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feat(build): migrate from Prettier to Oxfmt for performant code formatting (#42434)
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Đỗ Trọng Hải
@@ -5,13 +5,13 @@ sidebar_position: 1
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version: 1
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---
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import useBaseUrl from "@docusaurus/useBaseUrl";
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import useBaseUrl from '@docusaurus/useBaseUrl';
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## Creating Your First Dashboard
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This section is focused on documentation for end-users who will be using Superset
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for the data analysis and exploration workflow
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(data analysts, business analysts, data
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(data analysts, business analysts, data
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scientists, etc).
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:::tip
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@@ -37,22 +37,44 @@ pre-configured in Superset for you.
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Under the **+** menu in the top right, select Data, and then the _Connect Database_ option:
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<img src={useBaseUrl("/img/tutorial/tutorial_01_add_database_connection.png")} width="600" />{" "} <br/><br/>
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<img
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src={useBaseUrl('/img/tutorial/tutorial_01_add_database_connection.png')}
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width="600"
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/>
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<br />
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<br />
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Then select your database type in the resulting modal:
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<img src={useBaseUrl("/img/tutorial/tutorial_02_select_database.png" )} width="600" />{" "} <br/><br/>
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<img
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src={useBaseUrl('/img/tutorial/tutorial_02_select_database.png')}
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width="600"
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/>
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<br />
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<br />
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Once you've selected a database, you can configure a number of advanced options in this window,
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or for the purposes of this walkthrough, you can click the link below all these fields:
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<img src={useBaseUrl("/img/tutorial/tutorial_03a_database_connection_string_link.png" )} width="600" />{" "} <br/><br/>
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<img
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src={useBaseUrl(
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'/img/tutorial/tutorial_03a_database_connection_string_link.png',
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)}
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width="600"
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/>
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<br />
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<br />
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Please note, if you are trying to connect to another locally running database (whether on host or another container), and you get the message `The port is closed.`, then you need to adjust the HOST to `host.docker.internal`
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Once you've clicked that link you only need to specify two things (the database name and SQLAlchemy URI):
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<img src={useBaseUrl("/img/tutorial/tutorial_03b_connection_string_details.png" )} width="600" />{" "} <br/><br/>
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<img
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src={useBaseUrl('/img/tutorial/tutorial_03b_connection_string_details.png')}
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width="600"
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/>
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<br />
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<br />
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As noted in the text below the form, you should refer to the SQLAlchemy documentation on
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[creating new connection URIs](https://docs.sqlalchemy.org/en/12/core/engines.html#database-urls)
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@@ -70,28 +92,28 @@ that you want exposed in Superset for querying.
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Navigate to **Data ‣ Datasets** and select the **+ Dataset** button in the top right corner.
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<img src={useBaseUrl("/img/tutorial/tutorial_08_sources_tables.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_08_sources_tables.png')} />
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A modal window should pop up in front of you. Select your **Database**,
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**Schema**, and **Table** using the drop downs that appear. In the following example,
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we register the **cleaned_sales_data** table from the **examples** database.
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<img src={useBaseUrl("/img/tutorial/tutorial_09_add_new_table.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_09_add_new_table.png')} />
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To finish, click the **Add** button in the bottom right corner. You should now see your dataset in the list of datasets.
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### Customizing column properties
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Now that you've registered your dataset, you can configure column properties
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for how the column should be treated in the Explore workflow:
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for how the column should be treated in the Explore workflow:
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- Is the column temporal? (should it be used for slicing & dicing in time series charts?)
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- Should the column be filterable?
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- Is the column dimensional?
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- If it's a datetime column, how should Superset parse
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the datetime format? (using the [ISO-8601 string pattern](https://en.wikipedia.org/wiki/ISO_8601))
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the datetime format? (using the [ISO-8601 string pattern](https://en.wikipedia.org/wiki/ISO_8601))
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<img src={useBaseUrl("/img/tutorial/tutorial_column_properties.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_column_properties.png')} />
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### Superset semantic layer
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@@ -99,53 +121,55 @@ Superset has a thin semantic layer that adds many quality of life improvements f
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The Superset semantic layer can store 2 types of computed data:
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1. Virtual metrics: you can write SQL queries that aggregate values
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from multiple column (e.g. `SUM(recovered) / SUM(confirmed)`) and make them
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available as columns for (e.g. `recovery_rate`) visualization in Explore.
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Aggregate functions are allowed and encouraged for metrics.
