Requirements; Python 3.9
- Have conda or miniconda installed
git cloneor download the repository- In the project directory in terminal:
$ conda env create -f environment.yaml
$ conda activate sim-proj
$ pip install simpy- Optional: Setup use of Jupyter Notebook (pass these commands in order, in terminal)
$ pip install --user ipykernel
$ python -m ipykernel install --user --name=sim-proj
# check that the kernel is installed,
# sim-proj should be listed after this command
$ jupyter kernelspec list.
├── README.md
├── arena
│ ├── ARENA-output.pdf
│ └── Attrition-Model-v-2021-30-11.doe
├── data # hidden file directory, download data from kaggle
│ └── raw
│ └── WA_Fn-UseC_-HR-Employee-Attrition.csv
├── environment.yaml # file to create virtual conda environment
├── notebooks
│ ├── IBM-Data-EDA-for-SIM.ipynb # statistical analysis, EDA, plots
│ └── LogReg.ipynb # work & results for logistic regression
├── reports
│ ├── figures # plots generated
│ └── README.md # data dictionary
└── src
├── config.py # global variables
├── dectree.py # decision tree code
├── helper.py # data preprocessing & prep
└── logreg.py # logisitc regression binary classifierData Source: https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-attrition-dataset