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[docs] many improvements to the documentation / cleanup (#4817) 

* fixed RSTs so images will show up on github
* fresh screenshots on main page
* removing irrelevant portions
* moved a set of sections under 'Misc'
* rebuilt the Gallery with all screenshots
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Maxime Beauchemin 2018-04-13 10:23:27 -07:00 committed by GitHub
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1
docs/_build/html/README.md vendored
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@ -1 +0,0 @@
Folder containing the sphinx-generated documentation

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docs/conf.py
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@ -52,7 +52,7 @@ master_doc = 'index'
# General information about the project.
project = "Apache Superset"
copyright = None
copyright = 'Apache Software Foundation'
author = u'Maxime Beauchemin'
# The version info for the project you're documenting, acts as replacement for

25
docs/druid.rst
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@ -1,16 +1,14 @@
Druid
=====
Superset works well with Druid, though currently not all
advanced features out of Druid are covered. This page clarifies what is
covered and what isn't and explains how to use some of the features.
Superset has a native connector to Druid, and a majority of Druid's
features are accessible through Superset.
.. note ::
Currently Airbnb runs against Druid ``0.8.x`` and previous /
following versions are not tested against.
Supported
'''''''''
Druid now supports SQL and can be accessed through Superset's
SQLAlchemy connector. The long term vision is to deprecate
the Druid native REST connector and query Druid exclusively through
the SQL interface.
Aggregations
------------
@ -28,7 +26,7 @@ element correspond to Druid aggregation definition. You can create your own
aggregations manually from the ``List Druid Metric`` tab following Druid
documentation.
.. image:: _static/img/druid_agg.png
.. image:: images/druid_agg.png
:scale: 50 %
Post-Aggregations
@ -41,8 +39,9 @@ json post-aggregation definition (as specified in the Druid docs) in the
Json field.
Not yet supported
'''''''''''''''''
Unsupported Features
--------------------
- Regex filters
- Lookups / joins
.. note ::
Unclear at this point, this section of the documentation could use
some input.

8
docs/faq.rst
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@ -48,8 +48,10 @@ https://github.com/airbnb/superset/issues?q=label%3Aexample+is%3Aclosed
Can I upload and visualize csv data?
------------------------------------
Yes, using the ``Upload a CSV`` button under the ``Sources``
menu item. This brings up a form that allows you specify required information. After creating the table from CSV, it can then be loaded like any other on the ``Sources -> Tables``page.
Yes, using the ``Upload a CSV`` button under the ``Sources`` menu item.
This brings up a form that allows you specify required information.
After creating the table from CSV, it can then be loaded like any
other on the ``Sources -> Tables`` page.
Why are my queries timing out?
@ -168,7 +170,7 @@ Here, the entire dashboard will refresh at once if periodic refresh is on. The s
2.5 seconds is ignored.
Why does fabmanager or superset freezed/hung/not responding when started (my home directory is NFS mounted)?
-----------------------------------------------------------------------------------------
------------------------------------------------------------------------------------------------------------
By default, superset creates and uses an sqlite database at ``~/.superset/superset.db``. Sqlite is known to `don't work well if used on NFS`__ due to broken file locking implementation on NFS.
__ https://www.sqlite.org/lockingv3.html