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from multiple column (e.g. `SUM(recovered) / SUM(confirmed)`) and make them
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available as columns for (e.g. `recovery_rate`) visualization in Explore.
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Aggregate functions are allowed and encouraged for metrics.
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<img src={useBaseUrl("/img/tutorial/tutorial_sql_metric.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_sql_metric.png')} />
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You can also certify metrics if you'd like for your team in this view.
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1. Virtual calculated columns: you can write SQL queries that
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customize the appearance and behavior
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of a specific column (e.g. `CAST(recovery_rate as float)`).
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Aggregate functions aren't allowed in calculated columns.
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customize the appearance and behavior
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of a specific column (e.g. `CAST(recovery_rate as float)`).
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Aggregate functions aren't allowed in calculated columns.
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<img src={useBaseUrl("/img/tutorial/tutorial_calculated_column.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_calculated_column.png')} />
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### Creating charts in Explore view
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Superset has 2 main interfaces for exploring data:
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- **Explore**: no-code viz builder. Select your dataset, select the chart,
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customize the appearance, and publish.
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customize the appearance, and publish.
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- **SQL Lab**: SQL IDE for cleaning, joining, and preparing data for Explore workflow
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We'll focus on the Explore view for creating charts right now.
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To start the Explore workflow from the **Datasets** tab, start by clicking the name
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of the dataset that will be powering your chart.
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<img src={useBaseUrl("/img/tutorial/tutorial_launch_explore.png" )} /><br/><br/>
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<img src={useBaseUrl('/img/tutorial/tutorial_launch_explore.png')} />
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<br />
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<br />
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You're now presented with a powerful workflow for exploring data and iterating on charts.
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- The **Dataset** view on the left-hand side has a list of columns and metrics,
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scoped to the current dataset you selected.
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scoped to the current dataset you selected.
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- The **Data** preview below the chart area also gives you helpful data context.
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- Using the **Data** tab and **Customize** tabs, you can change the visualization type,
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select the temporal column, select the metric to group by, and customize
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the aesthetics of the chart.
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select the temporal column, select the metric to group by, and customize
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the aesthetics of the chart.
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As you customize your chart using drop-down menus, make sure to click the **Run** button
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to get visual feedback.
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<img src={useBaseUrl("/img/tutorial/tutorial_explore_run.jpg" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_explore_run.jpg')} />
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In the following screenshot, we craft a grouped Time-series Bar Chart to visualize
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our quarterly sales data by product line just by clicking options in drop-down menus.
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<img src={useBaseUrl("/img/tutorial/tutorial_explore_settings.jpg" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_explore_settings.jpg')} />
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### Creating a slice and dashboard
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@@ -156,26 +180,32 @@ To save your chart, first click the **Save** button. You can either:
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In the following screenshot, we save the chart to a new "Superset Duper Sales Dashboard":
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<img src={useBaseUrl("/img/tutorial/tutorial_save_slice.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_save_slice.png')} />
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To publish, click **Save and goto Dashboard**.
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Behind the scenes, Superset will create a slice and store all the information needed
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to create your chart in its thin data layer
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(the query, chart type, options selected, name, etc).
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(the query, chart type, options selected, name, etc).
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<img src={useBaseUrl("/img/tutorial/tutorial_first_dashboard.png" )} style={{width: "100%", maxWidth: "500px"}} />
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<img
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src={useBaseUrl('/img/tutorial/tutorial_first_dashboard.png')}
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style={{ width: '100%', maxWidth: '500px' }}
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/>
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To resize the chart, start by clicking the Edit Dashboard button in the top right corner.
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To resize the chart, start by clicking the Edit Dashboard button in the top right corner.
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<img src={useBaseUrl("/img/tutorial/tutorial_edit_button.png" )} width="300" />
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<img src={useBaseUrl('/img/tutorial/tutorial_edit_button.png')} width="300" />
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Then, click and drag the bottom right corner of the chart until the chart layout snaps
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into a position you like onto the underlying grid.
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<img src={useBaseUrl("/img/tutorial/tutorial_chart_resize.png" )} style={{width: "100%", maxWidth: "500px"}} />
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<img
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src={useBaseUrl('/img/tutorial/tutorial_chart_resize.png')}
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style={{ width: '100%', maxWidth: '500px' }}
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/>
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Click **Save** to persist the changes.
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Click **Save** to persist the changes.
