documentation and cleaning

* added notebook gallery
* update README
* removed scatterplot message in SQLExecutor
* fixed typo in SQL documentation

README.md

@@ -28,11 +28,16 @@
     </a>
 </p>
 
-Lux is a Python library that makes data science easier by automating aspects of the data exploration process. Lux facilitate faster experimentation with data, even when the user does not have a clear idea of what they are looking for. Visualizations are displayed via [an interactive widget](https://github.com/lux-org/lux-widget) that allow users to quickly browse through large collections of visualizations directly within their Jupyter notebooks.
+Lux is a Python library that facilitate fast and easy data exploration by automating the visualization and data analysis process. By simply printing out a dataframe in a Jupyter notebook, Lux recommends a set of visualizations highlighting interesting trends and patterns in the dataset. Visualizations are displayed via [an interactive widget](https://github.com/lux-org/lux-widget) that enables users to quickly browse through large collections of visualizations and make sense of their data.
 
+<img src="https://github.com/lux-org/lux-resources/blob/master/readme_img/demohighlight.gif?raw=true"
+     alt="Highlighted Visual Dataframe Workflow with Lux"
+     style="width:900px" />
+
 Here is a [1-min video](https://www.youtube.com/watch?v=qmnYP-LmbNU) introducing Lux, and [slides](http://dorisjunglinlee.com/files/Zillow_07_2020_Slide.pdf) from a more extended talk.
 
-Try out Lux on your own in a live Jupyter Notebook [here](https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/demo/employee_demo.ipynb)! 
+Check out our [notebook gallery](https://lux-api.readthedocs.io/en/latest/source/reference/gallery.html) with examples of how Lux can be used with a variety of dataset and analysis scenarios. 
+<br>Or try out Lux on your own in a [live Jupyter Notebook](https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/demo/employee_demo.ipynb)! 
 
 # Getting Started
 
@@ -93,7 +98,7 @@ df
 
 ### Easy programmatic access and export of visualizations: 
 
-Now that we have found some interesting visualizations through Lux, we might be interested in digging into these visualizations a bit more or sharing it with others. We can save the visualizations generated in Lux as a [static, shareable HTML](https://lux-api.readthedocs.io/en/latest/source/guide/export.html#exporting-widget-visualizations-as-static-html) or programmatically access these visualizations further in Jupyter. Selected `Vis` objects can be translated into [Altair](http://altair-viz.github.io/) or [Vega-Lite](https://vega.github.io/vega-lite/) code, so that they can be further edited.
+Now that we have found some interesting visualizations through Lux, we might be interested in digging into these visualizations a bit more or sharing it with others. We can save the visualizations generated in Lux as a [static, shareable HTML](https://lux-api.readthedocs.io/en/latest/source/guide/export.html#exporting-widget-visualizations-as-static-html) or programmatically access these visualizations further in Jupyter. Selected `Vis` objects can be translated into [Altair](http://altair-viz.github.io/), [Matplotlib](https://matplotlib.org/), or [Vega-Lite](https://vega.github.io/vega-lite/) code, so that they can be further edited.
 
 <img src="https://github.com/lux-org/lux-resources/blob/master/readme_img/export.gif?raw=true"
      alt="Easily exportable visualization object"
@@ -134,7 +139,7 @@ To find out more about other features in Lux, see the complete documentation on
 # Installation & Setup
 
 To get started, please follow both the installation and setup instructions in your command line.
-`lux-api` can be installed through [PyPI](https://pypi.org/project/lux-api/). 
+`lux-api` can be installed through [PyPI](https://pypi.org/project/lux-api/) or [conda-forge](https://github.com/conda-forge/lux-api-feedstock). 
 
 ```bash
 pip install lux-api
@@ -162,13 +167,13 @@ Note that you may have to restart the Jupyter Notebook server to ensure that the
 
 ## Setup in Jupyter Lab
 
-To use Lux in [Jupyter Lab](https://github.com/jupyterlab/jupyterlab), activate the lab extension:
+Lux is compatible with both Jupyter Lab version 2 and 3. To use Lux in [Jupyter Lab](https://github.com/jupyterlab/jupyterlab), activate the lab extension:
 
