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Delete pages/4_Test.py
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pages/4_Test.py
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import streamlit as st
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import leafmap.foliumap as leafmap
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import json
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import requests
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# Functions to dynamically fetch columns
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def get_columns_from_geojson(geojson_data):
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"""Retrieve column names from a GeoJSON data."""
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if "features" in geojson_data:
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properties = geojson_data["features"][0]["properties"]
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return list(properties.keys())
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return []
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def get_columns_from_url(url):
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"""Retrieve column names from a GeoJSON URL."""
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response = requests.get(url)
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geojson_data = response.json()
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return get_columns_from_geojson(geojson_data)
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st.set_page_config(layout="wide")
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# Sidebar Information
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st.sidebar.info(
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'''
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- Web App URL: <https://interactive-crime-map.hf.space/>
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- HuggingFace repository: <https://huggingface.co/spaces/interactive-crime/map/tree/main>
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'''
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)
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st.sidebar.title("Contact")
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st.sidebar.info(
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'''
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Yunus Serhat Bıçakçı at [yunusserhat.com](https://yunusserhat.com) | [GitHub](https://github.com/yunusserhat) | [Twitter](https://twitter.com/yunusserhat) | [LinkedIn](https://www.linkedin.com/in/yunusserhat)
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'''
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)
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# Title and Description
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st.title("Interactive Analysis of Hate Metrics in London & Custom Dataset Visualization")
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st.markdown(
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'''
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Dive into an interactive analysis of hate metrics in London, exploring the disparities and correlations between hate-related tweets and reported crimes in boroughs. This platform offers a comparative visualization based on data from X and the London Metropolitan Police Service as of December 2022.
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Additionally, users can upload and visualize their own GeoJSON datasets, facilitating personalized analysis and insights. Delve deeper into the patterns of hate sentiment, understand how online behavior might mirror real-world incidents, or uncover patterns in your own data.
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'''
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)
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# File Uploader
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uploaded_file = st.file_uploader("Upload a GeoJSON file", type=["geojson"])
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uploaded_geojson = None
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# Map URLs
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map_1 = "https://raw.githubusercontent.com/yunusserhat/data/main/data/boroughs_count_df_2022_dec.geojson"
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map_2 = "https://raw.githubusercontent.com/yunusserhat/data/main/data/mps_hate_2022_dec_count.geojson"
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map_3 = "https://raw.githubusercontent.com/yunusserhat/data/main/data/mps2022dec_count.geojson"
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if uploaded_file:
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try:
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uploaded_geojson = json.load(uploaded_file)
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if "features" not in uploaded_geojson:
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st.warning("The uploaded file does not seem to be a valid GeoJSON format.")
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uploaded_geojson = None
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else:
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st.success("GeoJSON file uploaded successfully!")
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except json.JSONDecodeError:
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st.error("Failed to decode the uploaded file. Please ensure it's a valid GeoJSON format.")
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# Map Selection
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map_choices = ["Hate Tweets", "MPS Hate Crime Data", "MPS All Crime Data"]
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if uploaded_geojson:
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map_choices.append("Uploaded GeoJSON")
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selected_map_1 = st.selectbox("Select data for Map 1", map_choices)
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# Determine the columns based on the selected dataset for Map 1
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if selected_map_1 == "Uploaded GeoJSON" and uploaded_geojson:
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available_columns_1 = get_columns_from_geojson(uploaded_geojson)
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elif selected_map_1 == "Hate Tweets":
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available_columns_1 = get_columns_from_url(map_1)
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elif selected_map_1 == "MPS Hate Crime Data":
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available_columns_1 = get_columns_from_url(map_2)
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elif selected_map_1 == "MPS All Crime Data":
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available_columns_1 = get_columns_from_url(map_3)
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selected_column_1 = st.selectbox("Select column for Map 1 visualization", available_columns_1)
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selected_map_2 = st.selectbox("Select data for Map 2", map_choices)
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# Determine the columns based on the selected dataset for Map 2
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if selected_map_2 == "Uploaded GeoJSON" and uploaded_geojson:
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available_columns_2 = get_columns_from_geojson(uploaded_geojson)
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elif selected_map_2 == "Hate Tweets":
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available_columns_2 = get_columns_from_url(map_1)
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elif selected_map_2 == "MPS Hate Crime Data":
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available_columns_2 = get_columns_from_url(map_2)
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elif selected_map_2 == "MPS All Crime Data":
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available_columns_2 = get_columns_from_url(map_3)
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selected_column_2 = st.selectbox("Select column for Map 2 visualization", available_columns_2)
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# Display Maps
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row1_col1, row1_col2 = st.columns([1, 1])
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with row1_col1:
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m1 = leafmap.Map(center=[51.50, -0.1], zoom=10)
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if selected_map_1 == "Uploaded GeoJSON":
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m1.add_data(uploaded_geojson, column=selected_column_1)
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elif selected_map_1 == "Hate Tweets":
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m1.add_data(map_1, column=selected_column_1)
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elif selected_map_1 == "MPS Hate Crime Data":
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m1.add_data(map_2, column=selected_column_1)
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else:
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m1.add_data(map_3, column=selected_column_1)
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with row1_col2:
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m2 = leafmap.Map(center=[51.50, -0.1], zoom=10)
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if selected_map_2 == "Uploaded GeoJSON":
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m2.add_data(uploaded_geojson, column=selected_column_2)
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elif selected_map_2 == "Hate Tweets":
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m2.add_data(map_1, column=selected_column_2)
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elif selected_map_2 == "MPS Hate Crime Data":
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m2.add_data(map_2, column=selected_column_2)
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else:
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m2.add_data(map_3, column=selected_column_2)
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# Zoom
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longitude = -0.1
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latitude = 51.50
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zoomlevel = st.number_input("Zoom", 0, 20, 10)
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row2_col1, row2_col2 = st.columns([1, 1])
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with row2_col1:
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m1.set_center(longitude, latitude, zoomlevel)
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with row2_col2:
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m2.set_center(longitude, latitude, zoomlevel)
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row3_col1, row3_col2 = st.columns([1, 1])
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with row3_col1:
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m1.to_streamlit()
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with row3_col2:
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m2.to_streamlit()
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