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Congrats! You’ve successfully linked, analyzed, and visualized data in Superset. There are a wealth
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of other table configuration and visualization options, so please start exploring and creating
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@@ -192,14 +222,14 @@ Non-owner users access can be managed in two different ways. The dashboard needs
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- Granting a role access to a dashboard will bypass dataset level checks. Having dashboard access implicitly grants read access to all the featured charts in the dashboard, and thereby also all the associated datasets.
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- If no roles are specified for a dashboard, regular **Dataset permissions** will apply.
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<img src={useBaseUrl("/img/tutorial/tutorial_dashboard_access.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_dashboard_access.png')} />
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### Publishing a Dashboard
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If you would like to make your dashboard available to other users, click on the `Draft` button next to the
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title of your dashboard.
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<img src={useBaseUrl("/img/tutorial/publish_button_dashboard.png" )} />
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<img src={useBaseUrl('/img/tutorial/publish_button_dashboard.png')} />
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:::warning
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Draft dashboards are only visible to the dashboard owners and admins. Published dashboards are visible to all users with access to the underlying datasets or if RBAC is enabled, to the roles that have been granted access to the dashboard.
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@@ -5,7 +5,7 @@ sidebar_position: 2
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version: 1
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---
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import useBaseUrl from "@docusaurus/useBaseUrl";
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import useBaseUrl from '@docusaurus/useBaseUrl';
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## Exploring Data in Superset
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@@ -30,12 +30,12 @@ explains how to enable this functionality for the examples database.
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In the top menu, select **Settings ‣ Data ‣ Database Connections**. Find the **examples** database in the list and
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select the **Edit** button.
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<img src={useBaseUrl("/img/tutorial/edit-record.png" )} />
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<img src={useBaseUrl('/img/tutorial/edit-record.png')} />
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In the resulting modal window, switch to the **Advanced** tab and open **Security** section.
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Then, tick the checkbox for **Allow file uploads to database**. End by clicking the **Finish** button.
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<img src={useBaseUrl("/img/tutorial/allow-file-uploads.png" )} />
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<img src={useBaseUrl('/img/tutorial/allow-file-uploads.png')} />
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### Loading CSV Data
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@@ -43,16 +43,16 @@ Download the CSV dataset to your computer from
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[GitHub](https://raw.githubusercontent.com/apache-superset/examples-data/master/tutorial_flights.csv).
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In the top menu, select **Settings ‣ Data ‣ Database Connections**. Then, **Upload file to database ‣ Upload CSV**.
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<img src={useBaseUrl("/img/tutorial/upload_a_csv.png" )} />
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<img src={useBaseUrl('/img/tutorial/upload_a_csv.png')} />
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Then, select select the CSV file from your computer, select **Database** and **Schema**, and enter the **Table Name**
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as _tutorial_flights_.
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<img src={useBaseUrl("/img/tutorial/csv_to_database_configuration.png" )} />
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<img src={useBaseUrl('/img/tutorial/csv_to_database_configuration.png')} />
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Next enter the text _Travel Date_ into the **File settings ‣ Columns to be parsed as dates** field.
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<img src={useBaseUrl("/img/tutorial/parse_dates_column.png" )} />
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<img src={useBaseUrl('/img/tutorial/parse_dates_column.png')} />
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Leaving all the other options in their default settings, select **Upload** at the bottom of the page.
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@@ -68,7 +68,7 @@ By default, Apache Superset only shows the last week of data. In our example, we
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of the data in the dataset. Click the **Time ‣ Time Range** section and change
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the **Range Type** to **No Filter**.
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<img src={useBaseUrl("/img/tutorial/no_filter_on_time_filter.png" )} />
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<img src={useBaseUrl('/img/tutorial/no_filter_on_time_filter.png')} />
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Click **Apply** to save.
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@@ -78,24 +78,24 @@ example, we want to understand different Travel Classes, we select **Travel Clas
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Next, we can specify the metrics we would like to see in our table with the **Metrics** option.
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- `COUNT(*)`, which represents the number of rows in the table
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(in this case, quantity of flights in each Travel Class)
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(in this case, quantity of flights in each Travel Class)
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- `SUM(Cost)`, which represents the total cost spent by each Travel Class
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<img src={useBaseUrl("/img/tutorial/sum_cost_column.png" )} />
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<img src={useBaseUrl('/img/tutorial/sum_cost_column.png')} />
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Finally, select **Run Query** to see the results of the table.
