{"id":6655,"date":"2021-05-22T09:06:40","date_gmt":"2021-05-22T03:36:40","guid":{"rendered":"https:\/\/python-programs.com\/?p=6655"},"modified":"2021-11-22T18:45:25","modified_gmt":"2021-11-22T13:15:25","slug":"pandas-sort-a-dataframe-based-on-column-names-or-row-index-labels-using-dataframe-sort_index","status":"publish","type":"post","link":"https:\/\/python-programs.com\/pandas-sort-a-dataframe-based-on-column-names-or-row-index-labels-using-dataframe-sort_index\/","title":{"rendered":"Pandas : Sort a DataFrame based on column names or row index labels using Dataframe.sort_index()"},"content":{"rendered":"<h2>Sorting a DataFrame based on column names or row index labels using Dataframe.sort_index() in Python<\/h2>\n<p>In this article we will discuss how we organize the content of data entered based on column names or line reference labels using <code>Dataframe.sort_index ().<\/code><\/p>\n<h3>Dataframe.sort_index():<\/h3>\n<p>In the Python Pandas Library, the Dataframe section provides a member sort sort_index () to edit DataFrame based on label names next to the axis i.e.<\/p>\n<pre>DataFrame.sort_index(axis=0, level=None, ascending=True, inplace=False, kind='quicksort', na_position='last', sort_remaining=True, by=None)<\/pre>\n<p>Where,<\/p>\n<ul>\n<li><strong>axis :<\/strong>If the axis is 0, then the data name will be sorted based on the line index labels. The default is 0<\/li>\n<li><strong>ascending :<\/strong>If the axis is 1, then the data name will be sorted based on column names.<\/li>\n<li><strong>inplace :<\/strong> If the type of truth in the rise of another type arrange in order. The default is true<\/li>\n<li><strong>na_position<\/strong> :\u00a0 If True, enable localization in Dataframe. Determines NaN status after filter i.e. irst puts NaNs first, finally puts NaNs at the end.<\/li>\n<\/ul>\n<p>It returns the edited data object. Also, if the location dispute is untrue then it will return a duplicate copy of the provided data, instead of replacing the original Dataframe. While, if the internal dispute is true it will cause the current file name to be edited.<\/p>\n<p>Let&#8217;s understand some examples,<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\"># Program :\r\n\r\nimport pandas as pd\r\n# List of Tuples\r\nstudents = [ ('Rama', 31, 'canada') ,\r\n             ('Symon', 23, 'Chennai' ) ,\r\n             ('Arati', 16, 'Maharastra') ,\r\n             ('Bhabani', 32, 'Kolkata' ) ,\r\n             ('Modi', 33, 'Uttarpradesh' ) ,\r\n             ('Heeron', 39, 'Hyderabad' )\r\n              ]\r\n# Create a DataFrame object\r\ndfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])\r\nprint(dfObj)\r\n<\/pre>\n<pre>Output :\r\n\u00a0 \u00a0 Name\u00a0 \u00a0Marks\u00a0 City\r\nb\u00a0 Rama\u00a0 \u00a0 \u00a031\u00a0 \u00a0canada\r\na\u00a0 Symon\u00a0 \u00a023\u00a0 \u00a0Chennai\r\nf\u00a0 \u00a0Arati\u00a0 \u00a0 \u00a0 16\u00a0 \u00a0Maharastra\r\ne\u00a0 Bhabani\u00a0 32\u00a0 Kolkata\r\nd\u00a0 Modi\u00a0 \u00a0 \u00a0 33\u00a0 Uttarpradesh\r\nc\u00a0 Heeron\u00a0 39\u00a0 \u00a0Hyderabad<\/pre>\n<p>Now let&#8217;s see how we organize this DataFrame based on labels i.e. columns or line reference labels,<\/p>\n<h3 style=\"background: white; vertical-align: baseline; margin: 0cm 0cm 12.0pt 0cm;\"><span lang=\"EN-US\" style=\"font-size: 16.0pt; line-height: 115%; font-family: 'Arial',sans-serif; color: #555555;\">Sort rows of a Dataframe based on Row index labels :<\/span><\/h3>\n<p>Sorting by line index labels we can call <code>sort_index()<\/code> in the data name item.