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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() | |