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README.md

@@ -1,12 +1,6 @@
 ---
-title: Movement
-emoji: 🐢
-colorFrom: pink
-colorTo: red
+title: movement
+app_file: gradio_app.py
 sdk: gradio
 sdk_version: 5.38.0
-app_file: app.py
-pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

backend.py

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+"""
+Functions to scrape and graph data from TRAC's "ICE Detainees" page
+(https://tracreports.org/immigration/detentionstats/pop_agen_table.html).
+"""
+
+import streamlit as st
+import requests
+import pandas as pd
+import plotly.express as px
+
+colorblind_palette = colorblind_palette = [
+    "#377eb8",  # blue
+    "#ff7f00",  # orange
+    "#a65628",  # brown
+    "#999999",  # gray
+]
+
+
+@st.cache_data(ttl="15m")
+def get_detention_data():
+    """
+    Get the data which powers TRAC's "ICE Detainees" page and return it as a dataframe.
+
+    This function caches the data for 15 minutes. They seem to update the site just a few times a month, so this should
+    be fine.
+
+    URLS of interest:
+    1. TRAC Reports homepage: https://tracreports.org/
+    2. TRAC Reports Immigration page: https://tracreports.org/immigration/
+    3. TRAC Reports Immigration Detention Quick Facts page:
+       https://tracreports.org/immigration/quickfacts/detention.html
+    4. The "See More Data" page when you get on "Detention Quick Facts":
+       https://tracreports.org/immigration/detentionstats/pop_agen_table.html
+    5. The JSON which populates the Detention Quick Facts page:
+       https://tracreports.org/immigration/detentionstats/pop_agen_table.json
+
+    This function gets the data from (5), does some light processing, and returns it.
+    """
+    response = requests.get(
+        "https://tracreports.org/immigration/detentionstats/pop_agen_table.json"
+    )
+
+    df = pd.DataFrame(response.json())
+    df.date = pd.to_datetime(df.date).dt.date
+
+    return df
+
+
+def get_aa_count_chart():
+    """Get a chart that shows detentions by arresting authority as a count."""
+    df = get_detention_data()
+
+    df = df.rename(columns={"ice_all": "ICE", "cbp_all": "CBP", "total_all": "Total"})
+
+    # Converts df from wide to long
+    df_melted = df.melt(
+        id_vars="date",
+        value_vars=["ICE", "CBP", "Total"],
+        var_name="Arresting Authority",
+        value_name="count",
+    )
+
+    fig = px.line(
+        df_melted,
+        x="date",
+        y="count",
+        color="Arresting Authority",
+        color_discrete_sequence=colorblind_palette,
+    )
+
+    fig.update_layout(
+        xaxis_title="Date",
+        yaxis_title="Detainees",
+        title="ICE Detainees by Date* and Arresting Authority",
+    )
+
+    return fig
+
+
+def get_aa_pct_chart():
+    """Get a chart that shows detentions by arresting authority as a percent."""
+    df = get_detention_data()
+
+    df["ICE"] = (df.ice_all / df.total_all * 100).round()  # Rounding is in the original
+    df["CBP"] = (df.cbp_all / df.total_all * 100).round()
+
+    # Converts df from wide to long
+    df_melted = df.melt(
+        id_vars="date",
+        value_vars=["ICE", "CBP"],
+        var_name="Arresting Authority",
+        value_name="percent",
+    )
+
+    fig = px.line(
+        df_melted,
+        x="date",
+        y="percent",
+        color="Arresting Authority",
+        color_discrete_sequence=colorblind_palette,
+    )
+
+    fig.update_layout(
+        xaxis_title="Date",
+        yaxis_title="Percent",
+        title="ICE Detainees by Date* and Arresting Authority",
+    )
+
+    return fig
+
+
+def get_col_prefix(authority):
+    """
+    Return the column prefix for the UI text "ICE", "CBP" and "All".
+
+    When viewing the criminality dataset the UI lets users select stats for each arresting authority ("ICE", "CBP") and
+    together ("All"). In the dataset, these subsets are denoted by the column prefixes "ice", "cbp" and "total". This
+    function converts the UI text to the column prefix.
+    """
+    if authority == "All":
+        return "total"
+    elif authority == "ICE":
+        return "ice"
+    elif authority == "CBP":
+        return "cbp"
+    else:
+        raise ValueError(f"Unknown authority {authority}")
+
+
+def get_criminality_count_chart(authority):
+    """Get a chart that shows the criminality of detainees by arresting authority as a count."""
+    df = get_detention_data()
+
+    # Converts df from wide to long
+    prefix = get_col_prefix(authority)
+    df = df.rename(
+        columns={
+            f"{prefix}_all": "Total",
+            f"{prefix}_conv": "Convicted Criminal",
+            f"{prefix}_pend": "Pending Criminal Charges",
+            f"{prefix}_other": "Other Immigration Violator",
+        }
+    )
+
+    df_melted = df.melt(
+        id_vars="date",
+        value_vars=[
+            "Convicted Criminal",
+            "Pending Criminal Charges",
+            "Other Immigration Violator",
+            "Total",
+        ],
+        var_name="Criminal Status",
+        value_name="count",
+    )
+
+    fig = px.line(
+        df_melted,
+        x="date",
+        y="count",
+        color="Criminal Status",
+        color_discrete_sequence=colorblind_palette,
+    )
+
+    fig.update_layout(
+        xaxis_title="Date",
+        yaxis_title="Detainees",
+        title="ICE Detainees by Date*, Criminality** and Arresting Authority",
+    )
+
+    return fig
+
+
+def get_criminality_pct_chart(authority):
+    """Get a chart that shows the criminality of detainees by arresting authority as a percent."""
+    df = get_detention_data()
+
+    prefix = get_col_prefix(authority)
+    all_col = f"{prefix}_all"
+    conv_col = f"{prefix}_conv"
+    pend_col = f"{prefix}_pend"
+    other_col = f"{prefix}_other"
+
+    df["Convicted Criminal"] = (
+        df[conv_col] / df[all_col] * 100
+    ).round()  # Rounding is in the original
+    df["Pending Criminal Charges"] = (df[pend_col] / df[all_col] * 100).round()
+    df["Other Immigration Violator"] = (df[other_col] / df[all_col] * 100).round()
+
+    # Converts df from wide to long
+    df_melted = df.melt(
+        id_vars="date",
+        value_vars=[
+            "Convicted Criminal",
+            "Pending Criminal Charges",
+            "Other Immigration Violator",
+        ],
+        var_name="Criminal Status",
+        value_name="percent",
+    )
+
+    fig = px.line(
+        df_melted,
+        x="date",
+        y="percent",
+        color="Criminal Status",
+        color_discrete_sequence=colorblind_palette,
+    )
+
+    fig.update_layout(
+        xaxis_title="Date",
+        yaxis_title="Percent",
+        title="ICE Detainees by Date*, Criminality** and Arresting Authority",
+    )
+
+    return fig
+
+
+def get_graph(dataset, display, authority):
+    """
+    Get the graph specified by the dataset, display and authority.
+
+    Parameters
+    ----------
+    - dataset: one of "Arresting Authority" or "Criminality"
+    - display: one of "Count" or "Percent"
+    - authority: one of "CBP" (for "Customers and Border Protection"), "ICE" (for "Immigration and Customers
+    Enforcement") or "All" (for the total number)
+
+    Returns
+    -------
+    - A plotly figure
+    """
+    if dataset == "Arresting Authority":
+        if display == "Count":
+            fig = get_aa_count_chart()
+        elif display == "Percent":
+            fig = get_aa_pct_chart()
+    elif dataset == "Criminality":
+        if display == "Count":
+            fig = get_criminality_count_chart(authority)
+        elif display == "Percent":
+            fig = get_criminality_pct_chart(authority)
+
+    if not fig:
+        raise ValueError(
+            f"Cannot create graph for dataset={dataset}, display={display}"
+        )
+
+    return fig

