Interactive Maps with Python

In this article, I will explain how to create interactive maps with the folium package in python. Along the way, you will also learn how to apply your new skills to visualize Boston criminal data.

To get started with the task of creating interactive maps with python, I will start with importing all the necessary libraries we need for this task:

Also, Read – Random Sampling with Python.

import pandas as pd
import geopandas as gpd
import math
import folium
from folium import Choropleth, Circle, Marker
from folium.plugins import HeatMap, MarkerClusterCode language: JavaScript (javascript)

Working with interactive maps

I’ll start by creating a relatively simple map with the folium.Map() method:

# Create a map
m_1 = folium.Map(location=[42.32,-71.0589], tiles='openstreetmap', zoom_start=10)

# Display the map
m_1Code language: PHP (php)

Several arguments customize the appearance of the map:

• the location defines the initial centre of the map. We use the latitude (42.32 ° N) and longitude (-71.0589 ° E) of the city of Boston.
• the tiles change the style of the map; in this case, we choose the OpenStreetMap style. If you are curious, you can find the other options listed here.
• the zoom_start sets the default zoom of the map, where higher values will ​​zoom closer to the map.

Now take the time to explore by zooming in and out, or dragging the map in different directions.

Working on Data

Now I will add crime data to the map. I won’t focus on the data loading step. Instead, you can imagine that you are at a point where you already have the data in a DataFrame pandas offence. Now let’s have a look at the first 5 rows from the data:

# Load the data
crimes = pd.read_csv("crime.csv", encoding='latin-1')

# Drop rows with missing locations
crimes.dropna(subset=['Lat', 'Long', 'DISTRICT'], inplace=True)

# Focus on major crimes in 2018
crimes = crimes[crimes.OFFENSE_CODE_GROUP.isin([
    'Larceny', 'Auto Theft', 'Robbery', 'Larceny From Motor Vehicle', 'Residential Burglary',
    'Simple Assault', 'Harassment', 'Ballistics', 'Aggravated Assault', 'Other Burglary', 
    'Arson', 'Commercial Burglary', 'HOME INVASION', 'Homicide', 'Criminal Harassment', 
    'Manslaughter'])]
crimes = crimes[crimes.YEAR>=2018]

# Print the first five rows of the table
crimes.head()
Code language: PHP (php)

To reduce the amount of data we need to fit on the map, we’ll limit our attention to daytime flights:

daytime_robberies = crimes[((crimes.OFFENSE_CODE_GROUP == 'Robbery') & \
                            (crimes.HOUR.isin(range(9,18))))]Code language: HTML, XML (xml)

Now we need to add markers to the map with folium.Marker(). Each marker below corresponds to a different flight:

# Create a map
m_2 = folium.Map(location=[42.32,-71.0589], tiles='cartodbpositron', zoom_start=13)

# Add points to the map
for idx, row in daytime_robberies.iterrows():
    Marker([row['Lat'], row['Long']]).add_to(m_2)

# Display the map
m_2
Code language: PHP (php)

What if we have a lot of markers to add? We need to use folium.plugins.MarkerCluster() that can help declutter the map. Each marker is added to a MarkerCluster object:

# Create the map
m_3 = folium.Map(location=[42.32,-71.0589], tiles='cartodbpositron', zoom_start=13)

# Add points to the map
mc = MarkerCluster()
for idx, row in daytime_robberies.iterrows():
    if not math.isnan(row['Long']) and not math.isnan(row['Lat']):
        mc.add_child(Marker([row['Lat'], row['Long']]))
m_3.add_child(mc)

# Display the map
m_3Code language: PHP (php)

Also, Read – Natural Language Processing for Other Languages.

I hope you liked this article on creating Interactive Maps with Python. Feel free to ask your valuable questions in the comments section below. You can also follow me on Medium to learn every topic of Machine Learning and Python.

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