update

pages/2_↔️_Comparision.py

@@ -1,93 +1,146 @@
 import streamlit as st
 import leafmap.foliumap as leafmap
-import leafmap.colormaps as cm
+import json
+import requests
+
+
+# Functions to dynamically fetch columns
+def get_columns_from_geojson(geojson_data):
+    """Retrieve column names from a GeoJSON data."""
+    if "features" in geojson_data:
+        properties = geojson_data["features"][0]["properties"]
+        return list(properties.keys())
+    return []
+
+
+def get_columns_from_url(url):
+    """Retrieve column names from a GeoJSON URL."""
+    response = requests.get(url)
+    geojson_data = response.json()
+    return get_columns_from_geojson(geojson_data)
+
 
 st.set_page_config(layout="wide")
 
+# Sidebar Information
 st.sidebar.info(
-    """
+    '''
     - Web App URL: <https://interactive-crime-map.hf.space/>
     - HuggingFace repository: <https://huggingface.co/spaces/interactive-crime/map/tree/main>
-    """
+    '''
 )
 
 st.sidebar.title("Contact")
 st.sidebar.info(
-    """
+    '''
     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)
-    """
+    '''
 )
 
-st.title("Comparision of Hate Tweets, Hate Crime Rates and Total Crime Rates")
+# Title and Description
+st.title("Interactive Analysis of Hate Metrics in London & Custom Dataset Visualization")
+
 st.markdown(
-    """
-    These interactive maps illustrate a comparison of overall borough-level rates based on Twitter and London Metropolitan Police Service (MPS) data as of December 2022.
+    '''
+    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. 
 
-    In the first map shows the representation of hate tweets according to Twitter data, while the second and third maps shows the representation of rates of hate and all crimes according to MPS data.
-    """
+    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.
+    '''
 )
 
-row1_col1, row1_col2, row1_col3 = st.columns([1, 1, 1])
+# File Uploader
+uploaded_file = st.file_uploader("Upload a GeoJSON file", type=["geojson"])
+uploaded_geojson = None
+
+# Map URLs
+map_1 = "https://raw.githubusercontent.com/yunusserhat/data/main/data/boroughs_count_df_2022_dec.geojson"
+map_2 = "https://raw.githubusercontent.com/yunusserhat/data/main/data/mps_hate_2022_dec_count.geojson"
+map_3 = "https://raw.githubusercontent.com/yunusserhat/data/main/data/mps2022dec_count.geojson"
+
+if uploaded_file:
+    try:
+        uploaded_geojson = json.load(uploaded_file)
+        if "features" not in uploaded_geojson:
+            st.warning("The uploaded file does not seem to be a valid GeoJSON format.")
+            uploaded_geojson = None
+        else:
+            st.success("GeoJSON file uploaded successfully!")
+    except json.JSONDecodeError:
+        st.error("Failed to decode the uploaded file. Please ensure it's a valid GeoJSON format.")
+
+# Map Selection
+map_choices = ["Hate Tweets", "MPS Hate Crime Data", "MPS All Crime Data"]
+if uploaded_geojson:
+    map_choices.append("Uploaded GeoJSON")
+
+selected_map_1 = st.selectbox("Select data for Map 1", map_choices)
+
+# Determine the columns based on the selected dataset for Map 1
+if selected_map_1 == "Uploaded GeoJSON" and uploaded_geojson:
+    available_columns_1 = get_columns_from_geojson(uploaded_geojson)
+elif selected_map_1 == "Hate Tweets":
+    available_columns_1 = get_columns_from_url(map_1)
+elif selected_map_1 == "MPS Hate Crime Data":
+    available_columns_1 = get_columns_from_url(map_2)
+elif selected_map_1 == "MPS All Crime Data":
+    available_columns_1 = get_columns_from_url(map_3)
+
+selected_column_1 = st.selectbox("Select column for Map 1 visualization", available_columns_1)
+
+selected_map_2 = st.selectbox("Select data for Map 2", map_choices)
+
+# Determine the columns based on the selected dataset for Map 2
+if selected_map_2 == "Uploaded GeoJSON" and uploaded_geojson:
+    available_columns_2 = get_columns_from_geojson(uploaded_geojson)
+elif selected_map_2 == "Hate Tweets":
+    available_columns_2 = get_columns_from_url(map_1)
+elif selected_map_2 == "MPS Hate Crime Data":
+    available_columns_2 = get_columns_from_url(map_2)
+elif selected_map_2 == "MPS All Crime Data":
+    available_columns_2 = get_columns_from_url(map_3)
+
+selected_column_2 = st.selectbox("Select column for Map 2 visualization", available_columns_2)
+
+# Display Maps
+row1_col1, row1_col2 = st.columns([1, 1])
 