footnotes.py

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+"""
+These footnotes are taken verbatim from
+https://tracreports.org/immigration/detentionstats/pop_agen_table.html.
+We don't include the third and final footnote because it is not used anywhere
+on the page.
+"""
+
+
+def get_abbreviations_text():
+    return '"ICE" stands for "Immigration and Customs Enforcement". "CBP" stands for "Customs and Border Protection".'
+
+
+def get_date_footnote_text():
+    return (
+        "* Dates before 11/15/2021 refer to the date ICE posted the data; "
+        "dates after 11/15/2021 refer to the date the information was current as of."
+    )
+
+
+def get_criminality_footnote_text():
+    return (
+        "** ICE classifies an individual as a convicted criminal if they have been convicted "
+        "of any criminal violation. Violations can range from serious felonies all the way down "
+        "to a purely immigration violation (such as illegal entry which is a petty offense under "
+        "the U.S. Code), or a violation which results in only in a fine such as not keeping a dog "
+        "on a leash, fishing without a permit, driving a vehicle with a tail light out, etc. For "
+        "historical series on ICE detainees identifying the most serious offense they have been "
+        "convicted of along with other details such as when they entered the U.S., nationality, "
+        "gender, etc. go to https://tracreports.org/phptools/immigration/detention/"
+    )
+
+
+def get_date_footnote():
+    return f"""
+        <p style='font-size: 0.85em; font-style: italic; margin-top: 10px;'>
+        {get_abbreviations_text()}<br>
+        {get_date_footnote_text()}
+        </p>
+        """
+
+
+def get_criminality_footnote():
+    return f"""
+        <p style='font-size: 0.85em; font-style: italic; margin-top: 10px;'>
+        {get_abbreviations_text()}<br>
+        {get_date_footnote_text()}<br>
+        {get_criminality_footnote_text()}
+        </p>
+        """
+
+
+def get_footnote(dataset):
+    if dataset == "Arresting Authority":
+        return get_date_footnote()
+    elif dataset == "Criminality":
+        return get_criminality_footnote()
+    else:
+        raise ValueError(f"Unknown dataset {dataset}")