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as pd\r\n# The List of Tuples\r\nstudents = [ ('Rama', 31, 'canada') ,\r\n             ('Symon', 23, 'Chennai' ) ,\r\n             ('Arati', 16, 'Maharastra') ,\r\n             ('Bhabani', 32, 'Kolkata' ) ,\r\n             ('Modi', 33, 'Uttarpradesh' ) ,\r\n             ('Heeron', 39, 'Hyderabad' )\r\n              ]\r\n# To create DataFrame object \r\ndfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])\r\n# By sorting the rows of dataframe based on row index label names\r\nmodDFObj = dfObj.sort_index()\r\nprint(' Dataframes are in sorted oreder of index value given:')\r\nprint(modDFObj)<\/pre>\n<pre>Output :\r\nDataframes are in sorted oreder of index value given:\r\n\u00a0 \u00a0 Name\u00a0 \u00a0 Marks\u00a0 \u00a0 \u00a0 \u00a0 City\r\na Symon\u00a0 \u00a0 \u00a0 23\u00a0 \u00a0 \u00a0 \u00a0 \u00a0Chennai\r\nb Rama\u00a0 \u00a0 \u00a0 \u00a0 31\u00a0 \u00a0 \u00a0 \u00a0 \u00a0canada\r\nc Heeron\u00a0 \u00a0 \u00a039\u00a0 \u00a0 \u00a0 \u00a0 \u00a0Hyderabad\r\nd Modi\u00a0 \u00a0 \u00a0 \u00a0 33\u00a0 \u00a0 \u00a0 \u00a0 \u00a0Uttarpradesh\r\ne Bhabani\u00a0 \u00a0 32\u00a0 \u00a0 \u00a0 \u00a0 \u00a0Kolkata\r\nf Arati\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 16\u00a0 \u00a0 \u00a0 \u00a0 \u00a0Maharastra<\/pre>\n<p>As we can see in the output lines it is sorted based on the reference labels now. Instead of changing the original name data backed up an edited copy of the dataframe.<\/p>\n<h3>Sort rows of a Dataframe in Descending Order based on Row index labels :<\/h3>\n<p>Sorting based on line index labels in descending order we need to pass the <code>argument = False<\/code> in <code>sort_index()<\/code> function in the data object object.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as pd\r\n# The List of Tuples\r\nstudents = [ ('Rama', 31, 'canada') ,\r\n             ('Symon', 23, 'Chennai' ) ,\r\n             ('Arati', 16, 'Maharastra') ,\r\n             ('Bhabani', 32, 'Kolkata' ) ,\r\n             ('Modi', 33, 'Uttarpradesh' ) ,\r\n             ('Heeron', 39, 'Hyderabad' )\r\n              ]\r\n# To create DataFrame object \r\ndfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])\r\n# By sorting the rows of dataframe in descending order based on row index label names\r\nconObj = dfObj.sort_index(ascending=False)\r\nprint('The Contents of Dataframe are sorted in descending Order based on Row Index Labels are of :')\r\nprint(conObj)\r\n<\/pre>\n<pre>The Contents of Dataframe are sorted in descending Order based on Row Index Labels are of :\r\n     Name\u00a0      Marks\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 City\r\nf\u00a0\u00a0\u00a0   Arati\u00a0\u00a0\u00a0\u00a0      16\u00a0\u00a0\u00a0       Maharastra\r\ne\u00a0    Bhabani\u00a0\u00a0\u00a0\u00a0 32\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0    Kolkata\r\nd\u00a0\u00a0\u00a0\u00a0 Modi\u00a0\u00a0\u00a0\u00a0    33\u00a0          Uttarpradesh\r\nc\u00a0\u00a0   Heeron\u00a0\u00a0\u00a0\u00a0 39\u00a0\u00a0\u00a0\u00a0       Hyderabad\r\nb\u00a0\u00a0\u00a0\u00a0 Rama\u00a0\u00a0\u00a0\u00a0   31\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0    canada\r\na\u00a0\u00a0\u00a0  Symon\u00a0\u00a0\u00a0\u00a0 23\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0     Chennai<\/pre>\n<p>As we can see in the output lines it is sorted by destructive sequence based on the current reference labels. Also, instead of changing the original data name it restored the edited copy of the data.<\/p>\n<h3>Sort rows of a Dataframe based on Row index labels in Place :<\/h3>\n<p>Filtering a local data name instead of finding the default copy transfer <code>inplace = True<\/code> in <code>sort_index ()<\/code> function in the data object object to filter the data name with local reference label labels i.e.