-# Twitter Hate Tweets Map
 with row1_col1:
-    twitter = "https://raw.githubusercontent.com/yunusserhat/data/main/data/boroughs_count_df_2022_dec.geojson"
     m1 = leafmap.Map(center=[51.50, -0.1], zoom=10)
-    m1.add_data(
-        twitter,
-        column="count",
-        scheme='Quantiles',
-        cmap='YlOrRd',
-        legend_title='Total Hate Tweet Number'
-    )
-
-# MPS Hate Crimes Map
+    if selected_map_1 == "Uploaded GeoJSON":
+        m1.add_data(uploaded_geojson, column=selected_column_1)
+    elif selected_map_1 == "Hate Tweets":
+        m1.add_data(map_1, column=selected_column_1)
+    elif selected_map_1 == "MPS Hate Crime Data":
+        m1.add_data(map_2, column=selected_column_1)
+    else:
+        m1.add_data(map_3, column=selected_column_1)
+
 with row1_col2:
-    mps_hate = "https://raw.githubusercontent.com/yunusserhat/data/main/data/mps_hate_2022_dec_count.geojson"
     m2 = leafmap.Map(center=[51.50, -0.1], zoom=10)
-    m2.add_data(
-        mps_hate,
-        column="Hate_Crime_Number",
-        scheme='Quantiles',
-        cmap='YlOrRd',
-        legend_title='Hate Crime Number'
-    )
-
-# MPS Total Crimes Map
-with row1_col3:
-    mps_total = "https://raw.githubusercontent.com/yunusserhat/data/main/data/mps2022dec_count.geojson"
-    m3 = leafmap.Map(center=[51.50, -0.1], zoom=10)
-    m3.add_data(
-        mps_total,
-        column="Crime_Number",
-        scheme='Quantiles',
-        cmap='YlOrRd',
-        legend_title='Total Crime Number'
-    )
-
-row2_col1, row2_col2, row2_col3 = st.columns([1, 1, 1])
-
-# Setting the zoom and center for each map
+    if selected_map_2 == "Uploaded GeoJSON":
+        m2.add_data(uploaded_geojson, column=selected_column_2)
+    elif selected_map_2 == "Hate Tweets":
+        m2.add_data(map_1, column=selected_column_2)
+    elif selected_map_2 == "MPS Hate Crime Data":
+        m2.add_data(map_2, column=selected_column_2)
+    else:
+        m2.add_data(map_3, column=selected_column_2)
+
+# Zoom
 longitude = -0.1
 latitude = 51.50
 zoomlevel = st.number_input("Zoom", 0, 20, 10)
 
+row2_col1, row2_col2 = st.columns([1, 1])
+
 with row2_col1:
     m1.set_center(longitude, latitude, zoomlevel)
-
 with row2_col2:
     m2.set_center(longitude, latitude, zoomlevel)
 
-with row2_col3:
-    m3.set_center(longitude, latitude, zoomlevel)
-
-row3_col1, row3_col2, row3_col3 = st.columns([1, 1, 1])
+row3_col1, row3_col2 = st.columns([1, 1])
 
 with row3_col1:
     m1.to_streamlit()
-
 with row3_col2:
     m2.to_streamlit()
-
-with row3_col3:
-    m3.to_streamlit()

pages/4_Test.py

@@ -35,7 +35,7 @@ st.sidebar.info(
 )
 
 # Title and Description
-st.title("Interactive Analysis of Hate Metrics in London and & Custom Dataset Visualization")
+st.title("Interactive Analysis of Hate Metrics in London & Custom Dataset Visualization")
 
 st.markdown(
     '''