latitudinal and longitudinal coordinates in the city. To show pickup
concentration, let's use Streamlit st.map()
function to overlay the data on a map of New York City.
Add a subheader for the section:
python
   st.subheader('Map of all pickups')
Use the st.map() function to plot the data:
python
   st.map(data)
Save your script. The map is fully interactive. Give it a try by panning or
   zooming in a bit.
After drawing your histogram, you determined that the busiest hour for Uber
pickups was 17:00. Let's redraw the map to show the concentration of pickups
at 17:00.
Locate the following code snippet:
python
   st.subheader('Map of all pickups')
   st.map(data)
Replace it with:
python
   hour_to_filter = 17
   filtered_data = data[data[DATE_COLUMN].dt.hour == hour_to_filter]
   st.subheader(f'Map of all pickups at {hour_to_filter}:00')
