{"id":8588,"date":"2021-06-12T10:54:42","date_gmt":"2021-06-12T05:24:42","guid":{"rendered":"https:\/\/python-programs.com\/?p=8588"},"modified":"2021-11-22T18:40:40","modified_gmt":"2021-11-22T13:10:40","slug":"convert-pandas-dataframe-column-into-an-index-using-set_index-in-python","status":"publish","type":"post","link":"https:\/\/python-programs.com\/convert-pandas-dataframe-column-into-an-index-using-set_index-in-python\/","title":{"rendered":"Pandas : Convert Dataframe column into an index using set_index() in Python"},"content":{"rendered":"<h2>Converting Dataframe column into an index using set_index() in Python<\/h2>\n<p>In this article we will learn to convert an existing column of Dataframe to a index including various cases. We can implement this using <code>set_index()<\/code> function of Pandas Dataframe class.<\/p>\n<ul>\n<li><a href=\"#Convert_a_column_of_Dataframe_into_an_index_of_the_Dataframe\">Convert a column of Dataframe into an index of the Dataframe<\/a><\/li>\n<li><a href=\"#Convert_a_column_of_Dataframe_into_index_without_deleting_the_column\">Convert a column of Dataframe into index without deleting the column<\/a><\/li>\n<li><a href=\"#Append_a_Dataframe_column_of_into_index_to_make_it_Multi-Index_Dataframe\">Append a Dataframe column of into index to make it Multi-Index Dataframe<\/a><\/li>\n<li><a href=\"#Check_for_duplicates_in_the_new_index\">Check for duplicates in the new index<\/a><\/li>\n<li><a href=\"#Modify_existing_Dataframe_by_converting_into_index\">Modify existing Dataframe by converting into index<\/a><\/li>\n<\/ul>\n<h3>DataFrame.set_index() :<\/h3>\n<pre>Syntax:- DataFrame.set_index(self, keys, drop=True, append=False, inplace=False, verify_integrity=False)<\/pre>\n<p><strong>Arguments:<\/strong><\/p>\n<ul>\n<li><strong>Keys:<\/strong> Column names that we want to set as an index of dataframe.<\/li>\n<li><strong>drop:<\/strong> (bool), default is True<\/li>\n<\/ul>\n<ol>\n<li>Where found True, after converting as an index column is deleted<\/li>\n<li>Where found False, then column is not deleted<\/li>\n<\/ol>\n<ul>\n<li><strong>append:<\/strong> (bool), default is False (If passed as True, then adds the given column is added to the existing index, and if passed as False, then current Index is replaced with it.)<\/li>\n<li><strong>inplace:<\/strong> (bool), in default is False (If passed as True then makes changes in the calling dataframe object otherwise if it is False, then returns a copy of modified dataframe.)<\/li>\n<\/ul>\n<ul>\n<li><strong>verify_integrity:<\/strong> (bool), default is False<\/li>\n<\/ul>\n<ol>\n<li>If True, searches for duplicate entries in new index.<\/li>\n<\/ol>\n<ul>\n<li>Dataframe has a default index and we can give a name e.g. SL<\/li>\n<\/ul>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as sc\r\n# List of Tuples\r\nplayers = [('Smith', 15, 'Pune', 170000),\r\n            ('Rana', 99, 'Mumbai', 118560),\r\n            ('Jaydev', 51, 'Kolkata', 258741),\r\n            ('Shikhar', 31, 'Hyderabad', 485169),\r\n            ('Sanju', 12, 'Rajasthan', 150000),\r\n            ('Raina', 35, 'Gujarat', 250000)\r\n            ]\r\n# Creation of DataFrame object\r\nplayDFObj = sc.DataFrame(players, columns=['Name', 'JerseyN', 'Team', 'Salary'])\r\n# Renaming index of dataframe as 'SL'\r\nplayDFObj.index.rename('SL', inplace=True)\r\nprint('Original Dataframe: ')\r\nprint(playDFObj)\r\n<\/pre>\n<pre>Output :\r\nOriginal Dataframe: \r\nName JerseyN Team Salary\r\nSL \r\n0 Smith 15 Pune 170000\r\n1 Rana 99 Mumbai 118560\r\n2 Jaydev 51 Kolkata 258741\r\n3 Shikhar 31 Hyderabad 485169\r\n4 Sanju 12 Rajasthan 150000\r\n5 Raina 35 Gujarat 250000<\/pre>\n<h3><a id=\"Convert_a_column_of_Dataframe_into_an_index_of_the_Dataframe\"><\/a>Converting a column of Dataframe into an index of the Dataframe :<\/h3>\n<p>Let&#8217;s try to convert of column <em>Name <\/em>into index of dataframe. We can implement this by passing that column name into <code>set_index<\/code>. Here the column names would be converted to &#8216;Name&#8217; deleting old index.