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# Time series autocorrelation tool | |
Tool demonstrating time series autocorrelation analysis with Python | |
Assumes uploaded data is clean. | |
## Built With | |
- [Streamlit](https://streamlit.io/) | |
## Local setup | |
### Obtain the repo locally and open its root folder | |
#### To potentially contribute | |
```shell | |
git clone https://github.com/pkiage/tool-time-series-autocorrelation-demo | |
``` | |
or | |
```shell | |
gh repo clone pkiage/tool-time-series-autocorrelation-demo | |
``` | |
#### Just to deploy locally | |
Download ZIP | |
### (optional) Setup virtual environment: | |
```shell | |
python -m venv venv | |
``` | |
### (optional) Activate virtual environment: | |
#### If using Unix based OS run the following in terminal: | |
```shell | |
.\venv\bin\activate | |
``` | |
#### If using Windows run the following in terminal: | |
```shell | |
.\venv\Scripts\activate | |
``` | |
### Install requirements by running the following in terminal: | |
#### Required packages | |
```shell | |
pip install -r requirements.txt | |
``` | |
## Build and install local package | |
```shell | |
python setup.py build | |
``` | |
```shell | |
python setup.py install | |
``` | |
### Run the streamlit app (app.py) by running the following in terminal (from repository root folder): | |
```shell | |
streamlit run src/app.py | |
``` | |
<p><small>Project structure based on the <a target="_blank" href="https://drivendata.github.io/cookiecutter-data-science/">cookiecutter data science project template</a>.</small></p> | |