{"published":"2026-06-20 16:45:09","blog_url":"https://www.crosshyou.info/","type":"rich","author_name":"cross_hyou","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/c/cross_hyou/20260620/20260620161643.jpg","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fwww.crosshyou.info%2Fentry%2F2026%2F06%2F20%2F164509\" title=\"IEA Gender and Energy Employment Data Analysis 3 - Making graphs to explore data analysis - 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>","provider_url":"https://hatena.blog","author_url":"https://blog.hatena.ne.jp/cross_hyou/","version":"1.0","title":"IEA Gender and Energy Employment Data Analysis 3 - Making graphs to explore data analysis","provider_name":"Hatena Blog","url":"https://www.crosshyou.info/entry/2026/06/20/164509","description":"www.crosshyou.info This post is continueation of above post. In this post, let's examine gender gap data by year, by sector and so on. Before makinga graphs, I renamed \"value\" to \"gap\". Let's start with Year. We see there is not large differences by Year. Next, let's see by sector. We see there is n\u2026","width":"100%","height":"190","categories":["Data_Analysis","\u30c7\u30fc\u30bf\u5206\u6790"],"blog_title":"R\u3067\u4f55\u304b\u3092\u3057\u305f\u308a\u3001\u8aad\u66f8\u3092\u3059\u308b\u30d6\u30ed\u30b0"}