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This project is in two parts. First, WeatherPy visualizes the weather of 500+ cities across the world of varying distances from the equator, using Python script, CityPy, and OpenWeatherMap APIs. The second part, VacationPy, uses Jupiter-Gmaps and the Google Places API to create a heatmap and filter down cities.

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Karla-Flores/Python-API

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Python-API---Challenge

  1. Maximum temperature vs. Latitude in Northern Hemisphere shows a high negative correlation -0.81, and the r-square is 0.66, which suggests the tendency toward the poles. The data points are concentrated well around the regression line, indicating a good fit. On the other hand, the Southern Hemisphere's plot has a positive correlation of 0.74, and the r-square is 0.55; the observation is similar.

  2. Screen Shot 2021-05-30 at 10 46 56 PM

    Screen Shot 2021-05-30 at 11 20 12 PM

  3. There is no correlation between Latitude and humidity, which the graphics Northern Hemisphere - Humidity (%) vs. Latitude and Southern Hemisphere - Humidity (%) vs. Latitude corroborate. The r-square values are in Northern Hemisphere is 0.0 and Southern Hemisphere is 0.04; these values are so low that they confirm a poor correlation.

  4. Screen Shot 2021-05-30 at 11 28 19 PM

    Screen Shot 2021-05-30 at 11 29 10 PM

  5. There is no correlation between Latitude and wind speed, which the graphics Northern Hemisphere - Wind Speed (kph) vs. Latitude and Southern Hemisphere - Wind Speed (kph) vs. Latitude corroborate. The r-square values are in Northern Hemisphere 0.02 and Southern Hemisphere 0.07; these values are so low that they confirm a poor correlation.

  6. Screen Shot 2021-05-30 at 11 41 09 PM

    Screen Shot 2021-05-30 at 11 41 30 PM

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This project is in two parts. First, WeatherPy visualizes the weather of 500+ cities across the world of varying distances from the equator, using Python script, CityPy, and OpenWeatherMap APIs. The second part, VacationPy, uses Jupiter-Gmaps and the Google Places API to create a heatmap and filter down cities.

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