Weather_forecast

Documentation

Description This script performs weather forecasts based on user-supplied weather information for a city. Additionally, it also allows you to obtain city zip code information and display weather data in a bar graph. And uses Scikit-Learn, for machine learning based on meteorological data and data storing in csv file

Dependencies

Make sure the following libraries are installed before running the script requests Flask pandas scikit-learn( MLPClassifier) matplotlib

You can install them using the command:

pip install requests Flask pandas scikit-learn matplotlib

or

pip install -r requirements.txt

Functionalities

Function new_weather_forecast(city) This function takes the name of a city as a parameter and performs the following actions:

• Obtains city weather data using the HGBrasil API.
• Displays information about temperature, date, time, description, city and wind speed.
• Saves the data to a CSV file called climate_weather.csv.
• Reads the CSV file, selects relevant columns, and splits the data into training and testing sets.
• Train a Neural Network model using MLPClassifier of scikit-learn.
• Makes predictions on the test set and displays the predicted weather condition along with the probability of rain.
• Identifies days with a probability of rain above 50%.
• Creates a bar chart showing the amount of rain, percentage of clouds, and probability of rain for each day.

Function get_information_cep(zip_code)

This function receives a CEP as a parameter and performs the following actions:

• Gets information about the CEP using the ViaCEP API.

• Displays the zip code, street, complement, neighborhood, city and UF

Comments

• Make sure to replace 'YOUR KEY' in the HGBrasil API URL with your actual API key.

• The get_information_cep(zip_code) function is called automatically after obtaining the CEP information. If you don't want this functionality, comment out or remove the new_prevision(city) function call new_weather_forecast(city)

[Silas Vasconcelos Cruz/Author]