Weather Forecast Project In Python With Source Code

The Weather Forecast Project In Python is a fully functional console-based application developed in Python that covers all of the features that IT students and computer-related courses will require for their college projects or assignments. These can be helpful articles and projects that you are looking for. This Weather Forecasting Project In Python is a basic console-based program that uses machine learning to assess if the current weather scenario is suitable for playing or not. It is carried out using supervised learning, in which data is first provided to train the system, and then the results for new data are generated. This Weather App Using Python is quite useful, and the concept and logic of the project are simple to grasp. The source code is open source and free to use. Simply scroll down and click the download option.

Watch the whole video to see how to run the Weather Forecast Project In Python, from start to finish!

Weather Forecast Project In Python : Project Output

Weather Forecast Output
Weather Forecast Output

What Is Weather Forecast Project In Python?

The Weather Forecast App Using Python is essentially a scientific prediction of the weather conditions in the future. The state of the atmosphere at a given time is expressed in terms of the most important meteorological variables as weather condition. Significant weather variables that are forecast vary by location.

Importance Of Weather Forecasting

This Weather Forecast Using Python is important because it predicts weather conditions to give people and organizations information they can use to reduce losses caused by weather and improve societal benefits, such as protecting life and property, improving public health and safety, and helping the economy and quality of life.

Why Do We Need To Have A Weather Forecast?

The Python Code For Weather Forecast is needed because it forecasts weather that includes weather warnings, which are used to protect people and property. Predictions based on temperature and rainfall are important for agriculture, so they are also important for traders in commodity markets. Utility companies use forecasts of the weather to estimate how much power will be used in the coming days.

Benefits Of Weather Forecast Project In Python

  • People can make smart choices about when and where to go on vacation – People’s work schedules are so full that they rarely have time to rest or even spend time with each other. Most of the time, workaholics like this use their vacation time to go on a relaxing trip. But these trips can be cut short by the weather if it starts to rain or if the sun stays out for too long. The weather forecast can be a big help in planning a trip for when the weather will be good. Still, if you don’t want to delay a tour, you can look for a place where the weather is good for the activities you want to do.
  • The weather forecast helps keep people safe – When it rains a lot, rivers and other bodies of water flood, sending water into people’s homes, gardens, and even public spaces. This affects a lot of people. If flooding comes out of nowhere, it can kill a lot of people. Still, this kind of disaster can be avoided with the help of weather forecasting. If the meteorological department finds out that a weather disaster is about to happen, they can tell people to leave the area that is likely to be affected.
  • Weather forecasting is important in the transportation sector – There have been reports of ships turning over and planes crashing in different parts of the world. Most of the time, bad weather is the main cause of these kinds of accidents. Forecasting the weather is important in the transportation industry because it lets pilots and ship captains know when the weather isn’t good enough to fly or sail.
  • Benefits of Agriculture – In the past, farmers lost a lot of money because of changes in the weather. Now, farmers use new technology to plan their schedules. Farmers can plan what to plant and when to plant it by looking at weather forecasts. For example, if it’s expected to rain for three months, farmers can plant seeds that will grow and be ready to harvest in that time.

About the Project : Weather Forecast Project In Python With Source Code

The Weather Forecast Project In Python is a console-based application written in the Python programming language. The project is open source, and it was made for novices who wish to learn Python. This Weather Forecast Project In Python With Source Code can run in console mode, which means that you have to enter it manually. The project will ask you what the weather is like outside, and you just have to type the answer. As soon as you finish answering all the questions, the system will give you the calculated conditional probabilities of the weather. I hope this article helps you a lot.

Project Details and Technology : Weather Forecast Project In Python

Project Name:Weather Forecast Project In Python
Abstract:This Weather Forecast Project In Python is a basic Python project that aims to predict incoming weather, which can be helpful to all human kind.
Language/s Used:Python (GUI Based)
Python version (Recommended):3.8 or 3.9
Type:Console Application
Developer:Source Code Hero
Weather Forecast Project In Python With Source Code – Project Information

The code given below is the full source code on Weather Prediction Using Python.

