Solar Panel Efficiency Management Model Kit
by sarthakkiran 
Updated: Jan 9, 2022
Solution Kit
Team Name: VIT/OW/55 "The future is green energy, sustainability, renewable energy. Once you got a solar panel on a roof, energy is free. Once we convert our entire electricity grid to green and renewable energy, the cost of living goes down." Welcome to our Sustainable Energy Management Hackathon kit. Check out our video Report!! https://drive.google.com/file/d/1me1sje1o5Lrm8SkKQpQy9Sx5j_2Itowi/view?usp=sharing
Exploratory Data Analysis in Python
These libraries are used for statistical, Univariate, descriptive, and exploratory analysis.
matplotlibby matplotlib
17088 Version:v3.7.1
License: No License (null)matplotlib: plotting with Python
matplotlibby matplotlib
Python 17088 Version:v3.7.1 License: No License
seabornby mwaskom
10513 Version:v0.12.2Statistical data visualization in Python
seabornby mwaskom
Python 10513 Version:v0.12.2 License: Permissive (BSD-3-Clause)
pandasby pandas-dev
37428 Version:v2.0.0rc1Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pandasby pandas-dev
Python 37428 Version:v2.0.0rc1 License: Permissive (BSD-3-Clause)
numpyby numpy
23036 Version:v1.24.2The fundamental package for scientific computing with Python.
numpyby numpy
Python 23036 Version:v1.24.2 License: Permissive (BSD-3-Clause)
Machine Learning Libraries for Prescriptive Analysis
These libraries are used for developing the machine learning pipeline model .
scikit-learnby scikit-learn
53544 Version:1.2.2scikit-learn: machine learning in Python
scikit-learnby scikit-learn
Python 53544 Version:1.2.2 License: Permissive (BSD-3-Clause)
pycaretby pycaret
7086 Version:3.0.0An open-source, low-code machine learning library in Python
pycaretby pycaret
Jupyter Notebook 7086 Version:3.0.0 License: Permissive (MIT)
auto-sklearnby automl
6802 Version:v0.15.0Automated Machine Learning with scikit-learn
auto-sklearnby automl
Python 6802 Version:v0.15.0 License: Permissive (BSD-3-Clause)
Annotation & Labelling libraries
These are used for data visualization, data Labelling, data annotation.
tortusby SiphuLangeni
11 Version:v1.0.2A PyPI package for easy text annotation in a Jupyter Notebook.
tortusby SiphuLangeni
Python 11 Version:v1.0.2 License: Strong Copyleft (GPL-3.0)
label-studioby heartexlabs
12415 Version:1.7.2Label Studio is a multi-type data labeling and annotation tool with standardized output format
label-studioby heartexlabs
Python 12415 Version:1.7.2 License: Permissive (Apache-2.0)
labelboxby Labelbox
1708 Version:CurrentLabelbox is the fastest way to annotate data to build and ship computer vision applications.
labelboxby Labelbox
JavaScript 1708 Version:Current License: Permissive (Apache-2.0)
Deployment Information
This section has the instructions to install the kit. For theSarthak & Ashutosh kit source, the deployment instructions are: 1. Clone our github repository from the source: https://github.com/Sarthak1807/Sustainable-Energy-Hackathon 2. Download and save all your files. 3. For the Prescriptive and Exploratory data analysis, Navigate to the 'energy hack.ipynb' and open and run each cell. 4. For the Statistical and Descriptive, time Series analysis , Navigate to the 'energy hack.ipynb' and open and run each cell. 5. For the Data Labelling and Annotation, Navigate to the 'tortus_labelling.ipynb' and open and run each cell. 6. Install the required libraries by 'pip install -r requirements.txt' 7. Read out report.