An exploratory data analysis and data visualization project on Air quality dataset.
Jupyter Notebook
Air-Quality-Dataset-Analysis-EDA
Challenge of the Month
In this project , I have done an in-depth analysis and visualization on the air quality dataset.The goal is to find the patterns and relationships in the dataset.
Summary of extracted patterns and relationships within the datset
Dependencies:
Matplotlib
Plotly
Seaborn
Requirements
Python 2.7 or Python 3.6
Jupyter Notebook
About the dataset
The dataset contains 9358 instances of hourly averaged responses from an array of 5 metal oxide chemical sensors embedded in an Air Quality Chemical Multisensor Device.
The device was located on the field in a significantly polluted area, at road level,within an Italian city. Data were recorded from March 2004 to February 2005 (one year)representing the longest freely available recordings of on field deployed air quality chemical sensor devices responses. Ground Truth hourly averaged concentrations for CO, Non Metanic Hydrocarbons,Benzene, Total Nitrogen Oxides (NOx) and Nitrogen Dioxide (NO2) and were provided by a co-located reference certified analyzer.