221
docs/gallery.rst
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@ -1,89 +1,190 @@
Gallery
=======
Visualizations Gallery
======================
.. image:: _static/img/viz_thumbnails/line.png
:scale: 50 %
.. image:: images/viz_thumbnails/area.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/bubble.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/table.png
:scale: 50 %
.. image:: images/viz_thumbnails/bar.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/pie.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/bar.png
:scale: 50 %
.. image:: images/viz_thumbnails/big_number.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/world_map.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/sankey.png
:scale: 50 %
.. image:: images/viz_thumbnails/big_number_total.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/word_cloud.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/filter_box.png
:scale: 50 %
.. image:: images/viz_thumbnails/box_plot.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/pivot_table.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/directed_force.png
:scale: 50 %
.. image:: images/viz_thumbnails/bubble.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/compare.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/sunburst.png
:scale: 50 %
.. image:: images/viz_thumbnails/bullet.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/area.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/big_number.png
:scale: 50 %
.. image:: images/viz_thumbnails/cal_heatmap.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/big_number_total.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/bullet.png
:scale: 50 %
.. image:: images/viz_thumbnails/chord.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/dist_bar.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/heatmap.png
:scale: 50 %
.. image:: images/viz_thumbnails/compare.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/markup.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/para.png
:scale: 50 %
.. image:: images/viz_thumbnails/country_map.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/iframe.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/box_plot.png
:scale: 50 %
.. image:: images/viz_thumbnails/deck_arc.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/treemap.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/cal_heatmap.png
:scale: 50 %
.. image:: images/viz_thumbnails/deck_geojson.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/horizon.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/mapbox.png
:scale: 50 %
.. image:: images/viz_thumbnails/deck_grid.png
:scale: 25 %
.. image:: _static/img/viz_thumbnails/separator.png
:scale: 50 %
.. image:: _static/img/viz_thumbnails/histogram.png
:scale: 50 %
.. image:: images/viz_thumbnails/deck_hex.png
:scale: 25 %
.. image:: images/viz_thumbnails/deck_multi.png
:scale: 25 %
.. image:: images/viz_thumbnails/deck_path.png
:scale: 25 %
.. image:: images/viz_thumbnails/deck_polygon.png
:scale: 25 %
.. image:: images/viz_thumbnails/deck_scatter.png
:scale: 25 %
.. image:: images/viz_thumbnails/deck_screengrid.png
:scale: 25 %
.. image:: images/viz_thumbnails/directed_force.png
:scale: 25 %
.. image:: images/viz_thumbnails/dist_bar.png
:scale: 25 %
.. image:: images/viz_thumbnails/dual_line.png
:scale: 25 %
.. image:: images/viz_thumbnails/event_flow.png
:scale: 25 %
.. image:: images/viz_thumbnails/filter_box.png
:scale: 25 %
.. image:: images/viz_thumbnails/heatmap.png
:scale: 25 %
.. image:: images/viz_thumbnails/histogram.png
:scale: 25 %
.. image:: images/viz_thumbnails/horizon.png
:scale: 25 %
.. image:: images/viz_thumbnails/iframe.png
:scale: 25 %
.. image:: images/viz_thumbnails/line.png
:scale: 25 %
.. image:: images/viz_thumbnails/mapbox.png
:scale: 25 %
.. image:: images/viz_thumbnails/markup.png
:scale: 25 %
.. image:: images/viz_thumbnails/paired_ttest.png
:scale: 25 %
.. image:: images/viz_thumbnails/para.png
:scale: 25 %
.. image:: images/viz_thumbnails/partition.png
:scale: 25 %
.. image:: images/viz_thumbnails/pie.png
:scale: 25 %
.. image:: images/viz_thumbnails/pivot_table.png
:scale: 25 %
.. image:: images/viz_thumbnails/rose.png
:scale: 25 %
.. image:: images/viz_thumbnails/sankey.png
:scale: 25 %
.. image:: images/viz_thumbnails/separator.png
:scale: 25 %
.. image:: images/viz_thumbnails/sunburst.png
:scale: 25 %
.. image:: images/viz_thumbnails/table.png
:scale: 25 %
.. image:: images/viz_thumbnails/time_pivot.png
:scale: 25 %
.. image:: images/viz_thumbnails/time_table.png
:scale: 25 %
.. image:: images/viz_thumbnails/treemap.png
:scale: 25 %
.. image:: images/viz_thumbnails/word_cloud.png
:scale: 25 %
.. image:: images/viz_thumbnails/world_map.png
:scale: 25 %

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../superset/assets/images/

15
docs/import_export_datasources.rst
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@ -49,12 +49,17 @@ By default, default (null) values will be omitted. Use the ``-d`` flag to includ
If you want back references to be included (e.g. a column to include the table id
it belongs to) use the ``-b`` flag.
Alternatively you can export datasources using the UI: ::
Alternatively you can export datasources using the UI:
1. Open **Sources** -> **Databases** to export all tables associated to a single or multiple databases. (**Tables** for one or more tables, **Druid Clusters** for clusters, **Druid Datasources** for datasources)
2. Select the items you would like to export
3. Click **Actions** -> **Export to YAML**
4. If you want to import an item that you exported through the UI, you will need to nest it inside its parent element, e.g. a `database` needs to be nested under `databases` a `table` needs to be nested inside a `database` element.
1. Open **Sources** -> **Databases** to export all tables associated to a
single or multiple databases. (**Tables** for one or more tables,
**Druid Clusters** for clusters, **Druid Datasources** for datasources)
#. Select the items you would like to export
#. Click **Actions** -> **Export to YAML**
#. If you want to import an item that you exported through the UI, you
will need to nest it inside its parent element, e.g. a `database`
needs to be nested under `databases` a `table` needs to be
nested inside a `database` element.
Exporting the complete supported YAML schema
--------------------------------------------

