Air Quality Analysis: Aotizhongxin Station🌍

Live Dashboard

Explore the live dashboard here : Air Quality Dashboard

Libraries Used

• Pandas
• Matplotlib
• Seaborn
• Streamlit
• Numpy
• Plotly

Data Source

The air quality data used in this project was obtained from the Aotizhongxin Station. The dataset contains measurements of various air pollutant with a focus on PM2.5. The goal is to identify patterns, seasonal fluctuations, and how various weather conditions affect the air quality.

Key Insight

• The analysis reveals a clear seasonal pattern in pollutant levels with PM2.5 concentrations peaking during winter months
• Impact of wind speed, rainfall's role, and wind direction on air quality
• Correlation between PM2.5 levels and weather conditions

How to Run the Dashboard

1. Create and Activate a Python Environtment:

• Using Conda : Conda

  conda create --name airquality-ds python=3.9
  conda activate airquality-ds

• Using venv :

  python -m airquality-ds
  #Mac/Linux users
  source airquality-ds/bin/activate
  #Windows users
  airquality-ds\Scripts\activate

2. Install Requirements Packages:

• Install the following packages for running the analysis and dashboard:

  pip install pandas matplotlib seaborn streamlit numpy plotly

• or install the requirements.txt:

  pip install -r requirements.txt

Run the Streamlit App

• After installing the dependencies, run the Streamlit app with:

  streamlit run dashboard.py

Additional Files

A detailed Python notebook Air_Quality_Analysis_Jessica.ipnyb contains data analysis and visualization.