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Unit 6 | Assignment: WeatherPy- Observable Trends

Temperature (F) vs. Latitude Observation #1

Equator

As you move from left to right on this graph it is obivous that the data is normalized. There just happen to not be as many samples from below -50 degrees in the displayed data pull. This normalization implies that the closer you are to 0 degrees the higher Max Temps are.

Humidity (%) vs. Latitude: Observation #2

Equator

One thing that stands out right away about this graph is the amount of clustering around -5 though 0 degrees and at 40 through 60 Latitude degrees. I have more high Humidity samples than lower. However, it does not appear that there is an obvious high humidity trend around the equator.

Cloudiness (%) vs. Latitude: Observation #3

Equator

The distribution of points in this graph is fairly spread out. There are clear lines at Cloudiness (%)'s: 0, 20, 75 There is possible evidence that cities closer to the equator are less clowdy. There seems to be verry little clusters close to 0 degrees

Wind Speed (mph) vs. Latitude: Observation #4

Equator

Obviously we can't have negative windspead but I have more low windspeed samples than high windspeed samples. Moving from left to righ on the X axis does not indicate variation in latitude would cause higher windspead. This is another graph with a wide distribution of points.

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