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docs/index.rst
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@ -1,4 +1,4 @@
.. image:: _static/img/s.png
.. image:: images/s.png
Apache Superset (incubating)
''''''''''''''''''''''''''''
@ -45,17 +45,22 @@ Features
- Integration with most SQL-speaking RDBMS through SQLAlchemy
- Deep integration with Druid.io
------
Screenshots
-----------
.. image:: https://camo.githubusercontent.com/82e264ef777ba06e1858766fe3b8817ee108eb7e/687474703a2f2f672e7265636f726469742e636f2f784658537661475574732e676966
.. image:: images/screenshots/bank_dash.png
------
.. image:: https://camo.githubusercontent.com/4991ff37a0005ea4e4267919a52786fda82d2d21/687474703a2f2f672e7265636f726469742e636f2f755a6767594f645235672e676966
.. image:: images/screenshots/explore.png
------
.. image:: https://camo.githubusercontent.com/a389af15ac1e32a3d0fee941b4c62c850b1d583b/687474703a2f2f672e7265636f726469742e636f2f55373046574c704c76682e676966
.. image:: images/screenshots/sqllab.png
------
.. image:: images/screenshots/deckgl_dash.png
------
@ -70,10 +75,9 @@ Contents
tutorial
security
sqllab
visualization
videos
gallery
druid
misc
faq

14
docs/installation.rst
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@ -208,7 +208,7 @@ In case that the reverse proxy is used for providing ssl encryption,
an explicit definition of the `X-Forwarded-Proto` may be required.
For the Apache webserver this can be set as follows: ::
　RequestHeader set X-Forwarded-Proto "https"
RequestHeader set X-Forwarded-Proto "https"
Configuration
-------------
@ -375,7 +375,7 @@ It is possible to tweak the database connection information using the
parameters exposed by SQLAlchemy. In the ``Database`` edit view, you will
find an ``extra`` field as a ``JSON`` blob.
.. image:: _static/img/tutorial/add_db.png
.. image:: images/tutorial/add_db.png
:scale: 30 %
This JSON string contains extra configuration elements. The ``engine_params``
@ -411,6 +411,16 @@ in your config file to point to that function. ::
SQLALCHEMY_CUSTOM_PASSWORD_STORE = example_lookup_password
A common pattern is to use environment variables to make secrets available.
``SQLALCHEMY_CUSTOM_PASSWORD_STORE`` can also be used for that purpose. ::
def example_password_as_env_var(url):
# assuming the uri looks like
# mysql://localhost?superset_user:{SUPERSET_PASSWORD}
return url.password.format(os.environ)
SQLALCHEMY_CUSTOM_PASSWORD_STORE = example_password_as_env_var
SSL Access to databases
-----------------------

10
docs/misc.rst Normal file
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@ -0,0 +1,10 @@
Misc
----
.. toctree::
:maxdepth: 2
visualization
videos
import_export_datasources

2
docs/security.rst
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@ -70,7 +70,7 @@ sure the users with limited access have [only] the Gamma role assigned to
them. Second, create a new role (``Menu -> Security -> List Roles``) and
click the ``+`` sign.
.. image:: _static/img/create_role.png
.. image:: images/create_role.png
:scale: 50 %
This new window allows you to give this new role a name, attribute it to users

5
docs/sqllab.rst
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@ -4,6 +4,11 @@ SQL Lab
SQL Lab is a modern, feature-rich SQL IDE written in
`React <https://facebook.github.io/react/>`_.
------
.. image:: images/screenshots/sqllab.png
------
Feature Overview
----------------

