Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/bryancastillo10/co2-emissions-analysis
https://github.com/bryancastillo10/co2-emissions-analysis
Last synced: about 2 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/bryancastillo10/co2-emissions-analysis
- Owner: bryancastillo10
- Created: 2024-04-04T16:11:15.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-04-12T14:17:06.000Z (9 months ago)
- Last Synced: 2024-04-13T20:51:13.423Z (9 months ago)
- Language: Jupyter Notebook
- Size: 7.49 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
Awesome Lists containing this project
README
Global CO2 Emission Project
**Technologies Used**
Data Cleaning and Exploratory Data Analysis
Data Visualization and Metrics Calculation
Introduction
Climate change had become a major environmental concern over time as environmental scientists
observed anomalous behavioral patterns throughout the environment. One of those factor they suspect as a probable cause is the accumulation of carbon dioxide in the atmosphere. CO₂ is described to have high longevity in the atmosphere because of its chemical properties which blankets the Earth's emitted infrared
radiation. Without further discussing about the chemistry of CO₂, this project presents a dataset collected
throughout time (1750 up to 2021) on different parts of the world (232 countries). As a data analyst, we
are to investigate the following objectives:
- What is the trend of CO₂ emissions in the world over time?
- In these observed trends on emission, can it be related to the demographics?
- Which country contributes the most emissions?
- What is the major chemical constituent of CO₂ gases in the atmosphere?
- What are the major sources of these emissions?
Data Manipulation by Pandas Library
The dataset was recovered from the Maven Analytics public dataset, and initially it
is composed of around 50,000 rows by 79 columns. With this structure of the dataset,it requires some data cleaning procedure and dimensional reduction. This step is shown in details on the Jupyter notebook of this repository.
Power BI Dashboard
Data visualization was performed utilizing Microsoft Power BI
**Dashboard Interpretation**
Based on the created dashboard, there is a significant increase of CO2 over time and it was further boosted by the man-made/anthropogenic activities (energy consumption being the primary man-made source). This calls for an environmental advocacy to contribute in achieving sustainable development goal pledge by the UN of net zero carbon emission by the year 2050.