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