gradio_app.py

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+import gradio as gr
+import requests
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+
+# Color palette for accessibility
+colorblind_palette = [
+    "#377eb8",  # blue
+    "#ff7f00",  # orange
+    "#a65628",  # brown
+    "#999999",  # gray
+]
+
+# Cache for data (simple in-memory cache)
+_cached_data = None
+_cache_timestamp = None
+
+def get_detention_data():
+    """
+    Get the data which powers TRAC's "ICE Detainees" page and return it as a dataframe.
+    """
+    global _cached_data, _cache_timestamp
+    
+    import time
+    current_time = time.time()
+    
+    # Check if we have cached data that's less than 15 minutes old
+    if _cached_data is not None and _cache_timestamp is not None:
+        if current_time - _cache_timestamp < 900:  # 15 minutes in seconds
+            return _cached_data
+    
+    try:
+        response = requests.get(
+            "https://tracreports.org/immigration/detentionstats/pop_agen_table.json"
+        )
+        response.raise_for_status()
+        
+        df = pd.DataFrame(response.json())
+        df.date = pd.to_datetime(df.date).dt.date
+        
+        # Cache the data
+        _cached_data = df
+        _cache_timestamp = current_time
+        
+        return df
+    except Exception as e:
+        # Return empty dataframe if request fails
+        return pd.DataFrame()
+
+def get_col_prefix(authority):
+    """Return the column prefix for the UI text "ICE", "CBP" and "All"."""
+    if authority == "All":
+        return "total"
+    elif authority == "ICE":
+        return "ice"
+    elif authority == "CBP":
+        return "cbp"
+    else:
+        raise ValueError(f"Unknown authority {authority}")
+
+def get_aa_count_chart():
+    """Get a chart that shows detentions by arresting authority as a count."""
+    df = get_detention_data()
+    if df.empty:
+        return go.Figure().add_annotation(text="Error loading data", showarrow=False)
+    
+    df = df.rename(columns={"ice_all": "ICE", "cbp_all": "CBP", "total_all": "Total"})
+    
+    df_melted = df.melt(
+        id_vars="date",
+        value_vars=["ICE", "CBP", "Total"],
+        var_name="Arresting Authority",
+        value_name="count",
+    )
+    
+    fig = px.line(
+        df_melted,
+        x="date",
+        y="count",
+        color="Arresting Authority",
+        color_discrete_sequence=colorblind_palette,
+    )
+    
+    fig.update_layout(
+        xaxis_title="Date",
+        yaxis_title="Detainees",
+        title="ICE Detainees by Date* and Arresting Authority",
+    )
+    
+    return fig
+
+def get_aa_pct_chart():
+    """Get a chart that shows detentions by arresting authority as a percent."""
+    df = get_detention_data()
+    if df.empty:
+        return go.Figure().add_annotation(text="Error loading data", showarrow=False)
+    
+    df["ICE"] = (df.ice_all / df.total_all * 100).round()
+    df["CBP"] = (df.cbp_all / df.total_all * 100).round()
+    
+    df_melted = df.melt(
+        id_vars="date",
+        value_vars=["ICE", "CBP"],
+        var_name="Arresting Authority",
+        value_name="percent",
+    )
+    
+    fig = px.line(
+        df_melted,
+        x="date",
+        y="percent",
+        color="Arresting Authority",
+        color_discrete_sequence=colorblind_palette,
+    )
+    
+    fig.update_layout(
+        xaxis_title="Date",
+        yaxis_title="Percent",
+        title="ICE Detainees by Date* and Arresting Authority",
+    )
+    
+    return fig
+
+def get_criminality_count_chart(authority):
+    """Get a chart that shows the criminality of detainees by arresting authority as a count."""
+    df = get_detention_data()
+    if df.empty:
+        return go.Figure().add_annotation(text="Error loading data", showarrow=False)
+    
+    prefix = get_col_prefix(authority)
+    df = df.rename(
+        columns={
+            f"{prefix}_all": "Total",
+            f"{prefix}_conv": "Convicted Criminal",
+            f"{prefix}_pend": "Pending Criminal Charges",
+            f"{prefix}_other": "Other Immigration Violator",
+        }
+    )
+    
+    df_melted = df.melt(
+        id_vars="date",
+        value_vars=[
+            "Convicted Criminal",
+            "Pending Criminal Charges",
+            "Other Immigration Violator",
+            "Total",
+        ],
+        var_name="Criminal Status",
+        value_name="count",
+    )
+    
+    fig = px.line(
+        df_melted,
+        x="date",
+        y="count",
+        color="Criminal Status",
+        color_discrete_sequence=colorblind_palette,
+    )
+    
+    fig.update_layout(
+        xaxis_title="Date",
+        yaxis_title="Detainees",
+        title="ICE Detainees by Date*, Criminality** and Arresting Authority",
+    )
+    
+    return fig
+
+def get_criminality_pct_chart(authority):
+    """Get a chart that shows the criminality of detainees by arresting authority as a percent."""
+    df = get_detention_data()
+    if df.empty:
+        return go.Figure().add_annotation(text="Error loading data", showarrow=False)
+    
+    prefix = get_col_prefix(authority)
+    all_col = f"{prefix}_all"
+    conv_col = f"{prefix}_conv"
+    pend_col = f"{prefix}_pend"
+    other_col = f"{prefix}_other"
+    
+    df["Convicted Criminal"] = (df[conv_col] / df[all_col] * 100).round()
+    df["Pending Criminal Charges"] = (df[pend_col] / df[all_col] * 100).round()
+    df["Other Immigration Violator"] = (df[other_col] / df[all_col] * 100).round()
+    
+    df_melted = df.melt(
+        id_vars="date",
+        value_vars=[
+            "Convicted Criminal",
+            "Pending Criminal Charges",
+            "Other Immigration Violator",
+        ],
+        var_name="Criminal Status",
+        value_name="percent",
+    )
+    
+    fig = px.line(
+        df_melted,
