{"action":"opened","issue":{"url":"https://api.github.com/repos/ikedaosushi/tech-news/issues/4085","repository_url":"https://api.github.com/repos/ikedaosushi/tech-news","labels_url":"https://api.github.com/repos/ikedaosushi/tech-news/issues/4085/labels{/name}","comments_url":"https://api.github.com/repos/ikedaosushi/tech-news/issues/4085/comments","events_url":"https://api.github.com/repos/ikedaosushi/tech-news/issues/4085/events","html_url":"https://github.com/ikedaosushi/tech-news/issues/4085","id":329715962,"node_id":"MDU6SXNzdWUzMjk3MTU5NjI=","number":4085,"title":"A Gentle Introduction to Data Visualization Methods in Python","user":{"login":"ikedaosushi","id":4068610,"node_id":"MDQ6VXNlcjQwNjg2MTA=","avatar_url":"https://avatars1.githubusercontent.com/u/4068610?v=4","gravatar_id":"","url":"https://api.github.com/users/ikedaosushi","html_url":"https://github.com/ikedaosushi","followers_url":"https://api.github.com/users/ikedaosushi/followers","following_url":"https://api.github.com/users/ikedaosushi/following{/other_user}","gists_url":"https://api.github.com/users/ikedaosushi/gists{/gist_id}","starred_url":"https://api.github.com/users/ikedaosushi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ikedaosushi/subscriptions","organizations_url":"https://api.github.com/users/ikedaosushi/orgs","repos_url":"https://api.github.com/users/ikedaosushi/repos","events_url":"https://api.github.com/users/ikedaosushi/events{/privacy}","received_events_url":"https://api.github.com/users/ikedaosushi/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-06-06T05:30:33Z","updated_at":"2018-06-06T05:30:33Z","closed_at":null,"author_association":"OWNER","body":"A Gentle Introduction to Data Visualization Methods in Python<br>\nSometimes data does not make sense until you can look at in a visual form, such as with charts and plots. Being able to quickly visualize your data samples for yourself and others is an important skill both in applied statistics and in applied machine learning.<br>\nhttps://ift.tt/2sA74bC"}}
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