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<img src={useBaseUrl("/img/tutorial/tutorial_table.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_table.png')} />
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To save the visualization, click on **Save** in the top left of the screen. In the following modal,
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- Select the **Save as**
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option and enter the chart name as Tutorial Table (you will be able to find it again through the
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**Charts** screen, accessible in the top menu).
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option and enter the chart name as Tutorial Table (you will be able to find it again through the
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**Charts** screen, accessible in the top menu).
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- Select **Add To Dashboard** and enter
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Tutorial Dashboard. Finally, select **Save & Go To Dashboard**.
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Tutorial Dashboard. Finally, select **Save & Go To Dashboard**.
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<img src={useBaseUrl("/img/tutorial/save_tutorial_table.png" )} />
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<img src={useBaseUrl('/img/tutorial/save_tutorial_table.png')} />
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### Dashboard Basics
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@@ -107,7 +107,7 @@ On this dashboard you should see the table you created in the previous section.
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dashboard** and then hover over the table. By selecting the bottom right hand corner of the table
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(the cursor will change too), you can resize it by dragging and dropping.
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<img src={useBaseUrl("/img/tutorial/resize_tutorial_table_on_dashboard.png" )} />
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<img src={useBaseUrl('/img/tutorial/resize_tutorial_table_on_dashboard.png')} />
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Finally, save your changes by selecting Save changes in the top right.
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@@ -122,7 +122,7 @@ tutorial_flights again as a datasource, then click on the visualization type to
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visualization menu. Select the **Pivot Table** visualization (you can filter by entering text in the
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search box) and then **Create New Chart**.
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<img src={useBaseUrl("/img/tutorial/create_pivot.png" )} />
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<img src={useBaseUrl('/img/tutorial/create_pivot.png')} />
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In the **Time** section, keep the Time Column as Travel Date (this is selected automatically as we
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only have one time column in our dataset). Then select Time Grain to be month as having daily data
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@@ -132,7 +132,7 @@ January 2011 and 30th June 2011 respectively by either entering directly the dat
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calendar widget (by selecting the month name and then the year, you can move more quickly to far
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away dates).
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||||
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||||
<img src={useBaseUrl("/img/tutorial/select_dates_pivot_table.png" )} />
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<img src={useBaseUrl('/img/tutorial/select_dates_pivot_table.png')} />
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||||
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Next, within the **Query** section, remove the default COUNT(\*) and add Cost, keeping the default
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SUM aggregate. Note that Apache Superset will indicate the type of the metric by the symbol on the
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@@ -144,7 +144,7 @@ selections we defined in the Time section.
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Within **Columns**, first select Department and then Travel Class. All set – let’s **Run Query** to
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||||
see some data!
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||||
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||||
<img src={useBaseUrl("/img/tutorial/tutorial_pivot_table.png" )} />
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||||
<img src={useBaseUrl('/img/tutorial/tutorial_pivot_table.png')} />
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||||
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You should see months in the rows and Department and Travel Class in the columns. Publish this chart
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to your existing Tutorial Dashboard you created earlier.
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@@ -159,7 +159,7 @@ time for the Time range select No filter as we want to look at entire dataset.
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Within Metrics, remove the default `COUNT(*)` metric and instead add `AVG(Cost)`, to show the mean value.
|
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||||
<img src={useBaseUrl("/img/tutorial/average_aggregate_for_cost.png" )} />
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<img src={useBaseUrl('/img/tutorial/average_aggregate_for_cost.png')} />
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||||
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Next, select **Run Query** to show the data on the chart.
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@@ -176,7 +176,7 @@ tab on the left hand pane. Within this pane, try changing the Color Scheme, remo
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filter by selecting No in the Show Range Filter drop down and adding some labels using X Axis Label
|
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and Y Axis Label.
|
||||
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||||
<img src={useBaseUrl("/img/tutorial/tutorial_line_chart.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/tutorial_line_chart.png')} />
|
||||
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Once you’re done, publish the chart in your Tutorial Dashboard.
|
||||
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@@ -189,14 +189,14 @@ dashboards. Got into edit mode by selecting **Edit dashboard**.
|
||||
Within the Insert components pane, drag and drop a Markdown box on the dashboard. Look for the blue
|
||||
lines which indicate the anchor where the box will go.
