Merge pull request #159 from jahn96/press-release

Press release & Version update

Author: jahn96

PRESS_RELEASE.md

@@ -0,0 +1,15 @@
+# Jupyter Bifrost: Interactive Data Visualization in JupyterLab
+
+## Intuitively explore data without repetitive code.
+
+Data exploration just got a whole lot easier, with Jupyter Bifrost. In this JupyterLab extension, users can use its interactive visualization interface to rapidly analyze complex datasets. Bifrost connects visualizations with Pandas dataframes, creating a dynamic bridge between the two.
+
+Without interactive visualizations, exploring datasets through code is sometimes slow and tedious. It can be difficult to know which columns in a dataset will yield useful information, or what kind of chart will best visualize the data. To follow up on a new question or insight, users have to tediously write and rewrite data transformations in code, distracting from the natural flow of exploration. Current interactive visualization applications aren’t well-integrated into the notebook environment, distancing them from the code and making it difficult to reproduce results.
+
+By contrast, users can easily make edits with Bifrost, letting them focus on extracting insights instead of coding repetitively. The extension is launched as a cell output, smoothly integrating it into the notebook. To help begin data analysis, Bifrost recommends charts based on user-specified columns from their dataset. This allows users to go from a thousand-column dataset to a useful visualization in a matter of seconds. It is also easy to filter and edit a visualization to narrow in on useful insights. After making edits, users can extract an updated pandas dataframe, exporting their insights back to code. All interactions are preserved in a history log, enabling iteration on previous versions of a visualization.
+
+> _“Jupyter Bifrost is a great way to jump into data exploration without writing a ton of code. While it's perfect for students and novices, we’ve also seen it speed up the workflows of seasoned developers. It’s so much easier to find compelling correlations and get into the flow of analysis.” —<b>Jupyter Developer<b>_
+
+To get started, import the Bifrost library and plot any Pandas dataframe to begin interacting with it. Our extension will translate all of your explorations in the graphic interface into Pandas data queries, allowing you to track and reproduce your experiments with large datasets. You can also apply the results of your analysis to the original Pandas DataFrame so that you can pick up where you left off in the code.
+
+Rewrite less code, explore more data. Download Jupyter Bifrost today!

jupyter_bifrost/_frontend.py

@@ -9,4 +9,4 @@
 """
 
 module_name = "jupyter_bifrost"
-module_version = "^0.2.2"
+module_version = "^0.3.0"

jupyter_bifrost/_version.py

@@ -4,5 +4,5 @@
 # Copyright (c) John Waidhofer(waidhoferj), Jay Ahn(jahn96).
 # Distributed under the terms of the Modified BSD License.
 
-version_info = (0, 2, 2)
+version_info = (0, 3, 0)
 __version__ = ".".join(map(str, version_info))

package.json

@@ -1,6 +1,6 @@
 {
   "name": "jupyter_bifrost",
-  "version": "0.2.2",
+  "version": "0.3.0",
   "description": "A Jupyter Widget for Interactive Data Visualization",
   "keywords": [
     "jupyter",