 ```bash
 jupyter labextension install @jupyter-widgets/jupyterlab-manager
 jupyter labextension install luxwidget
 ```
-Lux is only compatible with Jupyter Lab version 2.2.9 and below. Support for the recent [JupyterLab 3](https://blog.jupyter.org/jupyterlab-3-0-is-out-4f58385e25bb) will come soon. Note that JupyterLab and VSCode is supported only for lux-widget version >=0.1.2, if you have an earlier version, please upgrade to the latest version of [lux-widget](https://pypi.org/project/lux-widget/). Lux has only been tested with the Chrome browser. 
+Note that JupyterLab and VSCode is supported only for lux-widget version >=0.1.2, if you have an earlier version, please upgrade to the latest version of [lux-widget](https://pypi.org/project/lux-widget/). Lux has only been tested with the Chrome browser. 
 
 If you encounter issues with the installation, please refer to [this page](https://lux-api.readthedocs.io/en/latest/source/guide/FAQ.html#troubleshooting-tips) to troubleshoot the installation. Follow [these instructions](https://lux-api.readthedocs.io/en/latest/source/getting_started/installation.html#manual-installation-dev-setup) to set up Lux for development purposes.
 

doc/source/advanced/executor.rst

@@ -42,7 +42,7 @@ To do this, users first need to specify a connection to their SQL database. This
 	engine = create_engine("postgresql://postgres:lux@localhost:5432")
 
 Note that users will have to install these packages on their own if they want to connect Lux to their databases.
-Once this connection is created, users can connect the lux config to the database using the :code:`set_SQL_connection` command.
+Once this connection is created, users can connect Lux to their database using the :code:`set_SQL_connection` command.
 
 .. code-block:: python
 
@@ -54,7 +54,6 @@ Connecting a LuxSQLTable to a Table/View
 ----------------------------------------
 
 LuxSQLTables can be connected to individual tables or views created within your Postgresql database. This can be done by specifying the table or view name in the constructor. 
-.. We are actively working on supporting joins between multiple tables. But as of now, the functionality is limited to one table or view per LuxSQLTable object only.
 
 .. code-block:: python
 

doc/source/reference/gallery.rst

@@ -0,0 +1,61 @@
+
+Gallery of Notebook Examples
+==============================
+
+Demo Examples
+------------------
+The following notebooks demonstrates how Lux can be used with a variety of different datasets and analysis
+
+- Basic walkthrough of Lux with the Cars dataset [`Source <https://github.com/lux-org/lux-binder/blob/master/demo/cars_demo.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/demo/cars_demo.ipynb>`_]
+- Basic walkthrough of Lux with the College dataset [`Source <https://github.com/lux-org/lux-binder/blob/master/demo/college_demo.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/demo/college_demo.ipynb>`_]
+- Understanding Global COVID-19 intervention levels [`Source <https://github.com/lux-org/lux-binder/blob/master/demo/hpi_covid_demo.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/demo/hpi_covid_demo.ipynb>`_]
+- Understanding factors leading to Employee attrition [`Source <https://github.com/lux-org/lux-binder/blob/master/demo/employee_demo.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/demo/employee_demo.ipynb>`_]
+
+If you would like to try out Lux on your own, we provide a `notebook environment <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/demo/exercise/4-Data-Playground.ipynb>`_ for you to play around with several provided example datasets.
+
+Tutorials
+---------
+
+The following tutorials cover the most basic to advanced features in Lux. The first five tutorials introduces the core features in Lux:
+
+- Overview of Features in Lux [`Source <https://github.com/lux-org/lux-binder/blob/master/tutorial/0-overview.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/tutorial/0-overview.ipynb>`_]
+- Specifying user analysis intent in Lux [`Source <https://github.com/lux-org/lux-binder/blob/master/tutorial/1-specifying-intent.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/tutorial/1-specifying-intent.ipynb>`_]
+- Creating quick-and-dirty visualizations with :code:`Vis` and :code:`VisList` [`Source <https://github.com/lux-org/lux-binder/blob/master/tutorial/2-constructing-vis-and-vislist.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/tutorial/2-constructing-vis-and-vislist.ipynb>`_]
+- Seamless export of :code:`Vis` from notebook to downstream tasks [`Source <https://github.com/lux-org/lux-binder/blob/master/tutorial/3-widget-vis-export.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/tutorial/3-widget-vis-export.ipynb>`_]