+        x="date",
+        y="percent",
+        color="Criminal Status",
+        color_discrete_sequence=colorblind_palette,
+    )
+    
+    fig.update_layout(
+        xaxis_title="Date",
+        yaxis_title="Percent",
+        title="ICE Detainees by Date*, Criminality** and Arresting Authority",
+    )
+    
+    return fig
+
+def get_footnote_text(dataset):
+    """Get footnote text for the dataset."""
+    abbreviations = '"ICE" stands for "Immigration and Customs Enforcement". "CBP" stands for "Customs and Border Protection".'
+    date_footnote = "*Dates before 11/15/2021 refer to the date ICE posted the data; dates after 11/15/2021 refer to the date the information was current as of."
+    
+    if dataset == "Arresting Authority":
+        return f"{abbreviations}\n{date_footnote}"
+    elif dataset == "Criminality":
+        criminality_footnote = "**ICE classifies an individual as a convicted criminal if they have been convicted of any criminal violation. Violations can range from serious felonies all the way down to a purely immigration violation (such as illegal entry which is a petty offense under the U.S. Code), or a violation which results in only in a fine such as not keeping a dog on a leash, fishing without a permit, driving a vehicle with a tail light out, etc."
+        return f"{abbreviations}\n{date_footnote}\n{criminality_footnote}"
+    return ""
+
+def update_chart(dataset, display, authority):
+    """Update the chart based on user selections."""
+    try:
+        if dataset == "Arresting Authority":
+            if display == "Count":
+                fig = get_aa_count_chart()
+            elif display == "Percent":
+                fig = get_aa_pct_chart()
+        elif dataset == "Criminality":
+            if display == "Count":
+                fig = get_criminality_count_chart(authority)
+            elif display == "Percent":
+                fig = get_criminality_pct_chart(authority)
+        
+        footnote = get_footnote_text(dataset)
+        return fig, footnote
+    except Exception as e:
+        error_fig = go.Figure().add_annotation(
+            text=f"Error creating chart: {str(e)}", 
+            showarrow=False
+        )
+        return error_fig, "Error loading data"
+
+def get_data_info():
+    """Get information about the data."""
+    return """"""
+
+def download_data():
+    """Prepare data for download."""
+    df = get_detention_data()
+    if df.empty:
+        return None
+    return df.to_csv(index=False)
+
+# Create the Gradio interface
+def create_app():
+    with gr.Blocks(title="US Immigration Enforcement Data", theme=gr.themes.Soft()) as app:
+        gr.Markdown("# US Immigration Enforcement Data")
+        
+        with gr.Tabs():
+            with gr.TabItem("📈 Graphs"):
+                with gr.Row():
+                    dataset = gr.Dropdown(
+                        choices=["Arresting Authority", "Criminality"],
+                        value="Arresting Authority",
+                        label="Dataset"
+                    )
+                    display = gr.Dropdown(
+                        choices=["Count", "Percent"],
+                        value="Count",
+                        label="Display"
+                    )
+                    authority = gr.Dropdown(
+                        choices=["All", "ICE", "CBP"],
+                        value="All",
+                        label="Arresting Authority",
+                        visible=False
+                    )
+                
+                chart = gr.Plot()
+                footnote = gr.Markdown()
+                
+                # Update authority dropdown visibility based on dataset
+                def update_authority_visibility(dataset_choice):
+                    return gr.Dropdown(visible=(dataset_choice == "Criminality"))
+                
+                dataset.change(
+                    update_authority_visibility,
+                    inputs=[dataset],
+                    outputs=[authority]
+                )
+                
+                # Update chart when any input changes
+                for input_component in [dataset, display, authority]:
+                    input_component.change(
+                        update_chart,
+                        inputs=[dataset, display, authority],
+                        outputs=[chart, footnote]
+                    )
+                
+                # Initial chart load
+                app.load(
+                    update_chart,
+                    inputs=[dataset, display, authority],
+                    outputs=[chart, footnote]
+                )
+            
+            with gr.TabItem("📋 Data"):
+                gr.Markdown(get_data_info())
+                
+                with gr.Row():
+                    refresh_btn = gr.Button("Refresh Data")
+                    download_btn = gr.DownloadButton(
+                        "Download as CSV",
+                        lambda: download_data(),
+                        filename="ice_detention_data.csv"
+                    )
+                
+                data_display = gr.Dataframe(
+                    label="ICE Detention Data",
+                    wrap=True
+                )
+                
+                def refresh_data():
+                    global _cached_data, _cache_timestamp
+                    _cached_data = None
+                    _cache_timestamp = None
+                    df = get_detention_data()
+                    return df
+                
+                refresh_btn.click(refresh_data, outputs=[data_display])
+                
+                # Load data on app start
+                app.load(lambda: get_detention_data(), outputs=[data_display])
+    
+    
+    return app
+
+if __name__ == "__main__":
+    app = create_app()
+    app.launch()