94
docs/tutorial.rst
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@ -1,31 +1,31 @@
Tutorial for Superset Administrators
====================================
Tutorial - Creating your first dashboard
========================================
This tutorial targets a Superset administrator: someone configuring Superset
for an organization on behalf of users. We'll show you how to connect Superset
to a new database and configure a table in that database for analysis. You'll
also explore the data you've exposed and add a visualization to a dashboard
This tutorial targets someone who wants to create charts and dashboards
in Superset. We'll show you how to connect Superset
to a new database and configure a table in that database for analysis. You'll
also explore the data you've exposed and add a visualization to a dashboard
so that you get a feel for the end-to-end user experience.
Connecting to a new database
----------------------------
We assume you already have a database configured and can connect to it from the
instance on which you’re running Superset. If you’re just testing Superset and
want to explore sample data, you can load some
instance on which you’re running Superset. If you’re just testing Superset and
want to explore sample data, you can load some
`sample PostgreSQL datasets <https://wiki.postgresql.org/wiki/Sample_Databases>`_
into a fresh DB, or configure the
into a fresh DB, or configure the
`example weather data <https://github.com/dylburger/noaa-ghcn-weather-data>`_
we use here.
Under the **Sources** menu, select the *Databases* option:
.. image:: _static/img/tutorial/tutorial_01_sources_database.png
.. image:: images/tutorial/tutorial_01_sources_database.png
:scale: 70%
On the resulting page, click on the green plus sign, near the top right:
.. image:: _static/img/tutorial/tutorial_02_add_database.png
.. image:: images/tutorial/tutorial_02_add_database.png
:scale: 70%
You can configure a number of advanced options on this page, but for
@ -33,12 +33,12 @@ this walkthrough, you’ll only need to do **two things**:
1. Name your database connection:
.. image:: _static/img/tutorial/tutorial_03_database_name.png
.. image:: images/tutorial/tutorial_03_database_name.png
:scale: 70%
2. Provide the SQLAlchemy Connection URI and test the connection:
.. image:: _static/img/tutorial/tutorial_04_sqlalchemy_connection_string.png
.. image:: images/tutorial/tutorial_04_sqlalchemy_connection_string.png
:scale: 70%
This example shows the connection string for our test weather database.
@ -51,19 +51,19 @@ Click the **Test Connection** button to confirm things work end to end.
Once Superset can successfully connect and authenticate, you should see
a popup like this:
.. image:: _static/img/tutorial/tutorial_05_connection_popup.png
.. image:: images/tutorial/tutorial_05_connection_popup.png
:scale: 50%
Moreover, you should also see the list of tables Superset can read from
the schema you’re connected to, at the bottom of the page:
.. image:: _static/img/tutorial/tutorial_06_list_of_tables.png
.. image:: images/tutorial/tutorial_06_list_of_tables.png
:scale: 70%
If the connection looks good, save the configuration by clicking the **Save**
button at the bottom of the page:
.. image:: _static/img/tutorial/tutorial_07_save_button.png
.. image:: images/tutorial/tutorial_07_save_button.png
:scale: 70%
Adding a new table
@ -74,25 +74,25 @@ to Superset that you’d like to query.
Under the **Sources** menu, select the *Tables* option:
.. image:: _static/img/tutorial/tutorial_08_sources_tables.png
.. image:: images/tutorial/tutorial_08_sources_tables.png
:scale: 70%
On the resulting page, click on the green plus sign, near the top left:
.. image:: _static/img/tutorial/tutorial_09_add_new_table.png
.. image:: images/tutorial/tutorial_09_add_new_table.png
:scale: 70%
You only need a few pieces of information to add a new table to Superset:
* The name of the table
.. image:: _static/img/tutorial/tutorial_10_table_name.png
.. image:: images/tutorial/tutorial_10_table_name.png
:scale: 70%
* The target database from the **Database** drop-down menu (i.e. the one
you just added above)
.. image:: _static/img/tutorial/tutorial_11_choose_db.png
.. image:: images/tutorial/tutorial_11_choose_db.png
:scale: 70%
* Optionally, the database schema. If the table exists in the “default” schema
@ -101,13 +101,13 @@ You only need a few pieces of information to add a new table to Superset:
Click on the **Save** button to save the configuration:
.. image:: _static/img/tutorial/tutorial_07_save_button.png
.. image:: images/tutorial/tutorial_07_save_button.png
:scale: 70%
When redirected back to the list of tables, you should see a message indicating
that your table was created:
.. image:: _static/img/tutorial/tutorial_12_table_creation_success_msg.png
.. image:: images/tutorial/tutorial_12_table_creation_success_msg.png
:scale: 70%
This message also directs you to edit the table configuration. We’ll edit a limited
@ -116,7 +116,7 @@ a more advanced tutorial.
Click on the edit button next to the table you’ve created:
.. image:: _static/img/tutorial/tutorial_13_edit_table_config.png
.. image:: images/tutorial/tutorial_13_edit_table_config.png
:scale: 70%
On the resulting page, click on the **List Table Column** tab. Here, you’ll define the
@ -136,7 +136,7 @@ Here’s how we’ve configured fields for the weather data. Even for measures l
weather measurements (precipitation, snowfall, etc.), it’s ideal to group and filter
by these values:
.. image:: _static/img/tutorial/tutorial_14_field_config.png
.. image:: images/tutorial/tutorial_14_field_config.png
As with the configurations above, click the **Save** button to save these settings.
@ -146,17 +146,17 @@ Exploring your data
To start exploring your data, simply click on the table name you just created in
the list of available tables:
.. image:: _static/img/tutorial/tutorial_15_click_table_name.png
.. image:: images/tutorial/tutorial_15_click_table_name.png
By default, you’ll be presented with a Table View:
.. image:: _static/img/tutorial/tutorial_16_datasource_chart_type.png
