Defines which field of the {dataframe} is to be predicted. 
docs/reference/transform/checkpoints.asciidoc:. Updates the destination index (the {dataframe}) with the changed entities.
docs/reference/transform/apis/transformresource.asciidoc:{stack-ov}/ecommerce-dataframes.html[Transforming your data with {dataframes}].
docs/reference/transform/apis/transformresource.asciidoc:{stack-ov}/dataframe-limitations.html[{dataframe-cap} limitations].
docs/reference/transform/apis/put-transform.asciidoc:structure (known as a {dataframe}). The ID for each document in the
docs/reference/transform/apis/put-transform.asciidoc:{dataframe} is generated from a hash of the entity, so there is a unique row
docs/reference/transform/apis/put-transform.asciidoc:{stack-ov}/ml-dataframes.html[{transforms-cap}].
docs/reference/transform/apis/index.asciidoc:See also {stack-ov}/ml-dataframes.html[{transforms-cap}].
docs/reference/transform/dataframe-examples.asciidoc:[[dataframe-examples]]
docs/reference/transform/dataframe-examples.asciidoc:<<ecommerce-dataframes,Transforming your data with {dataframes}>>.
docs/reference/transform/dataframe-examples.asciidoc:* <<ecommerce-dataframes>>
docs/reference/transform/dataframe-examples.asciidoc:<1> This is the destination index for the {dataframe}. It is ignored by 
docs/reference/transform/dataframe-examples.asciidoc:<2> Two `group_by` fields have been selected. This means the {dataframe} will 
docs/reference/transform/dataframe-examples.asciidoc:dataset both these fields are unique. By including both in the {dataframe} it 
docs/reference/transform/dataframe-examples.asciidoc:{dataframe} in advance, populated with some sample values. For example:
docs/reference/transform/dataframe-examples.asciidoc:This {dataframe} makes it easier to answer questions such as:
docs/reference/transform/dataframe-examples.asciidoc:{dataframes} allow us to persist this data as a customer centric index. This 
docs/reference/transform/dataframe-examples.asciidoc:<2> This is the destination index for the {dataframe}. It is ignored by 
docs/reference/transform/dataframe-examples.asciidoc:This {dataframe} makes it easier to answer questions such as:
docs/reference/transform/dataframe-examples.asciidoc:For batch {dataframes} this occurs once.
docs/reference/transform/dataframe-examples.asciidoc:<2> This is the destination index for the {dataframe}. It is ignored by 
docs/reference/transform/dataframe-examples.asciidoc:This {dataframe} makes it easier to answer questions such as:
docs/reference/transform/troubleshooting.asciidoc:[[dataframe-troubleshooting]]
docs/reference/transform/limitations.asciidoc:[[dataframe-limitations]]
docs/reference/transform/limitations.asciidoc:the Elastic {dataframe} feature:
docs/reference/transform/limitations.asciidoc:=== {dataframe-cap} UI will not work during a rolling upgrade from 7.2
docs/reference/transform/limitations.asciidoc:created in 7.2, the {dataframe} UI will not work. Please wait until all nodes 
docs/reference/transform/limitations.asciidoc:have been upgraded to the newer version before using the {dataframe} UI.
docs/reference/transform/limitations.asciidoc:=== {dataframe-cap} data type limitation
docs/reference/transform/limitations.asciidoc:{dataframes-cap} do not (yet) support fields containing arrays – in the UI or 
docs/reference/transform/limitations.asciidoc:(deleted, updated, added) while the batch {dataframe} is in progress, then the 
docs/reference/transform/limitations.asciidoc:=== {cdataframe-cap} consistency does not account for deleted or updated documents
docs/reference/transform/limitations.asciidoc:will not be removed from the {dataframe} destination index.
docs/reference/transform/limitations.asciidoc:updated when viewing the {dataframe} destination index.
docs/reference/transform/limitations.asciidoc:=== Deleting a {transform} does not delete the {dataframe} destination index or {kib} index pattern
docs/reference/transform/limitations.asciidoc:neither the {dataframe} destination index nor the {kib} index pattern, should 
docs/reference/transform/limitations.asciidoc:{transform} checkpoint to complete. For {cdataframes}, the number of 
docs/reference/transform/limitations.asciidoc:=== {cdataframe-cap} scheduling limitations
docs/reference/transform/limitations.asciidoc:A {cdataframe} periodically checks for changes to source data. The functionality 
docs/reference/transform/limitations.asciidoc:=== {cdataframes-cap} may give incorrect results if documents are not yet available to search
docs/reference/transform/index.asciidoc:[[ml-dataframes]]
docs/reference/transform/index.asciidoc:* <<dataframe-examples>>
docs/reference/transform/index.asciidoc:* <<dataframe-troubleshooting>>
docs/reference/transform/index.asciidoc:* <<dataframe-limitations>>
docs/reference/transform/index.asciidoc:include::dataframe-examples.asciidoc[]
docs/reference/transform/overview.asciidoc:A _{dataframe}_ is a two-dimensional tabular data structure. In the context of
docs/reference/transform/overview.asciidoc:example, you can use {dataframes} to _pivot_ your data into a new entity-centric
docs/reference/transform/overview.asciidoc:individual document, for example a single item purchase. {dataframes-cap} enable
docs/reference/transform/overview.asciidoc:You can create {dataframes} by using {transforms}.
docs/reference/transform/overview.asciidoc:Pivoting results in a summary of your data, which is the {dataframe}.
docs/reference/transform/overview.asciidoc:ordered quantity. The result is a {dataframe} that shows the number of sold
docs/reference/transform/overview.asciidoc:image::images/ml-dataframepivot.jpg["Example of a data frame pivot in {kib}"]
docs/reference/transform/overview.asciidoc:creates a new index that is dedicated to the {dataframe}.
docs/reference/transform/usage.asciidoc:joined-up picture. This new index is sometimes referred to as a _{dataframe}_.
docs/reference/transform/usage.asciidoc:all aggregation results, you need to create the complete {dataframe}. If you
docs/reference/transform/ecommerce-example.asciidoc:[[ecommerce-dataframes]]
docs/reference/transform/ecommerce-example.asciidoc:<<ml-dataframes,{transforms-cap}>> enable you to retrieve information
docs/reference/transform/ecommerce-example.asciidoc:If you want to use more complex queries, you can create your {dataframe} from a
docs/reference/transform/ecommerce-example.asciidoc:image::images/dataframe-transforms.jpg["Managing {transforms} in {kib}"]

PR: elastic/elasticsearch#47093

[szabosteve]

List of occurrences in the Kibana repo:

Istvan-MacBook-Pro:kibana[master]$ find docs -name '*.asciidoc' | xargs egrep 'data frame'
Istvan-MacBook-Pro:kibana[master]$ find docs -name '*.asciidoc' | xargs egrep 'dataframe'
docs/redirects.asciidoc:{stack-ov}/ecommerce-dataframes.html[Transforming the eCommerce sample data].