{"blog_title":"R\u3067\u4f55\u304b\u3092\u3057\u305f\u308a\u3001\u8aad\u66f8\u3092\u3059\u308b\u30d6\u30ed\u30b0","provider_url":"https://hatena.blog","published":"2022-06-12 08:43:49","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/c/cross_hyou/20220612/20220612080648.jpg","type":"rich","title":"OECD Young self-employed data analysis 4 - data visualization again and combining GDP data.","author_name":"cross_hyou","height":"190","provider_name":"Hatena Blog","url":"https://www.crosshyou.info/entry/2022/06/12/084349","description":"Photo by Fatih Y\u00fcr\u00fcr on Unsplash www.crosshyou.info This post is following of above post. In the previous post, I made a new data frame, df_new, which has mem variable and women variable. Let's visualize those data. Firstly, men data by LOCATION JPN has the lowest and ZAF has the highest. Next, wome\u2026","width":"100%","author_url":"https://blog.hatena.ne.jp/cross_hyou/","blog_url":"https://www.crosshyou.info/","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fwww.crosshyou.info%2Fentry%2F2022%2F06%2F12%2F084349\" title=\"OECD Young self-employed data analysis 4 - data visualization again and combining GDP data. - R\u3067\u4f55\u304b\u3092\u3057\u305f\u308a\u3001\u8aad\u66f8\u3092\u3059\u308b\u30d6\u30ed\u30b0\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","categories":["Data_Analysis"],"version":"1.0"}