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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) |