Project Description
Environmental impact and sustainability analysis is critical to promoting environmentally friendly and sustainable business practices. In this project, we will evaluate environmental impacts and sustainability performance by analyzing energy consumption, emissions, waste management and water use data. Our goal is to help companies and organizations reduce their environmental impact and achieve their sustainability goals.
Project Usage Areas
This project has several uses for environmental engineers, sustainability analysts and data scientists:
Energy Management: Increasing energy efficiency and saving energy by analyzing energy consumption data.
Emission Control: Reducing carbon footprint and controlling emissions by analyzing emission data.
Waste Management: Reducing waste and increasing recycling by analyzing waste management data.
Water Usage: Saving water and optimizing water consumption by analyzing water usage data.
Strategic Decisions: Developing environmental strategies and achieving sustainability goals using data analysis.
Dataset Description
The data set to be used in this project includes the data required to evaluate environmental impact and sustainability performance. The dataset consists of four main files in total:
Energy Consumption Data (energy_consumption_data)
RecordID: Record ID
FacilityID: Facility ID
Date: Date
EnergyConsumed: Amount of energy consumed (kWh)
Emission Data (emission_data)
RecordID: Record ID
FacilityID: Facility ID
Date: Date
CO2Emissions: CO2 emissions (metric tons)
Waste Management Data (waste_management_data)
RecordID: Record ID
FacilityID: Facility ID
Date: Date
WasteGenerated: Amount of waste produced (metric tons)
WasteRecycled: Amount of waste recycled (metric tons)
Water Usage Data (water_usage_data)
RecordID: Record ID
FacilityID: Facility ID
Date: Date
WaterConsumed: Amount of water consumed (cubic meters)
There are various dirty data problems in this dataset, such as missing data, outlier data, and wrong data type. This is an ideal data set to experience data cleaning and processing processes commonly encountered in real life.
Student Benefits
This project provides many benefits for students:
Data Manipulation: Students develop skills in examining, cleaning, and analyzing data sets.
Using Pandas: They learn to use the data processing and analysis methods of the Pandas library effectively.
Data Cleaning: They gain skills in cleaning missing data, outliers and incorrect data types.
Business Intelligence: By analyzing data sets, they improve their ability to evaluate environmental impacts and sustainability performance and make strategic decisions.
Reporting: Provides skills to effectively report and present analysis results.
Real Life Applications: Provides practical information about data problems and analysis processes encountered in real life.
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