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as pd\r\n# The List of Tuples\r\nstudents = [ ('Rama', 31, 'canada') ,\r\n             ('Symon', 23, 'Chennai' ) ,\r\n             ('Arati', 16, 'Maharastra') ,\r\n             ('Bhabani', 32, 'Kolkata' ) ,\r\n             ('Modi', 33, 'Uttarpradesh' ) ,\r\n             ('Heeron', 39, 'Hyderabad' )\r\n              ]\r\n# To create DataFrame object \r\ndfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])\r\n#By sorting the rows of dataframe in Place based on row index label names\r\ndfObj.sort_index(inplace=True)\r\nprint('The Contents of Dataframe are sorted in Place based on Row Index Labels are of :')\r\nprint(dfObj)\r\n<\/pre>\n<pre>Output :\r\nThe Contents of Dataframe are sorted in Place based on Row Index Labels are of :\r\n  \u00a0 \u00a0Name\u00a0 \u00a0 \u00a0Marks\u00a0 \u00a0 \u00a0 City\r\na\u00a0\u00a0\u00a0 Symon\u00a0\u00a0\u00a0\u00a0 23\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Chennai\r\nb\u00a0\u00a0\u00a0\u00a0 Rama\u00a0\u00a0\u00a0\u00a0 31\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 canada\r\nc\u00a0\u00a0 Heeron\u00a0\u00a0\u00a0\u00a0 39\u00a0\u00a0\u00a0\u00a0 Hyderabad\r\nd\u00a0\u00a0\u00a0\u00a0 Modi\u00a0\u00a0\u00a0\u00a0 33\u00a0 \u00a0 \u00a0Uttarpradesh\r\ne\u00a0 Bhabani\u00a0\u00a0\u00a0\u00a0 32\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Kolkata\r\nf\u00a0\u00a0\u00a0 Arati\u00a0 \u00a0 \u00a0 \u00a016\u00a0 \u00a0 \u00a0 \u00a0Maharastra<\/pre>\n<h3>Sort Columns of a Dataframe based on Column Names :<\/h3>\n<p>To edit DataFrame based on column names we can say sort_index () in a DataFrame object with an axis= 1 i.e.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as pd\r\n# The List of Tuples\r\nstudents = [ ('Rama', 31, 'canada') ,\r\n             ('Symon', 23, 'Chennai' ) ,\r\n             ('Arati', 16, 'Maharastra') ,\r\n             ('Bhabani', 32, 'Kolkata' ) ,\r\n             ('Modi', 33, 'Uttarpradesh' ) ,\r\n             ('Heeron', 39, 'Hyderabad' )\r\n              ]\r\n# To create DataFrame object \r\ndfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])\r\n# By sorting a dataframe based on column names\r\nconObj = dfObj.sort_index(axis=1)\r\nprint('The Contents are of Dataframe sorted based on Column Names are in the type :')\r\nprint(conObj)\r\n\r\n<\/pre>\n<pre>Output :\r\nThe Contents are of Dataframe sorted based on Column Names are in the type :\r\n           City\u00a0         Marks\u00a0\u00a0\u00a0\u00a0 Name\r\nb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 canada\u00a0\u00a0\u00a0\u00a0     31\u00a0\u00a0\u00a0\u00a0  Rama\r\na\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Chennai\u00a0\u00a0\u00a0\u00a0     23\u00a0\u00a0\u00a0  Symon\r\nf\u00a0\u00a0\u00a0   Maharastra\u00a0\u00a0\u00a0\u00a0 16\u00a0\u00a0\u00a0  Arati\r\ne\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Kolkata\u00a0\u00a0\u00a0\u00a0      32\u00a0    Bhabani\r\nd\u00a0 Uttarpradesh\u00a0\u00a0\u00a0\u00a0 33\u00a0\u00a0\u00a0\u00a0 Modi\r\nc\u00a0\u00a0\u00a0\u00a0 Hyderabad\u00a0\u00a0\u00a0\u00a0 39\u00a0\u00a0    Heeron<\/pre>\n<p>As we can see, instead of changing the original data name it returns a fixed copy of the data data based on the column names.<\/p>\n<h3>Sort Columns of a Dataframe in Descending Order based on Column Names :<\/h3>\n<p>By sorting DataFrame based on column names in descending order, we can call <code>sort_index ()<\/code> in the DataFrame item with axis = 1 and ascending = False i.e.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as pd\r\n# The List of Tuples\r\nstudents = [ ('Rama', 31, 'canada') ,\r\n             ('Symon', 23, 'Chennai' ) ,\r\n             ('Arati', 16, 'Maharastra') ,\r\n             ('Bhabani', 32, 'Kolkata' ) ,\r\n             ('Modi', 33, 'Uttarpradesh' ) ,\r\n             ('Heeron', 39, 'Hyderabad' )\r\n              ]\r\n# To create DataFrame object \r\ndfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])\r\n# By sorting a dataframe in descending order based on column names\r\nconObj = dfObj.sort_index(ascending=False, axis=1)\r\nprint('The Contents of Dataframe sorted in Descending Order based on Column Names are of :')\r\nprint(conObj)\r\n<\/pre>\n<pre>Output :\r\nThe Contents of Dataframe sorted in Descending Order based on Column Names are of :\r\nName\u00a0 Marks\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 City\r\nb\u00a0\u00a0\u00a0\u00a0 Rama\u00a0\u00a0\u00a0\u00a0 31\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 canada\r\na\u00a0\u00a0\u00a0 