.. image:: images/tutorial/tutorial_16_datasource_chart_type.png
Let’s walk through a basic query to get the count of all records in our table.
First, we’ll need to change the **Since** filter to capture the range of our data.
You can use simple phrases to apply these filters, like "3 years ago":
.. image:: _static/img/tutorial/tutorial_17_choose_time_range.png
.. image:: images/tutorial/tutorial_17_choose_time_range.png
The upper limit for time, the **Until** filter, defaults to "now", which may or may
not be what you want.
@ -164,25 +164,25 @@ not be what you want.
Look for the Metrics section under the **GROUP BY** header, and start typing "Count"
- you’ll see a list of metrics matching what you type:
.. image:: _static/img/tutorial/tutorial_18_choose_metric.png
.. image:: images/tutorial/tutorial_18_choose_metric.png
Select the *COUNT(\*)* metric, then click the green **Query** button near the top
of the explore:
.. image:: _static/img/tutorial/tutorial_19_click_query.png
.. image:: images/tutorial/tutorial_19_click_query.png
You’ll see your results in the table:
.. image:: _static/img/tutorial/tutorial_20_count_star_result.png
.. image:: images/tutorial/tutorial_20_count_star_result.png
Let’s group this by the *weather_description* field to get the count of records by
the type of weather recorded by adding it to the *Group by* section:
.. image:: _static/img/tutorial/tutorial_21_group_by.png
.. image:: images/tutorial/tutorial_21_group_by.png
and run the query:
.. image:: _static/img/tutorial/tutorial_22_group_by_result.png
.. image:: images/tutorial/tutorial_22_group_by_result.png
Let’s find a more useful data point: the top 10 times and places that recorded the
highest temperature in 2015.
@ -190,11 +190,11 @@ highest temperature in 2015.
We replace *weather_description* with *latitude*, *longitude* and *measurement_date* in the
*Group by* section:
.. image:: _static/img/tutorial/tutorial_23_group_by_more_dimensions.png
.. image:: images/tutorial/tutorial_23_group_by_more_dimensions.png
And replace *COUNT(\*)* with *max__measurement_flag*:
.. image:: _static/img/tutorial/tutorial_24_max_metric.png
.. image:: images/tutorial/tutorial_24_max_metric.png
The *max__measurement_flag* metric was created when we checked the box under **Max** and
next to the *measurement_flag* field, indicating that this field was numeric and that
@ -206,16 +206,16 @@ precipitation and temperature). Therefore, we must filter our query only on reco
where the *weather_description* is equal to "Maximum temperature", which we do in
the **Filters** section at the bottom of the explore:
.. image:: _static/img/tutorial/tutorial_25_max_temp_filter.png
.. image:: images/tutorial/tutorial_25_max_temp_filter.png
Finally, since we only care about the top 10 measurements, we limit our results to
10 records using the *Row limit* option under the **Options** header:
.. image:: _static/img/tutorial/tutorial_26_row_limit.png
.. image:: images/tutorial/tutorial_26_row_limit.png
We click **Query** and get the following results:
.. image:: _static/img/tutorial/tutorial_27_top_10_max_temps.png
.. image:: images/tutorial/tutorial_27_top_10_max_temps.png
In this dataset, the maximum temperature is recorded in tenths of a degree Celsius.
The top value of 1370, measured in the middle of Nevada, is equal to 137 C, or roughly
@ -240,20 +240,20 @@ a dashboard.
We change the Chart Type to "Distribution - Bar Chart":
.. image:: _static/img/tutorial/tutorial_28_bar_chart.png
.. image:: images/tutorial/tutorial_28_bar_chart.png
Our filter on Maximum temperature measurements was retained, but the query and
formatting options are dependent on the chart type, so you’ll have to set the
values again:
.. image:: _static/img/tutorial/tutorial_29_bar_chart_series_metrics.png
.. image:: images/tutorial/tutorial_29_bar_chart_series_metrics.png
You should note the extensive formatting options for this chart: the ability to
set axis labels, margins, ticks, etc. To make the data presentable to a broad
audience, you’ll want to apply many of these to slices that end up in dashboards.
For now, though, we run our query and get the following chart:
.. image:: _static/img/tutorial/tutorial_30_bar_chart_results.png
.. image:: images/tutorial/tutorial_30_bar_chart_results.png
:scale: 70%
Creating a slice and dashboard
@ -265,39 +265,39 @@ a saved query is called a **Slice**.
To create a slice, click the **Save as** button near the top-left of the
explore:
.. image:: _static/img/tutorial/tutorial_19_click_query.png
.. image:: images/tutorial/tutorial_19_click_query.png
A popup should appear, asking you to name the slice, and optionally add it to a
dashboard. Since we haven’t yet created any dashboards, we can create one and
immediately add our slice to it. Let’s do it:
.. image:: _static/img/tutorial/tutorial_31_save_slice_to_dashboard.png
.. image:: images/tutorial/tutorial_31_save_slice_to_dashboard.png
:scale: 70%
Click Save, which will direct you back to your original query. We see that
our slice and dashboard were successfully created:
.. image:: _static/img/tutorial/tutorial_32_save_slice_confirmation.png
.. image:: images/tutorial/tutorial_32_save_slice_confirmation.png
:scale: 70%
Let’s check out our new dashboard. We click on the **Dashboards** menu:
.. image:: _static/img/tutorial/tutorial_33_dashboard.png
.. image:: images/tutorial/tutorial_33_dashboard.png
and find the dashboard we just created:
.. image:: _static/img/tutorial/tutorial_34_weather_dashboard.png
.. image:: images/tutorial/tutorial_34_weather_dashboard.png
Things seemed to have worked - our slice is here!
.. image:: _static/img/tutorial/tutorial_35_slice_on_dashboard.png
.. image:: images/tutorial/tutorial_35_slice_on_dashboard.png
:scale: 70%
But it’s a bit smaller than we might like. Luckily, you can adjust the size
of slices in a dashboard by clicking, holding and dragging the bottom-right
corner to your desired dimensions:
.. image:: _static/img/tutorial/tutorial_36_adjust_dimensions.gif
.. image:: images/tutorial/tutorial_36_adjust_dimensions.gif
:scale: 120%
After adjusting the size, you’ll be asked to click on the icon near the