+- Customizing plot styling with :code:`lux.config.plotting_style` [`Source <https://github.com/lux-org/lux-binder/blob/master/tutorial/4-chart-settings.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/tutorial/4-chart-settings.ipynb>`_]
+
+The following notebooks covers more advanced topics in Lux: 
+
+- Understanding data types in Lux [`Source <https://github.com/lux-org/lux-binder/blob/master/tutorial/9-datatype.ipynb?>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/tutorial/9-datatype.ipynb?raw=true>`_]
+- Working with datetime columns [`Source <https://github.com/lux-org/lux-binder/blob/master/tutorial/tutorial/5-datetime.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/tutorial/5-datetime.ipynb>`_] 
+- Working with geographic columns [`ReadTheDocs <https://lux-api.readthedocs.io/en/latest/source/advanced/map.html>`_] 
+- Working with dataframe indexes [`Source <https://github.com/lux-org/lux-binder/blob/master/tutorial/tutorial/6-index-group.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/tutorial/6-index-group.ipynb>`_]
+- Registering custom recommendation actions [`Source <https://github.com/lux-org/lux-binder/blob/master/tutorial/8-custom-action.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/tutorial/8-custom-action.ipynb>`_]
+- Using Lux with a SQL Database [`Source <https://github.com/lux-org/lux-binder-sql/blob/master/notebooks/Using%20Lux%20with%20SQL%20Databases.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder-sql/HEAD>`_]
+
+
+Exercise
+---------
+
+Here are some teaching resources on Lux. The materials are suited for a 1-1.5 hour industry bootcamp or lecture for a data visualization or data science course. Here is a `video <https://www.youtube.com/watch?v=YANIids_Nkk>`_ that walks through these hands-on exercise on Lux. To follow along, check out the instructions `here <https://github.com/lux-org/lux-binder>`_.
+
+1. How to specify your analysis interests as `intents` in Lux? [`Source <https://github.com/lux-org/lux-binder/blob/master/exercise/1-Specify-Intent.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/exercise/1-Specify-Intent.ipynb>`_]
+
+2. How to create visualizations using :code:`Vis` and :code:`VisList`? [`Source <https://github.com/lux-org/lux-binder/blob/master/exercise/2-Quick-Vis.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/exercise/2-Quick-Vis.ipynb>`_]
+
+3. How to export selected visualization(s) out of the notebook for sharing? [`Source <https://github.com/lux-org/lux-binder/blob/master/exercise/3-Export-Widget.ipynb>`_] [`Live Notebook <https://mybinder.org/v2/gh/lux-org/lux-binder/master?urlpath=tree/exercise/3-Export-Widget.ipynb>`_]
+
+Here are the `solutions <https://github.com/lux-org/lux-binder/blob/master/exercise/solution.txt>`_ to the notebook exercises.
+
+
+Community Contributions
+-------------------------
+Here are some awesome articles and tutorials written by the Lux community: 
+
+- `Exploring the Penguins dataset with Lux by Parul Pandey <https://towardsdatascience.com/intelligent-visual-data-discovery-with-lux-a-python-library-dc36a5742b2f>`_
+- `Analysis of the Wine dataset by Domino Data Lab <https://blog.dominodatalab.com/faster-data-exploration-in-jupyter-through-the-lux-widget/>`_
+- `Quick Recommendation-Based Data Exploration with Lux by Cornellius Yudha Wijaya <https://towardsdatascience.com/quick-recommendation-based-data-exploration-with-lux-f4d0ccb68133>`_
+- `Analyzing the Graduate Admissions dataset with Lux by Pranavi Duvva <https://pub.towardsai.net/speed-up-eda-with-the-intelligent-lux-37f96542527b>`_
+
+
+If you would like your notebook or articles to be featured here, please submit a pull request `here <https://github.com/lux-org/lux-binder>`_ to let us know!

doc/source/reference/gen/lux.core.frame.LuxDataFrame.rst

@@ -176,6 +176,7 @@
       ~LuxDataFrame.set_intent_as_vis
       ~LuxDataFrame.set_intent_on_click
       ~LuxDataFrame.shift
+      ~LuxDataFrame.show_all_column_vis
       ~LuxDataFrame.skew
       ~LuxDataFrame.slice_shift
       ~LuxDataFrame.sort_index

lux/executor/SQLExecutor.py

@@ -134,12 +134,6 @@ def add_quotes(var_name):
             query = "SELECT {} FROM {} {}".format(required_variables, tbl.table_name, where_clause)
         data = pandas.read_sql(query, lux.config.SQLconnection)
         view._vis_data = utils.pandas_to_lux(data)
-        # view._vis_data.length = list(length_query["length"])[0]
-
-        tbl._message.add_unique(
-            f"Large scatterplots detected: Lux is automatically binning scatterplots to heatmaps.",
-            priority=98,
-        )
 
     @staticmethod
     def execute_aggregate(view: Vis, tbl: LuxSQLTable, isFiltered=True):