{"id":2081,"date":"2020-06-22T15:03:01","date_gmt":"2020-06-22T06:03:01","guid":{"rendered":"https:\/\/itips.krsw.biz\/?p=2081"},"modified":"2020-06-22T15:03:01","modified_gmt":"2020-06-22T06:03:01","slug":"pandas-dataframe-update-column-value","status":"publish","type":"post","link":"https:\/\/itips.krsw.biz\/en\/pandas-dataframe-update-column-value\/","title":{"rendered":"[Python] Update column value of Pandas DataFrame"},"content":{"rendered":"<p><img decoding=\"async\" src=\"https:\/\/itips.krsw.biz\/wp-content\/uploads\/2018\/12\/code_1545140786-1024x683.jpg\" alt=\"[Python] Update column value of Pandas DataFrame\" width=\"800\" height=\"534\" class=\"aligncenter size-large wp-image-139\" srcset=\"https:\/\/itips.krsw.biz\/wp-content\/uploads\/2018\/12\/code_1545140786-1024x683.jpg 1024w, https:\/\/itips.krsw.biz\/wp-content\/uploads\/2018\/12\/code_1545140786-640x427.jpg 640w, https:\/\/itips.krsw.biz\/wp-content\/uploads\/2018\/12\/code_1545140786-800x534.jpg 800w, https:\/\/itips.krsw.biz\/wp-content\/uploads\/2018\/12\/code_1545140786-320x214.jpg 320w, https:\/\/itips.krsw.biz\/wp-content\/uploads\/2018\/12\/code_1545140786-768x512.jpg 768w, https:\/\/itips.krsw.biz\/wp-content\/uploads\/2018\/12\/code_1545140786-400x267.jpg 400w, https:\/\/itips.krsw.biz\/wp-content\/uploads\/2018\/12\/code_1545140786-300x200.jpg 300w, https:\/\/itips.krsw.biz\/wp-content\/uploads\/2018\/12\/code_1545140786.jpg 1280w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><\/p>\n<p>There are some ways to update column value of Pandas DataFrame.<br \/>\nSo I wrote down them for the future reference.<br \/>\nI used documents of <code>loc<\/code> and <code>where<\/code> below as a reference.<\/p>\n<div class=\"st-mybox  has-title st-mybox-class\" style=\"background:#fafafa;border-width:0px;border-radius:5px;margin: 25px 0 25px 0;\"><p class=\"st-mybox-title\" style=\"color:#757575;font-weight:bold;text-shadow: #fff 3px 0px 0px, #fff 2.83487px 0.981584px 0px, #fff 2.35766px 1.85511px 0px, #fff 1.62091px 2.52441px 0px, #fff 0.705713px 2.91581px 0px, #fff -0.287171px 2.98622px 0px, #fff -1.24844px 2.72789px 0px, #fff -2.07227px 2.16926px 0px, #fff -2.66798px 1.37182px 0px, #fff -2.96998px 0.42336px 0px, #fff -2.94502px -0.571704px 0px, #fff -2.59586px -1.50383px 0px, #fff -1.96093px -2.27041px 0px, #fff -1.11013px -2.78704px 0px, #fff -0.137119px -2.99686px 0px, #fff 0.850987px -2.87677px 0px, #fff 1.74541px -2.43999px 0px, #fff 2.44769px -1.73459px 0px, #fff 2.88051px -0.838246px 0px;\"><i class=\"fa fa-file-text-o st-css-no\" aria-hidden=\"true\"><\/i>Reference<\/p><div class=\"st-in-mybox\">\n<li><a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.DataFrame.loc.html\">pandas.DataFrame.loc \u2014 pandas 1.0.5 documentation<\/a><\/li>\n<li><a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.DataFrame.where.html\">pandas.DataFrame.where \u2014 pandas 1.0.5 documentation<\/a><\/li>\n<\/div><\/div>\n<p><!--more--><\/p>\n<p><\/br><\/p>\n<h2>Update column value of Pandas DataFrame<\/h2>\n<p>There are some ways to update column value of Pandas DataFrame.<br \/>\nCommon ways are below.<\/p>\n<ul>\n<li>Bulk update by single value<\/li>\n<li>Update rows that match condition<\/li>\n<li>Update with another DataFrame<\/li>\n<\/ul>\n<p>I'll introduce them with using DataFrame sample.<\/p>\n<pre class=\"prettyprint lang-python\">\nimport pandas as pd\n\ndata_list1 = &#091;\n&#091;1,2,3&#093;,\n&#091;2,3,4&#093;,\n&#091;3,4,5&#093;\n&#093;\ncol_list1 = &#091;&#34;c1&#34;,&#34;c2&#34;,&#34;c3&#34;&#093;\ndf1 = pd.DataFrame(data=data_list1, columns=col_list1)\nprint(df1)\n\n#    c1  c2  c3\n# 0   1   2   3\n# 1   2   3   4\n# 2   3   4   5\n<\/pre>\n<p><\/br><\/br><\/br><\/p>\n<h3>Bulk update by single value<\/h3>\n<p>Bulk update is easy.