Data visualization library "folium" by Python is very easy to use

This article is an article of Origami Advent Calendar

Overview

You may often hear that the method of Data Visualization by Python uses matplotlib or seaborn, but this time I would like to introduce a library called "folium".

folium is a library of data visualization using JavaScript OSS called leaflet, and has the advantage of many expressions using maps.

Therefore, if you want to output a bar graph, histogram, or scatter plot, it is better to use matplotlib or seaborn as appropriate, but for data with location information, folium is an option (affirmation).

Then, I will introduce what you can do with folium.

environment

- Mac OSX El Capitan(10.11.6)
- Python(3.5.1)
- jupyter lab(0.2.1)

Installation

$ pip install folium

Show map

First, let's display the map. In folium.Map, the options use location and zoom_start, but there are other tiles (change the appearance of the map), such as Stamen Toner and Stamen Terrain. ..

`folium-sample1.py`


import folium
m = folium.Map(location=[35.681382, 139.76608399999998], zoom_start=14) #Latitude and longitude of Tokyo station
m

Plot points on the map

First, paste the code.

`folium-sample2.py`


import folium

m = folium.Map(location=[35.681382, 139.76608399999998], zoom_start=12)

folium.Marker([35.658581, 139.745433], popup='Tokyo tower', icon=folium.Icon(color='blue')).add_to(m)
folium.Marker([35.710063, 139.8107], popup='Tokyo skytree', icon=folium.Icon(color='blue', icon='cloud')).add_to(m)

m

You can plot like a map by adding Maker to the map prepared earlier. Options are

-popup: leave a comment --color: Color the Maker --icon: Iconize Maker

Icon uses fontawesome and defaults to ʻinfo-sign` I have. Also, the default colors and the corresponding colors are listed here.

Plot circles on a map

You can draw a circle on the map by using CircleMarker. The unit of radius can be set to m, color or fil color.

`folium-sample3.py`


import folium

m = folium.Map(location=[35.681382, 139.76608399999998], zoom_start=12)

folium.Marker([35.658581, 139.745433], popup='Tokyo tower', icon=folium.Icon(color='blue')).add_to(m)
folium.Marker([35.710063, 139.8107], popup='Tokyo skytree', icon=folium.Icon(color='blue', icon='bookmark')).add_to(m)

folium.CircleMarker(
    location=[35.681382, 139.76608399999998],
    radius=2000,
    popup='Tokyo Station',
    color='#3186cc',
    fill_color='#3186cc'
).add_to(m)
m

Summary

Only a part of the functions are introduced here, but for example, it is easy to store the clustering result in pandas.Dataframe or numpy.array and display it on a map, so location information If you are doing data analysis related to, please use it. There are many examples in folium, so you can enjoy trying data visualization.