<\/p>\n<p>Here it only it changes is made in the copy of dataframe without modifying original dataframe.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as sc\r\n# List of Tuples\r\nplayers = [('Smith', 15, 'Pune', 170000),\r\n            ('Rana', 99, 'Mumbai', 118560),\r\n            ('Jaydev', 51, 'Kolkata', 258741),\r\n            ('Shikhar', 31, 'Hyderabad', 485169),\r\n            ('Sanju', 12, 'Rajasthan', 150000),\r\n            ('Raina', 35, 'Gujarat', 250000)\r\n            ]\r\n# Creation DataFrame object\r\nplayDFObj = sc.DataFrame(players, columns=['Name', 'JerseyN', 'Team', 'Salary'])\r\n# Renaming index of dataframe as 'SL'\r\nplayDFObj.index.rename('SL', inplace=True)\r\nprint('Original Dataframe: ')\r\nprint(playDFObj)\r\n# set column 'Name' as the index of the Dataframe\r\nmodifplayDF = playDFObj.set_index('Name')\r\nprint('Modified Dataframe of players:')\r\nprint(modifplayDF)\r\n<\/pre>\n<pre>Output :\r\nOriginal Dataframe: \r\nName JerseyN Team Salary\r\nSL \r\n0 Smith\u00a0 \u00a015  Pune            170000\r\n1 Rana\u00a0 \u00a0 \u00a099  Mumbai      118560\r\n2 Jaydev\u00a0 51  Kolkata        258741\r\n3 Shikhar 31  Hyderabad 485169\r\n4 Sanju\u00a0 \u00a0 12  Rajasthan   150000\r\n5 Raina\u00a0 \u00a0 35  Gujarat       250000\r\n\r\nModified Dataframe of players:\r\nJerseyN Team Salary\r\nName \r\nSmith\u00a0 \u00a0 15 Pune           170000\r\nRana\u00a0 \u00a0 \u00a099 Mumbai      118560\r\nJaydev\u00a0 51 Kolkata        258741\r\nShikhar 31 Hyderabad  485169\r\nSanju\u00a0 \u00a0 12 Rajasthan    150000\r\nRaina\u00a0 \u00a0 35 Gujarat        250000<\/pre>\n<h3><a id=\"Convert_a_column_of_Dataframe_into_index_without_deleting_the_column\"><\/a>Converting a column of Dataframe into index without deleting the column :<\/h3>\n<p>In this case we will try to keep the column name and also index as &#8216;Name&#8217; by passing drop argument as false.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as sc\r\n# List of Tuples\r\nplayers = [('Smith', 15, 'Pune', 170000),\r\n            ('Rana', 99, 'Mumbai', 118560),\r\n            ('Jaydev', 51, 'Kolkata', 258741),\r\n            ('Shikhar', 31, 'Hyderabad', 485169),\r\n            ('Sanju', 12, 'Rajasthan', 150000),\r\n            ('Raina', 35, 'Gujarat', 250000)\r\n            ]\r\n# Creation of DataFrame object\r\nplayDFObj = sc.DataFrame(players, columns=['Name', 'JerseyN', 'Team', 'Salary'])\r\nplayDFObj.index.rename('ID', inplace=True)\r\n# keep column name and index as 'Name'\r\nmodifplayDF = playDFObj.set_index('Name', drop=False)\r\nprint('Modified Dataframe of players:')\r\nprint(modifplayDF)\r\n<\/pre>\n<pre>Output :\r\nModified Dataframe of players:\r\nName\u00a0 JerseyN\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Team\u00a0 Salary\r\nName\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \r\nSmith\u00a0\u00a0\u00a0\u00a0\u00a0 Smith\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 15\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Pune\u00a0 170000\r\nRana\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Rana\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 99\u00a0\u00a0\u00a0\u00a0 Mumbai\u00a0 118560\r\nJaydev\u00a0\u00a0\u00a0 Jaydev\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 51\u00a0\u00a0\u00a0 Kolkata\u00a0 258741\r\nShikhar\u00a0 Shikhar\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 31\u00a0 Hyderabad\u00a0 485169\r\nSanju\u00a0\u00a0\u00a0\u00a0\u00a0 Sanju\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 12\u00a0 Rajasthan\u00a0 150000\r\nRaina\u00a0\u00a0\u00a0\u00a0\u00a0 Raina\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 35\u00a0\u00a0\u00a0 Gujarat\u00a0 250000<\/pre>\n<h3><a id=\"Append_a_Dataframe_column_of_into_index_to_make_it_Multi-Index_Dataframe\"><\/a>Appending a Dataframe column of into index to make it Multi-Index Dataframe :<\/h3>\n<p>In above cases the index &#8216;SL&#8217; is replaced. If we want to keep it we have to pass append argument as True.