<br \/>\nBut it updates all rows. So it is not so useful and we can use it only for initialization.<\/p>\n<pre class=\"prettyprint lang-python\">\ndf1&#091;&#34;c3&#34;&#093;=1\nprint(df1)\n#    c1  c2  c3\n# 0   1   2   1\n# 1   2   3   1\n# 2   3   4   1\n<\/pre>\n<p><\/br><\/br><\/br><\/p>\n<h3>Update rows that match condition<\/h3>\n<p>If you want to update specific rows that match condition, you can use <code>loc<\/code>.<\/p>\n<pre class=\"prettyprint lang-python\">\ndf1.loc&#091;df1&#091;&#34;c3&#34;&#093;&gt;3, &#091;&#34;c3&#34;&#093;&#093;=1\nprint(df1)\n#    c1  c2  c3\n# 0   1   2   3\n# 1   2   3   1\n# 2   3   4   1\n<\/pre>\n<p><\/br><\/br><\/br><\/p>\n<p>Without using <code>loc<\/code>, you will see warning and you will not update values.<\/p>\n<pre class=\"prettyprint lang-python\">\ndf1&#091;df1&#091;&#34;c3&#34;&#093;&gt;3&#093;&#091;&#34;c3&#34;&#093;=1\nprint(df1)\n# SettingWithCopyWarning: \n# A value is trying to be set on a copy of a slice from a DataFrame.\n# Try using .loc&#091;row_indexer,col_indexer&#093; = value instead\n#    c1  c2  c3\n# 0   1   2   3\n# 1   2   3   4\n# 2   3   4   5\n<\/pre>\n<p><\/br><\/p>\n<p>As an another method, we can update unmatched rows with using <code>where<\/code>.<br \/>\nIn the example below, it updates column &quot;c3&quot; values of rows that have less values than 4 in column &quot;c2&quot;.<\/p>\n<pre class=\"prettyprint lang-python\">\ndf1&#091;&#34;c3&#34;&#093;.where(df1&#091;&#34;c2&#34;&#093; &gt;= 4, 10, inplace=True)  # Update unmatched cells\nprint(df1)\n\n#    c1  c2    c3\n# 0   1   2  10.0\n# 1   2   3  10.0\n# 2   3   4   1.0\n<\/pre>\n<p><\/br><\/br><\/br><\/p>\n<h3>Update with another DataFrame<\/h3>\n<p>There is a way to update column with another DataFrame.<br \/>\nWith using this method, we can choose certail rows from parent DataFrame and apply updated values to parent DataFrame after the child process.<\/p>\n<pre class=\"prettyprint lang-python\">\ndata_list2 = &#091;\n&#091;5,7&#093;,\n&#091;6,8&#093;,\n&#093;\ncol_list2 = &#091;&#34;c4&#34;,&#34;c3&#34;&#093;\ndf2 = pd.DataFrame(data=data_list2, columns=col_list2)\nprint(df2)\n#    c4  c3\n# 0   5   7\n# 1   6   8\n\ndf1.update(df2)\nprint(df1)\n#    c1  c2   c3\n# 0   1   2  7.0\n# 1   2   3  8.0\n# 2   3   4  1.0\n<\/pre>\n","protected":false},"excerpt":{"rendered":"<p>There are some ways to update column value of Pandas DataFrame. So I wrote down them for the future  &#8230; <\/p>\n","protected":false},"author":1,"featured_media":139,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_locale":"en_US","_original_post":"https:\/\/itips.krsw.biz\/?p=2077","footnotes":""},"categories":[6],"tags":[35],"class_list":["post-2081","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","tag-pandas","en-US"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>[Python] Update column value of Pandas DataFrame - ITips\u30b7\u30b9\u30c6\u30e0\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u30ba<\/title>\n<meta name=\"description\" content=\"There are some ways to update column value of Pandas DataFrame.So I wrote down them for the future reference.I used documents of `loc` and `where` below as a reference.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/itips.krsw.biz\/en\/pandas-dataframe-update-column-value\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Python] Update column value of Pandas DataFrame - 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