creat requirements file

.history/README_20250329004717.md

+## TOAR-classifier v2: A data-driven classification tool for global air quality stations
+This study develops a machine learning approach to classify 23,974 air quality monitoring stations in the TOAR database as urban, suburban, or rural using K-means clustering and an ensemble of supervised classifiers. The proposed method outperforms existing classifications, improving suburban accuracy and providing a more reliable foundation for air quality assessments.
+<img src="./figures/toar_classifier_v2.png" alt="My image" with=100>
+
+### Files
+- `data` is the folder containing all the data used in this work, including the predictions of station categories from the Machine Learning (ML) model.
+- `figures` contains all the figures.
+- `TOAR-classifier_v2.ipynb` is the notebook containing the code.
+- `requirements.txt` contains all the necessary packages.
+
+### Run the Code
+
+**Note:** This has been tested on Ubuntu 24.04.
+
+1. Install Python 3 if not already installed (most Linux systems have Python pre-installed).
+2. Install Jupyter Notebook:
+   - `pip install notebook` (for Jupyter Notebook) or
+   - `pip install jupyterlab` (for JupyterLab).
+
+3. clone the project by running the following
+   - `git clone https://gitlab.jsc.fz-juelich.de/esde/toar-public/ml_toar_station_classification.git`
+
+change directory to ml_toar_station_classification
+-  `cd ml_toar_station_classification`
+
+creat virtual environment 
+- `python -m venv TOAR-classifier_v2` # feel free to change the virtual environment as convenient 
+
+activate the created venv 
+- `python -m ipykernel install --user --name=TOAR-classifier_v2 --display-name "Python (TOAR-classifier_v2)"`
+
+#### Install required package
+open jupyter notebook, `jupyter-notebook` and select kernel `TOAR-classifier_v2`
+
+Install all the required packages for the project by uncommenting the first cell in the notebook and running the cell
+
+Run the code cell by cell.
+

README.md

@@ -18,13 +18,16 @@ This study develops a machine learning approach to classify 23,974 air quality m
    - `pip install jupyterlab` (for JupyterLab).
 
 3. clone the project by running the following
-`git clone https://gitlab.jsc.fz-juelich.de/esde/toar-public/ml_toar_station_classification.git`
+   - `git clone https://gitlab.jsc.fz-juelich.de/esde/toar-public/ml_toar_station_classification.git`
 
-change directory to ml_toar_station_classification, `cd ml_toar_station_classification`
+change directory to ml_toar_station_classification
+-  `cd ml_toar_station_classification`
 
-creat virtual environment `python -m venv TOAR-classifier_v2` # feel free to change the virtual environment as convenient 
+creat virtual environment 
+- `python -m venv TOAR-classifier_v2` # feel free to change the virtual environment as convenient 
 
-activate the created venv `python -m ipykernel install --user --name=TOAR-classifier_v2 --display-name "Python (TOAR-classifier_v2)"`
+activate the created venv 
+- `python -m ipykernel install --user --name=TOAR-classifier_v2 --display-name "Python (TOAR-classifier_v2)"`
 
 #### Install required package
 open jupyter notebook, `jupyter-notebook` and select kernel `TOAR-classifier_v2`