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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)

app.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)