add Heroku and reflection

.ipynb_checkpoints/CONTRIBUTING-checkpoint.md

@@ -0,0 +1,2 @@
+We welcome all contributions to this project! If you notice a bug or have a feature request, please [open up an issue](https://github.com/ubco-mds-2020-labs/dashboard-project---r-data551_group9/issues). All contributors must abide by our [Code of Conduct](https://github.com/ubco-mds-2020-labs/dashboard-project-data551_group9/blob/main/code_of_conduct.md).
+

.ipynb_checkpoints/LICENSE-checkpoint

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2021 Haotian Jin, Fengcheng Liu
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

.ipynb_checkpoints/README-checkpoint.md

@@ -0,0 +1,23 @@
+# DATA 551 - Group 9
+
+Group members: Fengcheng Liu, Haotian Jin
+
+Dataset: [analysis.csv](https://github.com/ubco-mds-2020-labs/dashboard-project-data551_group9/blob/main/data/raw/analysis.csv)
+
+Dashboard address: [hr-marketing-analytics](https://hr-marketing-analytics.herokuapp.com/)
+
+## Welcome!
+----
+
+Hello and welcome to our Dashboard project. Our role is data scientists who focus on HR consulting and target audience are company's Marketing Department, HR & Job Seekers who are seek for data scientist jobs. Nowadays companies are paying more and more attention to hiring. A good hiring strategy can significantly help reducing the cost on training and also have a return of a more appropriate selection among the candidates. Big Data is one of the most popular method that are used for hiring. One general method is that these companies will conduct some training courses to the candidates and hiring by combining the test result with the candidates’ basic information. Many people signup for their training. In our case, our company wants to know which of these candidates has higher probability passing the test then get the data scientist position after. This will help to reduce the cost and time as well as to increase quality of training or planning the courses and categorization of candidates. Information related to demographics, education, experience are in hands from candidates signup and enrollment. From the company decision maker perspective, they would also like to know the distribution of the candidates (relationship between features of candidates) so that they can make future predictions that may be helpful in hiring suitable employees.
+
+## Looking for improvement!
+---
+
+We are always looking for feedbacks and contributions!
+
+You can run the app locally and contribute by:
+
+- Fork this repo
+- Adding your improvements to the app.R file in the root folder
+- Run Rscript app.R in terminal/command line

.ipynb_checkpoints/Untitled-checkpoint.ipynb

@@ -2,5 +2,5 @@
  "cells": [],
  "metadata": {},
  "nbformat": 4,
- "nbformat_minor": 4
+ "nbformat_minor": 5
 }

.ipynb_checkpoints/Untitled1-checkpoint.ipynb

@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}