Geocoded whole Japanese listed companies.

It just a beginning though, I made the csv and json files, where whole Japanese companies who listed on the first section of the Tokyo Stock Exchange are packed, with these geological coordinates. Since I couldn’t find even such a fundamental geological data aside from address-based location data, the dataset I made might benefit other people who devoting data visualization. I intend to use them later on, but I put it on here for now.

The data was originated in Tosho website, and retrieved by python’ library, scrapy and pygeocoder through the address data. Then Google refine and Google Fusion Tables for Joining the data.


Zip file containing the data and webscraping files:

Csv andJson files: Japanesecompany_coorinate.csv TSE1_japancompany_coordinate.json

The contents are like that:

1301,極洋,〒107-0052 東京都港区赤坂3−3−5,"(35.6747407, 139.7381582)"
1332,日本水産,〒100-8686 東京都千代田区大手町2−6−2,"(35.6853209, 139.7700388)"</pre>
<div id="file-tse1_japancompany_coordinate-json-LC1">{</div>
<div id="file-tse1_japancompany_coordinate-json-LC2">"geocompany" : [</div>
<div id="file-tse1_japancompany_coordinate-json-LC3">{</div>
<div id="file-tse1_japancompany_coordinate-json-LC4">"company" : "極洋",</div>
<div id="file-tse1_japancompany_coordinate-json-LC5">"latitude" : 35.6747407,</div>
<div id="file-tse1_japancompany_coordinate-json-LC6">"longitude" : 139.7381582,</div>
<div id="file-tse1_japancompany_coordinate-json-LC7">"code" : 1301,</div>
<div id="file-tse1_japancompany_coordinate-json-LC8">"place" : "〒107-0052 東京都港区赤坂3−3−5"</div>
<div id="file-tse1_japancompany_coordinate-json-LC9">},</div>
<div id="file-tse1_japancompany_coordinate-json-LC10">{</div>
<div id="file-tse1_japancompany_coordinate-json-LC11">"company" : "日本水産",</div>

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