{"id":14123,"date":"2022-10-06T14:35:43","date_gmt":"2022-10-06T09:05:43","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-how-to-separate-the-contents-of-parentheses-and-make-a-new-dataframe-column-closed\/"},"modified":"2022-10-06T14:35:43","modified_gmt":"2022-10-06T09:05:43","slug":"solved-how-to-separate-the-contents-of-parentheses-and-make-a-new-dataframe-column-closed","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-how-to-separate-the-contents-of-parentheses-and-make-a-new-dataframe-column-closed\/","title":{"rendered":"[Solved] How to separate the contents of parentheses and make a new dataframe column? [closed]"},"content":{"rendered":"<p> [ad_1]<br \/>\n<\/p>\n<div id=\"answer-68307462\" class=\"answer js-answer accepted-answer js-accepted-answer\" data-answerid=\"68307462\" data-parentid=\"68307284\" data-score=\"0\" data-position-on-page=\"1\" data-highest-scored=\"1\" data-question-has-accepted-highest-score=\"1\" itemprop=\"acceptedAnswer\" itemscope itemtype=\"https:\/\/schema.org\/Answer\">\n<div class=\"post-layout\">\n<div class=\"votecell post-layout--left\"><\/div>\n<div class=\"answercell post-layout--right\">\n<div class=\"s-prose js-post-body\" itemprop=\"text\">\n<p>Seems like <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.Series.str.extract.html\"><code>str.extract<\/code><\/a> would work assuming the seat number is the numeric characters before <code>\u5e2d<\/code> and the seat arrangement is the values inside the parenthesis:<\/p>\n<pre><code>import numpy as np\nimport pandas as pd\n\ndf = pd.DataFrame({\n    'seat': ['45\u5e2d\uff081\u968e\u30ab\u30a6\u30f3\u30bf\u30fc4\u5e2d\u3001\uff16\u301c\uff18\u4eba\u30c6\u30fc\u30d6\u30eb\uff11\u5e2d2\u968e\u5730\u4e0b\u305d\u308c\u305e\u308c\u6700\u592720\u4eba\uff09',\n             np.nan,\n             np.nan,\n             np.nan,\n             '9\u5e2d\uff08\u30ab\u30a6\u30f3\u30bf\u30fc9\u5e2d\u3001\u500b\u5ba44\u5e2d\uff09']\n})\n<\/code><\/pre>\n<pre><code>new_df = df['seat'].str.extract(r'(\\d+)\u5e2d\uff08(.*)\uff09', expand=True)\nnew_df.columns = ['seat number', 'seat arrangement']\n<\/code><\/pre>\n<p><code>new_df<\/code>:<\/p>\n<pre><code>  seat number                   seat arrangement\n0          45  1\u968e\u30ab\u30a6\u30f3\u30bf\u30fc4\u5e2d\u3001\uff16\u301c\uff18\u4eba\u30c6\u30fc\u30d6\u30eb\uff11\u5e2d2\u968e\u5730\u4e0b\u305d\u308c\u305e\u308c\u6700\u592720\u4eba\n1         NaN                                NaN\n2         NaN                                NaN\n3         NaN                                NaN\n4           9                       \u30ab\u30a6\u30f3\u30bf\u30fc9\u5e2d\u3001\u500b\u5ba44\u5e2d\n<\/code><\/pre>\n<\/p><\/div>\n<div class=\"mt24\"><\/div>\n<\/div>\n<p>            <span class=\"d-none\" itemprop=\"commentCount\"><\/span> <\/p><\/div>\n<\/div>\n<p>[ad_2]<\/p>\n<p>solved How to separate the contents of parentheses and make a new dataframe column? [closed] <\/p>\n","protected":false},"excerpt":{"rendered":"<p>[ad_1] Seems like str.extract would work assuming the seat number is the numeric characters before \u5e2d and the seat arrangement is the values inside the parenthesis: import numpy as np import pandas as pd df = pd.DataFrame({ &#8216;seat&#8217;: [&#8217;45\u5e2d\uff081\u968e\u30ab\u30a6\u30f3\u30bf\u30fc4\u5e2d\u3001\uff16\u301c\uff18\u4eba\u30c6\u30fc\u30d6\u30eb\uff11\u5e2d2\u968e\u5730\u4e0b\u305d\u308c\u305e\u308c\u6700\u592720\u4eba\uff09&#8217;, np.nan, np.nan, np.nan, &#8216;9\u5e2d\uff08\u30ab\u30a6\u30f3\u30bf\u30fc9\u5e2d\u3001\u500b\u5ba44\u5e2d\uff09&#8217;] }) new_df = df[&#8216;seat&#8217;].str.extract(r'(\\d+)\u5e2d\uff08(.