Implementation of ARIMA model (Auto Regressive Integrated Moving Average)
Project description
Raptor ARIMA Model Python API
- This API Supports to model time series data using box-jenkins model.
Python Installation:
- Command for installation: 'pip3 install raptorarima'
Usage
The ARIMA Model is an implementation from scratch which using MA, AR and differencing to model the Data.
Define the p,d,q parameters.
q = 1
d = 0
p = 3
m = ARIMA(q, d, p)
pred = m.fit_predict(x)
Installation
git clone https://github.com/swaroop9ai9/Fintech/raptor_arima_api.git
cd raptor arima
python setup.py install
Requirements
- pandas
- numpy
- random
Note
Make sure to use Time series Data Values.
Steps to create pip package
- Prepare directory with setup.py, packagename(apiname(init.py[with main code]),other py files which supports the init.py file.)
- Upload the package to Git
- cd packagename
- chmod +x apiname #makes it an executable
- python3 setup.py bdist_wheel [
- build: build package information.
- dist: Contains your .whl file. A WHL file is a package saved in the Wheel format, which is the standard built-package format used for Python distributions. You can directly install a .whl file using pip install some_package.whl on your system
- project.egg.info: An egg package contains compiled bytecode, package information, dependency links, and captures the info used by the setup.py test command when running tests.]
-
[Optional] to check install on local machine python -m pip install dist/packagename-0.1-py3-none-any.whl
-
python3 -m twine upload dist/* [in order to upload the package] (Will ask your username and password in pypi)
-
Login to pypi account to view the uploaded package
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