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/blue_bar_insert_component.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/blue_bar_insert_component.png')} />
|
||||
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||||
Now, to edit the text, select the box. You can enter text, in markdown format (see
|
||||
[this Markdown Cheatsheet](https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet) for
|
||||
more information about this format). You can toggle between Edit and Preview using the menu on the
|
||||
top of the box.
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/markdown.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/markdown.png')} />
|
||||
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||||
To exit, select any other part of the dashboard. Finally, don’t forget to keep your changes using
|
||||
**Save changes**.
|
||||
@@ -211,7 +211,7 @@ If you would like to make your dashboard available to other users, simply select
|
||||
title of your dashboard on the top left to change your dashboard to be in Published state. You can
|
||||
also favorite this dashboard by selecting the star.
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/publish_dashboard.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/publish_dashboard.png')} />
|
||||
|
||||
### Annotations
|
||||
|
||||
@@ -228,7 +228,7 @@ Next, add an annotation by navigating to Manage ‣ Annotations and then create
|
||||
selecting the green plus sign. Then, select the Volcanic Eruptions layer, add a short description
|
||||
Grímsvötn and the eruption dates (23-25 May 2011) before finally saving.
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/edit_annotation.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/edit_annotation.png')} />
|
||||
|
||||
Then, navigate to the line chart by going to Charts then selecting Tutorial Line Chart from the
|
||||
list. Next, go to the Annotations and Layers section and select Add Annotation Layer. Within this
|
||||
@@ -239,11 +239,11 @@ dialogue:
|
||||
- Set the Annotation Source as Superset annotation
|
||||
- Specify the Annotation Layer as Volcanic Eruptions
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/annotation_settings.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/annotation_settings.png')} />
|
||||
|
||||
Select **Apply** to see your annotation shown on the chart.
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/annotation.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/annotation.png')} />
|
||||
|
||||
If you wish, you can change how your annotation looks by changing the settings in the Display
|
||||
configuration section. Otherwise, select **OK** and finally **Save** to save your chart. If you keep
|
||||
@@ -265,7 +265,7 @@ datasource and the **Line Chart** visualization type. Within the Time section, s
|
||||
Next, in the query section, change the Metrics to the sum of Cost. Select **Run Query** to show the
|
||||
chart. You should see the total cost per day for each month in October 2011.
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/advanced_analytics_base.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/advanced_analytics_base.png')} />
|
||||
|
||||
Finally, save the visualization as Tutorial Advanced Analytics Base, adding it to the Tutorial
|
||||
Dashboard.
|
||||
@@ -284,7 +284,7 @@ on 7 days and we avoid any ramp up period.
|
||||
After displaying the chart by selecting **Run Query** you will see that the data is less variable
|
||||
and that the series starts later as the ramp up period is excluded.
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/rolling_mean.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/rolling_mean.png')} />
|
||||
|
||||
Save the chart as Tutorial Rolling Mean and add it to the Tutorial Dashboard.
|
||||
|
||||
@@ -299,13 +299,15 @@ Next, in the Time Comparison subsection of **Advanced Analytics**, enter the Tim
|
||||
“minus 1 week” (note this box accepts input in natural language). Run Query to see the new chart,
|
||||
which has an additional series with the same values, shifted a week back in time.
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/time_comparison_two_series.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/time_comparison_two_series.png')} />
|
||||
|
||||
Then, change the **Calculation type** to Absolute difference and select **Run Query**. We can now
|
||||
see only one series again, this time showing the difference between the two series we saw
|
||||
previously.
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/time_comparison_absolute_difference.png" )} />
|
||||
<img
|
||||
src={useBaseUrl('/img/tutorial/time_comparison_absolute_difference.png')}
|
||||
/>
|
||||
|
||||
Save the chart as Tutorial Time Comparison and add it to the Tutorial Dashboard.
|
||||
|
||||
@@ -317,7 +319,7 @@ As in the previous section, reopen the Tutorial Advanced Analytics Base chart.
|
||||
Next, in the Python Functions subsection of **Advanced Analytics**, enter 7D, corresponding to seven
|
||||
days, in the Rule and median as the Method and show the chart by selecting **Run Query**.
|
||||
|
||||
<img src={useBaseUrl("/img/tutorial/resample.png" )} />
|
||||
<img src={useBaseUrl('/img/tutorial/resample.png')} />
|
||||
|
||||
Note that now we have a single data point every 7 days. In our case, the value showed corresponds to
|
||||
the median value within the seven daily data points. For more information on the meaning of the
|
||||
|
||||
Reference in New Issue
Block a user