I tried using folium

Introduction

Recently, I tried using folium, a library that displays data on a map, so I summarized it in an article while studying.

What is folium

Folium is a python library that visualizes data with a map of Leaflet.js.

You can take advantage of both python data manipulation and leaflet mapping.

Github:https://github.com/python-visualization/folium Documentation:https://python-visualization.github.io/folium/

Installation

You can install it with pip install.

`folium installation`


$ pip install folium

Let's display the map!

First, use jupyter to display a map of Japan centered on Tokyo Station ([35.681167, 139.767052]). If you enter latitude and longitude in location, you can display a map centered on that position.

`Plot a map of Japan centered around Tokyo Station`


import folium
map_ = folium.Map(location=[35.681167, 139.767052], zoom_start=7)
map_

The map could be displayed with only 3 lines.

Next, let's map the location information of the department store to the created map of Japan. I searched the location information of the department store on HP and saved it as a csv file.

The csv file is saved in this format. (department_info.csv)

	store_name	contry	area	prefecture	city	address	latitude	longitude	depart
0	Nihombashi Mitsukoshi Main Store	Japan	Kanto	Tokyo	Chuo-ku	1 Nihonbashi Muromachi, Chuo-ku, Tokyo-4-1	35.685633	139.773430	Mitsukoshi
1	Ginza Mitsukoshi	Japan	Kanto	Tokyo	Chuo-ku	4 Ginza, Chuo-ku, Tokyo-6-16	35.671370	139.765738	Mitsukoshi
・・・
88	ShinQs Beauty Palette Machida	Japan	Kanto	Tokyo	Machida City	6 Haramachida, Machida-shi, Tokyo-4-1 Machida Tokyu Twins WEST 3F	35.542690	139.446409	Tokyu Department Store
89	Nagano Tokyu Department Store	Japan	Chubu	Nagano Prefecture	Nagano city	1 Minamichitose, Nagano City, Nagano Prefecture-1-1	36.645052	138.188676	Tokyu Department Store

`Add a department store marker to the map you just displayed`


import pandas as pd
data = pd.read_csv('department_info.csv')
color_list = {'Mitsukoshi':'red', 'Daimaru':'blue', 'Seibu / Sogo':'green', 
              'Takashimaya':'purple', 'Hankyu Hanshin':'orange', 'Tokyu Department Store':'darkred'}
for k, v in data.iterrows():
    folium.Marker([v.latitude, v.longitude], popup=v.store_name, icon=folium.Icon(color=color_list[v.depart])).add_to(map_)    

map_

popup=xxx If you add a comment to xxx, it can be displayed as a pop-up.
icon=folium.Icon(color=xxx1, icon=xxx2) The marker icon type can be changed by specifying xxx1 and xxx2.

Colors that can be used for xxx1

[‘red’, ‘blue’, ‘green’, ‘purple’, ‘orange’, ‘darkred’,
’lightred’, ‘beige’, ‘darkblue’, ‘darkgreen’, ‘cadetblue’, 
‘darkpurple’, ‘white’, ‘pink’, ‘lightblue’, ‘lightgreen’, 
‘gray’, ‘black’, ‘lightgray’]

Markers that can be used for xxx2 https://glyphsearch.com/?library=font-awesome

Next, let's display a circle with a radius of 20km for each displayed department store.

`20km area from the department store is displayed in yen`


for k, v in data.iterrows():
  folium.Circle([v.latitude, v.longitude], radius=20 * 1000, tooltip='20km', popup=v.store_name
                              , color=color_list[v.depart], fill_color=None).add_to(map_)

map_

I saved the last created map in html format.

`Save the created map`


map_.save('department_location.html')

in conclusion

I was able to visualize a beautiful map more easily than I expected.

(Reposted due to account migration)