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https://github.com/canayter/wine_and_climate_change
Utilized Pandas for data cleaning and integration to create a high-quality, uniform dataset of global wine production and historical temperature records. Employed SciPy for statistical analysis to ensure data integrity and accuracy. Generated visualizations using Matplotlib and Seaborn to effectively communicate findings.
https://github.com/canayter/wine_and_climate_change
matplotlib pandas python scipy seaborn
Last synced: about 1 month ago
JSON representation
Utilized Pandas for data cleaning and integration to create a high-quality, uniform dataset of global wine production and historical temperature records. Employed SciPy for statistical analysis to ensure data integrity and accuracy. Generated visualizations using Matplotlib and Seaborn to effectively communicate findings.
- Host: GitHub
- URL: https://github.com/canayter/wine_and_climate_change
- Owner: canayter
- Fork: true (AEKoller/wine_and_climate_change)
- Created: 2024-05-09T00:31:05.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-08-31T03:35:26.000Z (3 months ago)
- Last Synced: 2024-09-26T16:24:06.871Z (about 2 months ago)
- Topics: matplotlib, pandas, python, scipy, seaborn
- Language: Jupyter Notebook
- Homepage:
- Size: 10.3 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0