weather / eda.py
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import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
def run():
# Create a title for the app
st.title('Prediction of Weather Conditions')
# Display an image
image = Image.open('weather.jpeg')
st.image(image, caption='Predict the weather conditions using machine learning models')
st.markdown('------')
# Subheading for Exploratory Data Analysiss
st.subheader('Exploratory Data Analysis Weather Conditions')
# Load the dataset
credit_card_data = pd.read_csv('weather_classification_data.csv')
st.write(credit_card_data)
# Average Temperature by Season
st.write("#### Average Temperature by Season")
image = Image.open('Average Temperature by Season.png')
st.image(image, caption='Graph showing the average temperatures across different seasons')
# Average Temperature per Location
st.write("#### Average Temperature per Site")
image = Image.open('Average Temperature per Site.png')
st.image(image, caption='Graph depicting the average temperatures for various locations')
# Number of Weather Types per Season
st.write("#### Number of Weather Types per Season")
image = Image.open('Number of Weather Types per Season.png')
st.image(image, caption='Bar chart showing the number of different weather types in each season')
# Average Humidity per Weather Type
st.write("#### Average Humidity per Weather Type")
image = Image.open('Average Humidity per Weather Type.png')
st.image(image, caption='Graph displaying the average humidity levels for each weather type')
if __name__ == "__main__":
run()