[WIP] Documentation & Notebook updates

README.md

@@ -42,7 +42,10 @@ The original version (0.2) of cuxfilter, most known for the backend powering the
 
 ## Usage
 
-### Example 1
+### Example 1 
+[![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/auto_accidents_example.ipynb) [<img src="https://img.shields.io/badge/-Setup Studio Lab Environment-gray.svg">](./notebooks/README.md#amazon-sagemaker-studio-lab)
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/auto_accidents_example.ipynb) [<img src="https://img.shields.io/badge/-Setup Colab Environment-gray.svg">](./notebooks/README.md#google-colab)
 
 ```python
 import cuxfilter
@@ -69,16 +72,19 @@ chart4 = cuxfilter.charts.bar('MONTH')
 #declare dashboard
 d = cux_df.dashboard([chart1, chart3, chart4], sidebar=[chart2], layout=cuxfilter.layouts.feature_and_double_base, title='Auto Accident Dataset')
 
-# run the dashboard within the notebook cell
-# d.app()
-
 #run the dashboard as a webapp:
-d.show('jupyter-notebook/lab-url')
+# d.show('jupyter-notebook/lab-url')
+
+#run the dashboard within the notebook cell
+d.app()
+
 ```
 ![output dashboard](./docs/_images/demo.gif)
 
-### Example 2
-
+### Example 2 
+[![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/Mortgage_example.ipynb) [<img src="https://img.shields.io/badge/-Setup Studio Lab Environment-gray.svg">](./notebooks/README.md#amazon-sagemaker-studio-lab)
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/Mortgage_example.ipynb) [<img src="https://img.shields.io/badge/-Setup Colab Environment-gray.svg">](./notebooks/README.md#google-colab)
 
 ```python
 import cuxfilter
@@ -104,11 +110,12 @@ chart1 = cuxfilter.charts.drop_down('dti')
 #declare dashboard
 d = cux_df.dashboard([chart0, chart2],sidebar=[chart3, chart1], layout=cuxfilter.layouts.feature_and_double_base,theme = cuxfilter.themes.light, title='Mortgage Dashboard')
 
-# run the dashboard within the notebook cell
+#run the dashboard within the notebook cell
 # d.app()
 
 #run the dashboard as a webapp:
 d.show('jupyter-notebook/lab-url')
+
 ```
 ![output dashboard](./docs/_images/demo2.gif)
 
@@ -152,25 +159,17 @@ cuxfilter can be installed with conda ([miniconda](https://conda.io/miniconda.ht
 
 For `cuxfilter version == 22.02` :
 ```bash
-# for CUDA 10.1
+# for CUDA 11.5
 conda install -c rapidsai -c nvidia -c numba -c conda-forge \
-    cuxfilter=22.02 python=3.7 cudatoolkit=10.1
-
-# or, for CUDA 10.2
-conda install -c rapidsai -c nvidia -c numba -c conda-forge \
-    cuxfilter=22.02 python=3.7 cudatoolkit=10.2
+    cuxfilter=22.02 python=3.7 cudatoolkit=11.5
 
 ```
 
 For the nightly version of `cuxfilter` :
 ```bash
-# for CUDA 10.1
-conda install -c rapidsai-nightly -c nvidia -c numba -c conda-forge \
-    cuxfilter python=3.7 cudatoolkit=10.1
-
-# or, for CUDA 10.2
+# for CUDA 11.5
 conda install -c rapidsai-nightly -c nvidia -c numba -c conda-forge \
-    cuxfilter python=3.7 cudatoolkit=10.2
+    cuxfilter python=3.7 cudatoolkit=11.5
 ```
 
 Note: cuxfilter is supported only on Linux, and with Python versions 3.7 and later.
@@ -214,6 +213,8 @@ The notebooks inside `python/notebooks` already have a check function which veri
 
