In this project, the goal is to analyze local and global temperature data and compare the temperature trends where I live to overall global temperature trends.
| Table of Contents |
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| Prerequisites 🔍📜 |
| Design 📐 |
| License 🔖 |
| Conclusions 📌 |
- DB Browser for SQLite
- Excel
(Image is from Udacity.)
In order to create a visualization and prepare a write up describing the similarities and differences between global temperature trends and temperature trends in the closest big city to where I live, following steps were carried out.
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Extract the data: write SQL queries to extract the city level data, global data as well as city_list from database attached to workspace in Udacity course, followed by exporting them to CSV;
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Open up the CSV: using Excel to handle the files;
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Create a line chart: compares my city’s temperatures with the global temperatures. In addition, ploting the moving average rather than the yearly averages in order to smooth out the lines, making trends more observable;
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Make observations: the similarities and differences between the world averages and my city’s averages, as well as overall trends, etc.
In sum, Kingston is cooler when compared with global temperature over the past 250 years, such difference was constant with time. It makes sense as Kingston's coordinators located in the north part of the hemisphere, thus it belongs to frigid region.