53
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@ -1,54 +1,5 @@
Videos
======
Here is a collection of short videos showing different aspect
of Superset.
Quick Intro
'''''''''''
This video demonstrates how Superset works at a high level, it shows how
to navigate through datasets and dashboards that are already available.
.. youtube:: https://www.youtube.com/watch?v=3Txm_nj_R7M
Dashboard Creation
''''''''''''''''''
This video walk you through the creation of a simple dashboard as a
collection of data slices.
- Coming soon!
Dashboard Filtering
'''''''''''''''''''
This video shows how to create dynamic filters on dashboards, how to
immunize certain widgets from being affected by filters.
- Coming soon!
Customize CSS and dashboard themes
''''''''''''''''''''''''''''''''''
A quick walkthrough on how to apply existing CSS templates, alter them and
create new ones.
- Coming soon!
Slice Annotations
'''''''''''''''''
A short video on how to annotate your charts, the markdown language and
to toggle them on dashboards.
- Coming soon!
Adding a Table
''''''''''''''
This videos shows you how to expose a new table in Superset, and how to
define the semantics on how this can be accessed by others in the ``Explore``
and ``Dashboard`` views.
- Coming soon!
Define SQL Expressions
''''''''''''''''''''''
A walkthrough on how to create your own derived dimensions and metrics.
- Coming soon!
.. note ::
This section of the documentation has yet to be filled in.

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