 While in the directory you want the datasets to be saved, execute the following
 
+> Note: Auto Accidents dataset has corrupted coordinate data from the years 2012-2014
+
 ```bash
 #go the the environment where cuxfilter is installed. Skip if in a docker container
 source activate test_env
@@ -239,7 +240,6 @@ Currently supported layout templates and example code can be found on the [layou
 | custom    | view_dataframe |
 | pydeck    | choropleth(3d and 2d)   |
 
-
 ## Contributing Developers Guide
 
 cuxfilter acts like a connector library and it is easy to add support for new libraries. The `python/cuxfilter/charts/core` directory has all the core chart classes which can be inherited and used to implement a few (viz related) functions and support dashboarding in cuxfilter directly.

notebooks/README.md

@@ -1,10 +1,78 @@
 # Example notebooks
 
-These are example notebooks to showcase cuxfilter. Related Datasets can be download using the link below:
+These are example notebooks to showcase cuxfilter.
 
-- Download the mortgage dataset from [here](https://docs.rapids.ai/datasets/mortgage-viz-data)
+## TRY CUXFILTER NOTEBOOKS ONLINE
 
-- Nyc taxi dataset from [here](https://drive.google.com/file/d/1mTvl66VLzHwQJPcgnGBdmZTNEdNp1tYo/view?usp=sharing)
+[<img src="https://img.shields.io/badge/-Setup Studio Lab Environment-gray.svg">](#amazon-sagemaker-studio-lab) [<img src="https://img.shields.io/badge/-Setup Colab Environment-gray.svg">](#google-colab)
 
+1. Mortgage_example.ipynb
 
-- Auto dataset from [here](https://drive.google.com/file/d/1jxySYJ9e32hI8PQ5QPr9_xrsu37N5fOM/view?usp=sharing)
+    [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/Mortgage_example.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/Mortgage_example.ipynb) 
+
+2. NYC_taxi_example.ipynb
+
+    [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/NYC_taxi_example.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/NYC_taxi_example.ipynb)
+
+3. auto_accidents_example.ipynb
+
+    [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/auto_accidents_example.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/auto_accidents_example.ipynb)
+
+4. graphs.ipynb
+
+    [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/graphs.ipynb) 
+    [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/rapidsai/cuxfilter/blob/branch-22.02/notebooks/graphs.ipynb)
+</br>
+
+
+## Setup Remote Environments
+### Amazon Sagemaker Studio Lab
+
+[Amazon SageMaker Studio Lab](https://studiolab.sagemaker.aws/faq) is a free ML development environment that provides the compute, storage (up to 15GB), and security —all at no cost (currently). This includes GPU notebook instances.
+
+Once you have registered with your email address, simply sign in to your account, start a CPU or GPU runtime, and open your project - all in your browser.
+
+To setup a rapids environment in studio lab(you only need to do this the first time, since studio lab has 15GB of persistent storage across sessions), open a new terminal:
+
+```bash
+conda install ipykernel
+
+# for stable rapids version
+conda install -c rapidsai -c nvidia -c numba -c conda-forge \
+    cuxfilter=22.02 python=3.7 cudatoolkit=11.5
+
+# for nightly rapids version
+conda install -c rapidsai-nightly -c nvidia -c numba -c conda-forge \
+    cuxfilter python=3.7 cudatoolkit=11.5
+```
+> Above are sample install snippets for cuxfilter, see the [Get RAPIDS version picker](https://rapids.ai/start.html) for installing the latest `cuxfilter` version.
+
+Once installed, you should see a card in the launcher for that environment and kernel after about a minute.
+
+<div class="alert alert-info"> <b>Note:</b> It may take about one minute for the new environment to appear as a kernel option.</div>
+
+
+### Google Colab
+
+[Google Colab](https://colab.research.google.com/?utm_source=scs-index), or "Colaboratory", allows you to write and execute Python in your browser, with 
+- Zero configuration required
+- Free access to GPUs
+- Easy sharing
+
+To launch cuxfilter notebooks on the colab environment, you need to follow the the RAPIDS installation instructions guide by clicking [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1rY7Ln6rEE1pOlfSHCYOVaqt8OvDO35J0#forceEdit=true&offline=true&sandboxMode=true). Once the RAPIDS libraries are installed, you can run the cuxfilter notebooks.
+
+> Note: Unlike Studio Lab, environment storage is not persistent and each notebook needs a separate RAPIDS installation every time you start a new session.
+
+> Copy the installation notebook cells to the top of the cuxfilter notebooks and install RAPIDS before executing the cuxfilter code.
+
+
+</br>
+
+## Download Datasets
+- [Mortgage dataset](https://docs.rapids.ai/datasets/mortgage-viz-data)
+
+- [Nyc taxi dataset](https://drive.google.com/file/d/1mTvl66VLzHwQJPcgnGBdmZTNEdNp1tYo/view?usp=sharing)
+
+- [Auto Accidents dataset](https://drive.google.com/file/d/1jxySYJ9e32hI8PQ5QPr9_xrsu37N5fOM/view?usp=sharing)
+
+> Note: Auto Accidents dataset has corrupted coordinate data from the years 2012-2014