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[feat] docs; update admonition syntax (#68842)
* [feat] docs; update admonition syntax - Standardizes according to style conventions: https://grafana.com/docs/writers-toolkit/style-guide/style-conventions/#admonitions - Prepares docs for better, uniform admonition style. * Remove false positives and irregularities * false positive removal * Update docs/sources/datasources/mysql/_index.md * Update docs/sources/developers/angular_deprecation/angular-plugins.md * fix link errors * Prettify some nested blockquotes * remoe unnecessary admonition
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@@ -200,7 +200,9 @@ In the example below, the panel has three queries (A, B, C). I removed the B que
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{{< figure src="/static/img/docs/transformations/filter-by-query-stat-example-7-0.png" class="docs-image--no-shadow" max-width= "1100px" >}}
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> **Note:** This transformation is not available for Graphite because this data source does not support correlating returned data with queries.
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{{% admonition type="note" %}}
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This transformation is not available for Graphite because this data source does not support correlating returned data with queries.
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{{% /admonition %}}
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### Filter data by value
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@@ -490,7 +492,9 @@ Here is the result after applying the Merge transformation.
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Use this transformation to rename, reorder, or hide fields returned by the query.
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> **Note:** This transformation only works in panels with a single query. If your panel has multiple queries, then you must either apply an Outer join transformation or remove the extra queries.
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{{% admonition type="note" %}}
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This transformation only works in panels with a single query. If your panel has multiple queries, then you must either apply an Outer join transformation or remove the extra queries.
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{{% /admonition %}}
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Grafana displays a list of fields returned by the query. You can:
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@@ -661,7 +665,9 @@ As you can see each row in the source data becomes a separate field. Each field
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### Prepare time series
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> **Note:** This transformation is available in Grafana 7.5.10+ and Grafana 8.0.6+.
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{{% admonition type="note" %}}
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This transformation is available in Grafana 7.5.10+ and Grafana 8.0.6+.
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{{% /admonition %}}
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Prepare time series transformation is useful when a data source returns time series data in a format that isn't supported by the panel you want to use. For more information about data frame formats, refer to [Data frames]({{< relref "../../../developers/plugins/data-frames/" >}}).
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@@ -673,7 +679,9 @@ Select the `Wide time series` option to transform the time series data frame fro
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### Series to rows
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> **Note:** This transformation is available in Grafana 7.1+.
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{{% admonition type="note" %}}
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This transformation is available in Grafana 7.1+.
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{{% /admonition %}}
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Use this transformation to combine the result from multiple time series data queries into one single result. This is helpful when using the table panel visualization.
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@@ -737,6 +745,8 @@ Here is the result after adding a Limit transformation with a value of '3':
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### Time series to table transform
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> **Note:** This transformation is available in Grafana 9.5+ as an opt-in beta feature. Modify Grafana [configuration file]({{< relref "../../../setup-grafana/configure-grafana/#configuration-file-location" >}}) to enable the `timeSeriesTable` [feature toggle]({{< relref "../../../setup-grafana/configure-grafana/#feature_toggles" >}}) to use it.
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{{% admonition type="note" %}}
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This transformation is available in Grafana 9.5+ as an opt-in beta feature. Modify Grafana [configuration file]({{< relref "../../../setup-grafana/configure-grafana/#configuration-file-location" >}}) to enable the `timeSeriesTable` [feature toggle]({{< relref "../../../setup-grafana/configure-grafana/#feature_toggles" >}}) to use it.
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{{% /admonition %}}
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Use this transformation to convert time series result into a table, converting time series data frame into a "Trend" field. "Trend" field can then be rendered using [sparkline cell type]({{< relref "../../visualizations/table/#sparkline" >}}), producing an inline sparkline for each table row. If there are multiple time series queries, each will result in a separate table data frame. These can be joined using join or merge transforms to produce a single table with multiple sparklines per row.
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