ML based forecasting
Project description
Forecasting
Install
First, clone the repo like and cd to its root path, like so:
git clone git@github.com:JaumeAmoresDS/forecasting.git
cd forecasting
Then install dependencies using one of the following options:
Option 1: installing from forecasting.yml file
conda env create -n forecasting --file forecasting.yml
conda activate forecasting
Option 2: installing from requirements file
conda create -n forecasting python=3.10 pip
conda activate forecasting
pip install requirements.txt
Option 3: installing from setup.py
conda create -n forecasting python=3.10 pip
conda activate forecasting
pip install -e .[dev]
How to use
Run:
python scripts/run_pipeline.py
This will save the predictions into a file called predictions.parquet
.
To display it, you can do something like:
import pandas as pd
predictions = pd.read_parquet ('predictions.parquet')
predictions.plot ();
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
tsforecast-0.0.1.tar.gz
(22.2 kB
view hashes)
Built Distribution
tsforecast-0.0.1-py3-none-any.whl
(23.9 kB
view hashes)
Close
Hashes for tsforecast-0.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f6ae8fc0993383834e045d18e77959b16956b0be77069fe0d4632a62e7fce008 |
|
MD5 | 42e33d9c21413267ae442a528ff1a067 |
|
BLAKE2b-256 | 52b5357b997474f0e88eff113d2a72c17327aacc0e6d068508a8a3ce9ed092d2 |