The purpose of this project was to create a set of interactive webpages displaying visualizations an alysis of Maximum Temperature, Humidity, Cloudiness, and Wind Speed versus Latitude.
Pandas was used to read a CSV file of data and convert it to HTML code.
Bootstrap was used to create a navigation bar and the grid used to format the webpages.
A menu using images was created to offer an additional option of navigation between pages.
As expected, the weather becomes significantly warmer as one approaches the equator (0 Deg. Latitude).
More interestingly, however, is the fact that the southern hemisphere tends to be warmer this time of year than the northern hemisphere. This may be due to the tilt of the earth at the time of the year this data was gathered.
From this plot, we can see that most locations from which we collected data experience humidity levels between 60-100%. There is, however, no clear connection between latitude and humidity. One may be expect other factors to affect the humidity, such as proximity to bodies of water.
Based on this plot, there is no conclusive correlation between latitude and cloudiness. However, cloudiness does appear to follow a pattern of similar cloud percentage across all latitudes.
Based on this plot, there is no conclusive correlation between latitude and cloudiness. However, cloudiness does appear to follow a pattern of similar cloud percentage across all latitudes.