| import streamlit as st | |
| import pandas as pd | |
| def create_resource_page(): | |
| st.title("Meteonet Dataset") | |
| with st.columns([0.1,0.8,0.1])[1]: | |
| st.image(image="src/media/meteonet.png", caption="Regions explored in Meteonet Dataset", width=1000) | |
| data = { | |
| "Data Type": ["Total Rain radar images", "Total Satellite Images", "Total Wind maps in U direction", "Total Wind maps in V direction"], | |
| "2016": [105389, 8751, 9100, 9100], | |
| "2017": [105105, 8745, 8683, 8683], | |
| "2018": [105103, 8744, 8159, 8066], | |
| "Total": [315597, 26240, 25942, 25849] | |
| } | |
| df = pd.DataFrame(data).set_index("Data Type") | |
| st.write(""" | |
| Dataset Used for this is the Meteonet Dataset by Meteo France: [Meteonet](https://meteofrance.github.io/meteonet). We have utilized below data sources from the dataset in training and testing the application.""") | |
| st.table(df) | |