ice_detention_data.csv

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requirements.txt

@@ -0,0 +1 @@
+gradio, pandas, plotly, requests

streamlit_app.py

@@ -0,0 +1,46 @@
+import streamlit as st
+import backend as be
+import footnotes
+
+st.title("US Immigration Enforcement Data")
+
+graph_tab, data_tab, about_tab = st.tabs(["📈 Graphs", "📋 Data", "ℹ️ About"])
+with graph_tab:
+    col1, col2, col3 = st.columns(3)
+    with col1:
+        dataset = st.selectbox("Dataset", ["Arresting Authority", "Criminality"])
+    with col2:
+        display = st.selectbox("Display", ["Count", "Percent"])
+    with col3:
+        # In the original dataset the "Criminality" table has 3 tables. This lets
+        # you see how the criminality of detainees varies by arresting authority.
+        if dataset == "Criminality":
+            authority = st.selectbox("Arresting Authority", ["All", "ICE", "CBP"])
+        else:
+            authority = None
+
+    fig = be.get_graph(dataset, display, authority)
+    st.plotly_chart(fig, use_container_width=True)
+    # Each dataset has different footnotes.
+    st.markdown(footnotes.get_footnote(dataset), unsafe_allow_html=True)
+with data_tab:
+    st.write(open("data.md").read())
+    df = be.get_detention_data()
+    st.dataframe(df, hide_index=True)
+    st.download_button(
+        label="Download as CSV",
+        data=df.to_csv(index=False),
+        file_name="ice_detention_data.csv",
+        mime="text/csv",
+    )
+with about_tab:
+    st.write(open("about.md").read())
+
+st.markdown(
+    """
+    ---
+    :small[Created by [Ari Lamstein](https://arilamstein.com/).
+    View the source code
+    [here](https://github.com/arilamstein/immigration_enforcement).]
+    """
+)