*)\uff09&#8217;, expand=True) new_df.columns = [&#8216;seat number&#8217;, &#8216;seat arrangement&#8217;] new_df: &#8230; <a title=\"[Solved] How to separate the contents of parentheses and make a new dataframe column? [closed]\" class=\"read-more\" href=\"https:\/\/jassweb.com\/solved\/solved-how-to-separate-the-contents-of-parentheses-and-make-a-new-dataframe-column-closed\/\" aria-label=\"More on [Solved] How to separate the contents of parentheses and make a new dataframe column? [closed]\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[320],"tags":[415,349,347],"class_list":["post-14123","post","type-post","status-publish","format-standard","hentry","category-solved","tag-pandas","tag-python","tag-regex"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>[Solved] How to separate the contents of parentheses and make a new dataframe column? [closed] - JassWeb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jassweb.com\/solved\/solved-how-to-separate-the-contents-of-parentheses-and-make-a-new-dataframe-column-closed\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Solved] How to separate the contents of parentheses and make a new dataframe column? [closed] - JassWeb\" \/>\n<meta property=\"og:description\" content=\"[ad_1] Seems like str.extract would work assuming the seat number is the numeric characters before \u5e2d and the seat arrangement is the values inside the parenthesis: import numpy as np import pandas as pd df = pd.DataFrame({ &#039;seat&#039;: [&#039;45\u5e2d\uff081\u968e\u30ab\u30a6\u30f3\u30bf\u30fc4\u5e2d\u3001\uff16\u301c\uff18\u4eba\u30c6\u30fc\u30d6\u30eb\uff11\u5e2d2\u968e\u5730\u4e0b\u305d\u308c\u305e\u308c\u6700\u592720\u4eba\uff09&#039;, np.nan, np.nan, np.nan, &#039;9\u5e2d\uff08\u30ab\u30a6\u30f3\u30bf\u30fc9\u5e2d\u3001\u500b\u5ba44\u5e2d\uff09&#039;] }) new_df = df[&#039;seat&#039;].str.extract(r&#039;(d+)\u5e2d\uff08(.*)\uff09&#039;, expand=True) new_df.columns = [&#039;seat number&#039;, &#039;seat arrangement&#039;] new_df: ... 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[closed] - JassWeb","og_description":"[ad_1] Seems like str.extract would work assuming the seat number is the numeric characters before \u5e2d and the seat arrangement is the values inside the parenthesis: import numpy as np import pandas as pd df = pd.DataFrame({ 'seat': ['45\u5e2d\uff081\u968e\u30ab\u30a6\u30f3\u30bf\u30fc4\u5e2d\u3001\uff16\u301c\uff18\u4eba\u30c6\u30fc\u30d6\u30eb\uff11\u5e2d2\u968e\u5730\u4e0b\u305d\u308c\u305e\u308c\u6700\u592720\u4eba\uff09', np.nan, np.nan, np.nan, '9\u5e2d\uff08\u30ab\u30a6\u30f3\u30bf\u30fc9\u5e2d\u3001\u500b\u5ba44\u5e2d\uff09'] }) new_df = df['seat'].str.extract(r'(d+)\u5e2d\uff08(.*)\uff09', expand=True) new_df.columns = ['seat number', 'seat arrangement'] new_df: ... 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