The given code below is a python file for

from functools import reduce
import pandas as pd
import pprint

class Classifier():
    data = None
    class_attr = None
    priori = {}
    cp = {}
    hypothesis = None

    def __init__(self,filename=None, class_attr=None ): = pd.read_csv(filename, sep=',', header =(0))
        self.class_attr = class_attr

        probability(class) =    How many  times it appears in cloumn
                                  count of all class attribute
    def calculate_priori(self):
        class_values = list(set([self.class_attr]))
        class_data =  list([self.class_attr])
        for i in class_values:
            self.priori[i]  = class_data.count(i)/float(len(class_data))
        print ("Priori Values: ", self.priori)

        Here we calculate the individual probabilites 
        P(outcome|evidence) =   P(Likelihood of Evidence) x Prior prob of outcome
    def get_cp(self, attr, attr_type, class_value):
        data_attr = list([attr])
        class_data = list([self.class_attr])
        total =1
        for i in range(0, len(data_attr)):
            if class_data[i] == class_value and data_attr[i] == attr_type:
        return total/float(class_data.count(class_value))

        Here we calculate Likelihood of Evidence and multiple all individual probabilities with priori
        (Outcome|Multiple Evidence) = P(Evidence1|Outcome) x P(Evidence2|outcome) x ... x P(EvidenceN|outcome) x P(Outcome)
        scaled by P(Multiple Evidence)
    def calculate_conditional_probabilities(self, hypothesis):
        for i in self.priori:
            self.cp[i] = {}
            for j in hypothesis:
                self.cp[i].update({ hypothesis[j]: self.get_cp(j, hypothesis[j], i)})
        print ("\nCalculated Conditional Probabilities: \n")

    def classify(self):
        print ("Result: ")
        for i in self.cp:
            print (i, " ==> ", reduce(lambda x, y: x*y, self.cp[i].values())*self.priori[i])

'''    Exit from the system it the input is "x" or "exit"   '''
def exitSystem():
        print("System Terminated!")
        print("Thank you for using this system!")

if __name__ == "__main__":
    c = Classifier(filename="dataset.csv", class_attr="Play")
    print("Enter the correct values shown in the option! *Case Sensitive")
    print("Enter 'x' or 'exit' to exit from the system")
    outlook = input("Whats the weather outside? (Sunny, Rainy, Overcast):")
    if outlook.lower() == 'x' or outlook.lower() == 'exit':
    temp = input("Whats the temperature today? (Hot, Mild, Cool):")
    if temp.lower() == 'x' or temp.lower()== 'exit':
    humidity = input("Whats the humidity? (High, Normal):")
    if humidity.lower() == 'x' or humidity.lower()== 'exit':
    windy = input("Is it windy tody? (t or f):")
    if windy.lower() == 'x' or windy.lower()== 'exit':

    c.hypothesis = {"Outlook":outlook, "Temp":temp, "Humidity":humidity , "Windy":windy}

This Weather Forecast Project In Python also includes a downloadable Project With Source Code for free, just find the downloadable source code below and click to start downloading.

By the way, if you are new to python programming and you don’t have any idea what Python IDE to use, I have here a list of Best Python IDE for Windows, Linux, Mac OS for you. Additionally, I also have here How to Download and Install Latest Version of Python on Windows.

To start executing a Weather Forecast Project In Python, make sure that you have installed Python in your computer.

Weather Forecast Project In Python : Steps on how to run the project

Time needed: 5 minutes.

These are the steps on how to run Weather Forecast Project In Python

  • Download Source Code

    First, find the downloadable source code below and click to start downloading the source code file.
    Weather Forecast Project In Python Download Button

  • Extract File

    Next, after finished to download the file, go to file location and right click the file and click extract.
    Weather Forecast Project In Python Extract File

  • Open PyCharm

    Next, open pycharm IDE and open the project you’ve download.
    Weather Forecast Project In Python Open Project

  • Run Project

    Next, go to the PyCharm and click the run button to start executing the project.

    Weather Forecast Project In Python Run Project

Download Source Code below!


This Article is the way to enhance and develop our skills and logic ideas which is important in practicing the python programming language which is most well known and most usable programming language in many company.


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