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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+distance.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,106 @@
+# %%
+import gradio as gr
+import pandas as pd
+import pickle
+
+
+with open("raoul_aufgabe_mit_distance_to_hb.pkl", "rb") as f:
+    model = pickle.load(f)
+
+
+features = ['rooms', 'area', 'pop', 'pop_dens', 'frg_pct', 'emp', 'tax_income', 'room_per_m2', 'luxurious', 'temporary', 'furnished', 'area_cat_ecoded',
+       '(LUXURIÖS)', '(POOL)', '(SEESICHT)',
+       '(EXKLUSIV)', '(ATTIKA)', '(LOFT)', 'Kreis 6', 'Kreis 11', 'Kreis 12', 'Kreis 10',
+       'Kreis 4', 'Kreis 1', 'Kreis 9', 'Kreis 5', 'Kreis 7', 'Kreis 3',
+       'Kreis 2', 'Kreis 8', 'distance_to_hb']
+
+
+from math import radians, sin, cos, sqrt, atan2
+
+def haversine_distance(lat, lon, center_lat=47.3769, center_lon=8.5417):
+    R = 6371  
+    dlat = radians(lat - center_lat)
+    dlon = radians(lon - center_lon)
+    a = sin(dlat / 2) ** 2 + cos(radians(lat)) * cos(radians(center_lat)) * sin(dlon / 2) ** 2
+    c = 2 * atan2(sqrt(a), sqrt(1 - a))
+    return R * c  
+
+
+def predict_price(rooms, area, pop, pop_dens, frg_pct, emp, tax_income, room_per_m2,
+                  luxurious, temporary, furnished, area_cat_ecoded, lux, pool, seesicht,
+                  exklusiv, attika, loft, k6, k11, k12, k10, k4, k1, k9, k5, k7, k3, k2, k8,
+                  lat, lon):
+    distance = haversine_distance(lat, lon)
+    input_data = pd.DataFrame([[rooms, area, pop, pop_dens, frg_pct, emp, tax_income, room_per_m2,
+                                 luxurious, temporary, furnished, area_cat_ecoded, lux, pool,
+                                 seesicht, exklusiv, attika, loft, k6, k11, k12, k10, k4, k1,
+                                 k9, k5, k7, k3, k2, k8, distance]],
+                               columns=features)
+    pred = model.predict(input_data)[0]
+    return f"Estimated Rent Price: CHF {pred:.2f}"
+
+
+inputs = [
+    gr.Number(label="Rooms"),
+    gr.Number(label="Area (m²)"),
+    gr.Number(label="Population"),
+    gr.Number(label="Population Density"),
+    gr.Number(label="Foreigners (%)"),
+    gr.Number(label="Employment"),
+    gr.Number(label="Taxable Income"),
+    gr.Number(label="Room per m²"),
+    gr.Checkbox(label="Luxurious"),
+    gr.Checkbox(label="Temporary"),
+    gr.Checkbox(label="Furnished"),
+    gr.Number(label="Area Category Encoded"),
+    gr.Checkbox(label="(LUXURIÖS)"),
+    gr.Checkbox(label="(POOL)"),
+    gr.Checkbox(label="(SEESICHT)"),
+    gr.Checkbox(label="(EXKLUSIV)"),
+    gr.Checkbox(label="(ATTIKA)"),
+    gr.Checkbox(label="(LOFT)"),
+    gr.Checkbox(label="Kreis 6"),
+    gr.Checkbox(label="Kreis 11"),
+    gr.Checkbox(label="Kreis 12"),
+    gr.Checkbox(label="Kreis 10"),
+    gr.Checkbox(label="Kreis 4"),
+    gr.Checkbox(label="Kreis 1"),
+    gr.Checkbox(label="Kreis 9"),
+    gr.Checkbox(label="Kreis 5"),
+    gr.Checkbox(label="Kreis 7"),
+    gr.Checkbox(label="Kreis 3"),
+    gr.Checkbox(label="Kreis 2"),
+    gr.Checkbox(label="Kreis 8"),
+    gr.Number(label="Latitude"),
+    gr.Number(label="Longitude")
+]
+
+examples = [
+    [3, 75, 100000, 1200, 30, 150000, 25000, 1.2, True, False, True, 1, True, False, True, False, True, False,
+     True, False, False, False, False, False, False, False, False, False, False, False,
+     47.3830, 8.5470],
+
+    [2, 55, 90000, 1500, 40, 140000, 22000, 1.3, False, True, True, 2, False, True, False, True, True, False,
+     False, False, False, False, True, False, False, False, False, False, False, False,
+     47.3750, 8.5275],
+
+    [4, 100, 130000, 1900, 28, 160000, 27000, 1.5, True, False, False, 3, True, True, True, False, False, True,
+     False, False, False, False, False, True, False, False, False, False, False, False,
+     47.3660, 8.5445],
+
+    [2, 60, 85000, 1100, 35, 135000, 21000, 1.1, False, False, True, 0, False, False, False, False, False, False,
+     False, False, False, False, False, False, False, False, False, False, False, False,
+     47.4100, 8.4900]
+]
+
+demo = gr.Interface(
+    fn=predict_price,
+    inputs=inputs,
+    outputs="text",
+    examples=examples,
+    title="Zürich Apartment Rent Estimator",
+    description="Predicts the estimated monthly rent (CHF) for an apartment in Zürich based on various features."
+)
+
+demo.launch()
+# %%

raoul_aufgabe_mit_distance_to_hb.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:216710efc7a54e89c75f6c9ab0acf194a60c5148ac760b36becf2b83813fd039
+size 6713529

requirements.txt

@@ -0,0 +1,3 @@
+gradio
+pandas
+scikit-learn