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Browse files- README.md +38 -0
- app.py +3 -1
- requirements.txt +2 -1
README.md
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---
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title: "Alaska Lightning Strikes Visualization"
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emoji: "⚡"
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colorFrom: "blue"
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colorTo: "purple"
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sdk: "streamlit"
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sdk_version: "1.9.0"
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app_file: app.py
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pinned: false
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---
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# Alaska Lightning Strikes Visualization
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This project visualizes lightning strikes in Alaska using `geopandas` and `contextily` to plot the data on an interactive map in a Streamlit application.
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## Description
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This application reads lightning strike data from a shapefile, projects it to a different coordinate reference system, and plots it on an interactive map with a basemap for better visualization. The data is plotted using `geopandas` and the basemap is added using `contextily`.
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## Setup
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To run this application, you need the following dependencies:
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- `streamlit`
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- `geopandas`
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- `contextily`
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- `matplotlib`
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These dependencies are listed in the `requirements.txt` file and will be automatically installed when you deploy this application on Hugging Face Spaces.
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## Usage
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To use the application:
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1. Input the shapefile path to load the data.
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2. The application will process the data and visualize it on a map.
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app.py
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import folium
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import zipfile
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from streamlit.components.v1 import html
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# Función para descargar y descomprimir el archivo
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def download_and_extract_data():
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# Descargar y descomprimir los datos
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st.title('Alaska Lightning Detection Network Analysis')
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st.subheader('
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with st.spinner('Downloading and extracting data...'):
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download_and_extract_data()
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ax.set_ylabel('Count')
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ax.grid(True)
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st.pyplot(fig)
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import folium
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import zipfile
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from streamlit.components.v1 import html
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import contextily as cx
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# Función para descargar y descomprimir el archivo
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def download_and_extract_data():
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# Descargar y descomprimir los datos
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st.title('Alaska Lightning Detection Network Analysis')
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st.subheader('Verificar los rayos. ')
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with st.spinner('Downloading and extracting data...'):
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download_and_extract_data()
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ax.set_ylabel('Count')
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ax.grid(True)
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st.pyplot(fig)
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requirements.txt
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folium
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matplotlib
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mapclassify
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streamlit-folium
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folium
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matplotlib
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mapclassify
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streamlit-folium
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contextily
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