The objective of this topic is to predict the third-semester pointers on the basis of the first and second-semester pointers' values. And to create a method that can predict the near future data (one or two values) to its possible amount of accuracy by using the minimal amount of data.
The python modules/libraries required to run this code on Windows Machine:
$ pip install xlrd
$ pip install collections
$ pip install plotly
Or Install Plotly in Virtual Environment by the following instructions
Create your virtualenv
$ mkdir ~/.virtualenvs
$ cd ~/.virtualenvs
$ python -m venv plotly3.3
Activate the virtualenv
$ source ~/.virtualenvs/plotly2.7/bin/activate
(plotly2.7) $
Install plotly locally to virtualenv
(plotly2.7) $ pip install plotly==3.3
Deactivate to exit
(plotly2.7) $ deactivate
$
$ git clone https://github.com/Dhyeythumar/Data-prediction-and-plotting.git
$ cd data_prediction&plotting
$ python data_prediction.py
The project is running 😃
To create a build file you need to install cx_Freeze.
Install cx_Freeze
$ pip install cx_Freeze
Create build file
$ cd data_prediction&plotting
$ python setup.py build
Successfully created a build file 📦
This project is licensed under the GNU GPLv3 - see the LICENSE file for details.
- To see the More Details on project.