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as sc\r\n# List of Tuples\r\nplayers = [('Smith', 15, 'Pune', 170000),\r\n            ('Rana', 99, 'Mumbai', 118560),\r\n            ('Jaydev', 51, 'Kolkata', 258741),\r\n            ('Shikhar', 31, 'Hyderabad', 485169),\r\n            ('Sanju', 12, 'Rajasthan', 150000),\r\n            ('Raina', 35, 'Gujarat', 250000)\r\n            ]\r\n# Creation DataFrame object\r\nplayDFObj = sc.DataFrame(players, columns=['Name', 'JerseyN', 'Team', 'Salary'])\r\nplayDFObj.index.rename('SL', inplace=True)\r\n# Making a mulit-index dataframe\r\nmodifplayDF = playDFObj.set_index('Name', append=True)\r\nprint('Modified Dataframe of players:')\r\nprint(modifplayDF)\r\n<\/pre>\n<pre>Output :\r\nModified Dataframe of players:\r\nJerseyN\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Team\u00a0 Salary\r\nSL Name\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \r\n0\u00a0 Smith\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 15\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Pune\u00a0 170000\r\n1\u00a0 Rana\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 99\u00a0\u00a0\u00a0\u00a0 Mumbai\u00a0 118560\r\n2\u00a0 Jaydev\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 51\u00a0\u00a0\u00a0 Kolkata\u00a0 258741\r\n3\u00a0 Shikhar\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 31 \u00a0Hyderabad\u00a0 485169\r\n4\u00a0 Sanju\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 12\u00a0 Rajasthan\u00a0 150000\r\n5\u00a0 Raina\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 35\u00a0\u00a0\u00a0 Gujarat\u00a0 250000<\/pre>\n<h3><a id=\"Check_for_duplicates_in_the_new_index\"><\/a>Checking for duplicates in the new index :<\/h3>\n<p>If we wanted to check index doesn&#8217;t contain any duplicate values after converting a column to the index by passing <code>verify_integrity<\/code> as True in <code>set_index(<\/code>). If any duplicate value found error will be raised.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as sc\r\n# List of Tuples\r\nplayers = [('Smith', 15, 'Pune', 170000),\r\n            ('Rana', 99, 'Mumbai', 118560),\r\n            ('Jaydev', 51, 'Kolkata', 258741),\r\n            ('Shikhar', 31, 'Mumbai', 485169),\r\n            ('Sanju', 12, 'Rajasthan', 150000),\r\n            ('Raina', 35, 'Gujarat', 250000)\r\n            ]\r\n# Creation of DataFrame object\r\nplayDFObj = sc.DataFrame(players, columns=['Name', 'JerseyN', 'Team', 'Salary'])\r\n# Rename index of dataframe as 'SL'\r\nplayDFObj.index.rename('SL', inplace=True)\r\nmodifplayDF = playDFObj.set_index('Team', verify_integrity=True)\r\nprint(modifplayDF)\r\n<\/pre>\n<pre>Output :\r\nValueError: Index has duplicate keys<\/pre>\n<h3><a id=\"Modify_existing_Dataframe_by_converting_into_index\"><\/a>Modifying existing Dataframe by converting into index :<\/h3>\n<p><strong>\u00a0<\/strong>We can also make changes in existing dataframe. We can implement this by assign two methods-<\/p>\n<ol>\n<li>Assign the returned dataframe object to original dataframe variable where the variable would point to updated dataframe.<\/li>\n<li>Passing argument <code>inplace<\/code> as True.<\/li>\n<\/ol>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as sc\r\n# List of Tuples\r\nplayers = [('Smith', 15, 'Pune', 170000),\r\n            ('Rana', 99, 'Mumbai', 118560),\r\n            ('Jaydev', 51, 'Kolkata', 258741),\r\n            ('Shikhar', 31, 'Hyderabad', 485169),\r\n            ('Sanju', 12, 'Rajasthan', 150000),\r\n            ('Raina', 35, 'Gujarat', 250000)\r\n            ]\r\n# Creation DataFrame object\r\nplayDFObj = sc.DataFrame(players, columns=['Name', 'JerseyN', 'Team', 'Salary'])\r\nplayDFObj.index.rename('SL', inplace=True)\r\nplayDFObj.set_index('Name', inplace=True)\r\nprint('Contenets of original dataframe :')\r\nprint(playDFObj)\r\n<\/pre>\n<pre>Output :\r\nContenets of original dataframe :\r\nJerseyN Team Salary\r\nName \r\nSmith 15 Pune 170000\r\nRana 99 Mumbai 118560\r\nJaydev 51 Kolkata 258741\r\nShikhar 31 Hyderabad 485169\r\nSanju 12 Rajasthan 150000\r\nRaina 35 Gujarat 250000<\/pre>\n<p>Want to expert in the python programming language? Exploring\u00a0<a href=\"https:\/\/python-programs.com\/python-data-analysis-using-pandas\/\">Python Data Analysis using Pandas<\/a>\u00a0tutorial changes your knowledge from basic to advance level in python concepts.