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app.py

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+import os
+import shutil
+
+import gdown
+import pandas as pd
+import plotly.express as px
+import streamlit as st
+
+
+@st.cache
+def get_data():
+    # Download file from Google Drive
+    # This file is based on data from: http://insideairbnb.com/get-the-data/
+    file_id_1 = "1rsxDntx9CRSyDMy_fLHEI5Np4lB153sa"
+    downloaded_file_1 = "listings.pkl"
+    gdown.download(id=file_id_1, output=downloaded_file_1)
+
+    # Read a Python Pickle file
+    return pd.read_pickle("listings.pkl")
+
+
+df = get_data()
+
+
+st.title("The Airbnb dataset of Amsterdam")
+st.markdown(
+    "The dataset contains slight modifications with regards to the original for illustrative purposes"
+)
+st.dataframe(df.head(100))
+st.text("The dataset was retrieved using the following code:")
+st.code(
+    """
+@st.cache
+def get_data():
+    # Download file from Google Drive
+    # This file is based on data from: http://insideairbnb.com/get-the-data/
+    file_id_1 = "1f6o9IeaieH_xXyghjnREfl2dC44pIUc4"
+    downloaded_file_1 = "listings.pkl"
+    gdown.download(id=file_id_1, output=downloaded_file_1)
+    
+    # Read a Python Pickle file
+    return pd.read_pickle("listings.pkl")
+""",
+    language="python",
+)
+st.markdown(
+    "*Let's take a closer look at the supposed relation between **price_in_dollar** and **review_scores_rating**.*"
+)
+st.plotly_chart(
+    px.scatter(
+        df,
+        x="price_in_dollar",
+        y="review_scores_rating",
+        trendline="ols",
+        trendline_color_override="orange",
+    )
+)

requirements.txt

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+pandas
+streamlit
+plotly
+gdown
+statsmodels