Airbnb_Listings_WK1 / Week_1_project_visualization.py
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import pandas as pd
import plotly.express as px
import streamlit as st
# Display title and text
st.title("Week 1 - Data and visualization")
st.markdown("Here we can see the dataframe we've created during this weeks project.")
# Read dataframe
dataframe = pd.read_csv(
"WK1_Airbnb_Amsterdam_listings_proj_solution.csv",
names=[
"Airbnb Listing ID",
"Price",
"Latitude",
"Longitude",
"Meters from chosen location",
"Location",
],
)
# We have a limited budget, therefore we would like to exclude
# listings with a price above 100 pounds per night
dataframe = dataframe[dataframe["Price"] <= 100]
# Display as integer
dataframe["Airbnb Listing ID"] = dataframe["Airbnb Listing ID"].astype(int)
# Round of values
dataframe["Price"] = "£ " + dataframe["Price"].round(2).astype(str)
# Rename the number to a string
dataframe["Location"] = dataframe["Location"].replace(
{1.0: "To visit", 0.0: "Airbnb listing"}
)
# Display dataframe and text
st.dataframe(dataframe)
st.markdown("Below is a map showing all the Airbnb listings with a red dot and the location we've chosen with a blue dot.")
# Create the plotly express figure
fig = px.scatter_mapbox(
lat=dataframe["Latitude"],
lon=dataframe["Longitude"],
color=dataframe["Location"],
zoom=11,
height=500,
width=800,
hover_name=dataframe["Price"],
labels={"color": "Locations"},
)
fig.update_geos(center=dict(lat=dataframe.iloc[0][2], lon=dataframe.iloc[0][3]))
fig.update_layout(mapbox_style="stamen-terrain")
# Show the figure
st.plotly_chart(fig, use_container_width=True)