{"id":5268,"date":"2021-12-19T14:36:12","date_gmt":"2021-12-19T05:36:12","guid":{"rendered":"https:\/\/itips.krsw.biz\/?p=5268"},"modified":"2021-12-19T17:52:43","modified_gmt":"2021-12-19T08:52:43","slug":"pandas-dataframe-how-to-find-and-drop-duplicated-row","status":"publish","type":"post","link":"https:\/\/itips.krsw.biz\/en\/pandas-dataframe-how-to-find-and-drop-duplicated-row\/","title":{"rendered":"How to handle duplicated rows in pandas.DataFrame"},"content":{"rendered":"

\"How<\/p>\n

<\/div><\/div>
There may be duplicated rows in pandas DataFrame. I'd like to find and delete them.<\/div><\/div><\/div>\n

<\/br><\/p>\n

pandas.DataFrame<\/code> is useful to handle table format data.<\/p>\n

Sometimes DataFrame has duplicated data.<\/p>\n

In some cases, duplicated data is useless.<\/span> So we would like to find and delete them.<\/p>\n

But how can we find duplicated rows ?<\/p>\n

So today I will introduce "How to handle duplicated rows in pandas.DataFrame<\/span>"<\/strong>.<\/p>\n

<\/i>Author<\/p>


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<\/div><\/div>
Mid-carieer engineer (AI, system). Good at Python and SQL.<\/div><\/div><\/div>
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<\/span>Advantage to read<\/span><\/p><\/div>\n

<\/i><\/div>

You can understand \"How to handle duplicated rows in pandas.DataFrame\". After that you will be good at data handling.<\/span><\/p><\/div><\/div>\n

<\/p>\n

<\/br><\/p>\n

How to handle duplicated rows in pandas.DataFrame<\/h2>\n

\"\"<\/p>\n

So how can we handle duplicated rows in pandas.DataFrame ?<\/p>\n

There are mothods like following.<\/p>\n

Handle duplication<\/span><\/p>

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