Data science, Data manipulation and Machine learning library. Use permitted according to the terms of use and conditions set by the attached license.
Installation
# using pip.
pip install vandalDependencies
# using pip.
pip install vandal -r requirements.txtvandal provides an option of being run within any terminal as a data science/machine learning application in the form of a GUI.
# terminal app entry choices for GUI apps.
python -m vandal -e montecarlogui / python -m vandal --entry montecarloguivandal provides an option of being run within any terminal as a data science/machine learning application.
Terminal options
# terminal app options help.
python -m vandal -h / python -m vandal --help# terminal app entry choices.
python -m vandal -e / python -m vandal --entry# terminal app entry example.
python -m vandal -e montecarlo / python -m vandal --entry montecarloExample use
GUI USE #1
Example use
TERMINAL USE #1
TERMINAL USE #2
EXAMPLE GRAPH
EXAMPLE OUTPUT
vandal functions as a library that can be run in python/jupyter environment and also integrated in other libraries and projects.
Import
# import the library.
import vandalHelp
# library help.
print(help(vandal))# module/object help.
print(help(vandal.MonteCarlo))Meta data
# meta data (individual).
print(vandal.__version__)# all meta data.
print(help(vandal.misc._meta))Library location
# file location after installation.
print(help(vandal.__file__))For whom is vandal made for?
vandal is a Python library for Data science and Machine learning, designed to aid researchers and engineers to meet their goals with small effort.
Why vandal?
As a vandal gives abandoned walls meaning with graffiti, so does vandal library to the data.
A word from the author!
The library itself, its maintenance, updates and stability, logo, videos, promotional materials and everything associated with duality are done by David Kundih from Croatia.