<\/p>\n<p><strong>Read more Articles on Python Data Analysis Using Padas \u2013 Modify a Dataframe<\/strong><\/p>\n<ul>\n<li><a href=\"https:\/\/python-programs.com\/pandas-apply-apply-a-function-to-each-row-column-in-dataframe\/\">pandas.apply(): Apply a function to each row\/column in Dataframe<\/a><\/li>\n<li><a href=\"https:\/\/python-programs.com\/pandas-sort-rows-or-columns-in-dataframe-based-on-values-using-dataframe-sort_values\/\">Pandas: Sort rows or columns in Dataframe based on values using Dataframe.sort_values()<\/a><\/li>\n<li><a href=\"https:\/\/python-programs.com\/pandas-apply-a-function-to-single-or-selected-columns-or-rows-in-dataframe\/\">Apply a function to single or selected columns or rows in Dataframe<\/a><\/li>\n<li><a href=\"https:\/\/python-programs.com\/pandas-sort-a-dataframe-based-on-column-names-or-row-index-labels-using-dataframe-sort_index\/\">Sort a DataFrame based on column names or row index labels using Dataframe.sort_index() in Pandas<\/a><\/li>\n<li><a href=\"https:\/\/python-programs.com\/pandas-change-data-type-of-single-or-multiple-columns-of-dataframe-in-python\/\">Change data type of single or multiple columns of Dataframe in Python<\/a><\/li>\n<li><a href=\"https:\/\/python-programs.com\/python-pandas-replace-or-change-column-row-index-names-in-dataframe\/\">Change Column &amp; Row names in DataFrame<\/a><\/li>\n<li><a href=\"https:\/\/python-programs.com\/how-to-convert-dataframe-column-type-from-string-to-date-time\/\">Convert Dataframe column type from string to date time<\/a><\/li>\n<li><a href=\"https:\/\/python-programs.com\/pandas-convert-data-frame-index-into-column-using-dataframe-reset_index-in-python\/\">Convert Dataframe indexes into columns<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Converting Dataframe column into an index using set_index() in Python In this article we will learn to convert an existing column of Dataframe to a index including various cases. We can implement this using set_index() function of Pandas Dataframe class. Convert a column of Dataframe into an index of the Dataframe Convert a column of &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/python-programs.com\/convert-pandas-dataframe-column-into-an-index-using-set_index-in-python\/\"> <span class=\"screen-reader-text\">Pandas : Convert Dataframe column into an index using set_index() in Python<\/span> Read More &raquo;<\/a><\/p>\n","protected":false},"author":9,"featured_media":8593,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spay_email":"","jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true},"categories":[5],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v18.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pandas : Convert Dataframe column into an index using set_index() in Python - Python Programs<\/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:\/\/python-programs.com\/convert-pandas-dataframe-column-into-an-index-using-set_index-in-python\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas : Convert Dataframe column into an index using set_index() in Python - Python Programs\" \/>\n<meta property=\"og:description\" content=\"Converting Dataframe column into an index using set_index() in Python In this article we will learn to convert an existing column of Dataframe to a index including various cases. We can implement this using set_index() function of Pandas Dataframe class. 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We can implement this using set_index() function of Pandas Dataframe class. 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