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e633983
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  1. app.py +57 -0
  2. requirements.txt +5 -0
app.py ADDED
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+ import os
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+ import shutil
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+
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+ import gdown
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+ import pandas as pd
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+ import plotly.express as px
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+ import streamlit as st
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+
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+
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+ @st.cache
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+ def get_data():
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+ # Download file from Google Drive
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+ # This file is based on data from: http://insideairbnb.com/get-the-data/
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+ file_id_1 = "1rsxDntx9CRSyDMy_fLHEI5Np4lB153sa"
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+ downloaded_file_1 = "listings.pkl"
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+ gdown.download(id=file_id_1, output=downloaded_file_1)
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+
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+ # Read a Python Pickle file
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+ return pd.read_pickle("listings.pkl")
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+
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+
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+ df = get_data()
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+
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+
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+ st.title("The Airbnb dataset of Amsterdam")
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+ st.markdown(
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+ "The dataset contains slight modifications with regards to the original for illustrative purposes"
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+ )
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+ st.dataframe(df.head(100))
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+ st.text("The dataset was retrieved using the following code:")
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+ st.code(
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+ """
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+ @st.cache
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+ def get_data():
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+ # Download file from Google Drive
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+ # This file is based on data from: http://insideairbnb.com/get-the-data/
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+ file_id_1 = "1f6o9IeaieH_xXyghjnREfl2dC44pIUc4"
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+ downloaded_file_1 = "listings.pkl"
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+ gdown.download(id=file_id_1, output=downloaded_file_1)
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+
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+ # Read a Python Pickle file
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+ return pd.read_pickle("listings.pkl")
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+ """,
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+ language="python",
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+ )
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+ st.markdown(
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+ "*Let's take a closer look at the supposed relation between **price_in_dollar** and **review_scores_rating**.*"
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+ )
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+ st.plotly_chart(
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+ px.scatter(
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+ df,
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+ x="price_in_dollar",
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+ y="review_scores_rating",
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+ trendline="ols",
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+ trendline_color_override="orange",
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+ )
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+ )
requirements.txt ADDED
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+ pandas
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+ streamlit
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+ plotly
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+ gdown
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+ statsmodels