Symon\u00a0\u00a0\u00a0\u00a0 23\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Chennai\r\nf\u00a0\u00a0\u00a0 Arati\u00a0\u00a0\u00a0\u00a0 16\u00a0\u00a0\u00a0 Maharastra\r\ne\u00a0 Bhabani\u00a0\u00a0\u00a0\u00a0 32\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Kolkata\r\nd\u00a0\u00a0\u00a0\u00a0 Modi\u00a0\u00a0\u00a0\u00a0 33\u00a0 Uttarpradesh\r\nc\u00a0\u00a0 Heeron\u00a0\u00a0\u00a0\u00a0 39\u00a0\u00a0\u00a0\u00a0 Hyderabad<\/pre>\n<p>Instead of changing the original data name restore the edited copy of the data based on the column names (sorted by order)<\/p>\n<h3>Sort Columns of a Dataframe in Place based on Column Names :<\/h3>\n<p>Editing a local data name instead of obtaining an approved copy pass input = True and axis = 1 in sort_index () function in the dataframe object to filter the local data name by column names i.e.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as pd\r\n# The List of Tuples\r\nstudents = [ ('Rama', 31, 'canada') ,\r\n             ('Symon', 23, 'Chennai' ) ,\r\n             ('Arati', 16, 'Maharastra') ,\r\n             ('Bhabani', 32, 'Kolkata' ) ,\r\n             ('Modi', 33, 'Uttarpradesh' ) ,\r\n             ('Heeron', 39, 'Hyderabad' )\r\n              ]\r\n# To create DataFrame object \r\ndfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])\r\n# By sorting a dataframe in place based on column names\r\ndfObj.sort_index(inplace=True, axis=1)\r\nprint('The Contents of Dataframe sorted in Place based on Column Names are of:')\r\nprint(dfObj)\r\n\r\n<\/pre>\n<pre>Output :\r\nThe Contents of Dataframe sorted in Place based on Column Names are of:\r\nCity\u00a0 Marks\u00a0\u00a0\u00a0\u00a0 Name\r\nb\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 canada\u00a0\u00a0\u00a0\u00a0 31\u00a0\u00a0\u00a0\u00a0 Rama\r\na\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Chennai\u00a0\u00a0\u00a0\u00a0 23\u00a0\u00a0\u00a0 Symon\r\nf\u00a0\u00a0\u00a0 Maharastra\u00a0\u00a0\u00a0\u00a0 16\u00a0\u00a0\u00a0 Arati\r\ne\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Kolkata\u00a0\u00a0\u00a0\u00a0 32\u00a0 Bhabani\r\nd\u00a0 Uttarpradesh\u00a0\u00a0\u00a0\u00a0 33\u00a0\u00a0\u00a0\u00a0 Modi\r\nc\u00a0\u00a0\u00a0\u00a0 Hyderabad\u00a0\u00a0\u00a0\u00a0 39\u00a0\u00a0 Heeron<\/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-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\/convert-pandas-dataframe-column-into-an-index-using-set_index-in-python\/\">Convert Dataframe column into to the Index of Dataframe<\/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>Sorting a DataFrame based on column names or row index labels using Dataframe.sort_index() in Python In this article we will discuss how we organize the content of data entered based on column names or line reference labels using Dataframe.sort_index (). Dataframe.sort_index(): In the Python Pandas Library, the Dataframe section provides a member sort sort_index () &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/python-programs.com\/pandas-sort-a-dataframe-based-on-column-names-or-row-index-labels-using-dataframe-sort_index\/\"> <span class=\"screen-reader-text\">Pandas : Sort a DataFrame based on column names or row index labels using Dataframe.sort_index()<\/span> Read More &raquo;<\/a><\/p>\n","protected":false},"author":9,"featured_media":0,"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 : Sort a DataFrame based on column names or row index labels using Dataframe.sort_index() - 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\/pandas-sort-a-dataframe-based-on-column-names-or-row-index-labels-using-dataframe-sort_index\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas : Sort a DataFrame based on column names or row index labels using Dataframe.sort_index() - Python Programs\" \/>\n<meta property=\"og:description\" content=\"Sorting a DataFrame based on column names or row index labels using Dataframe.sort_index() in Python In this article we will discuss how we organize the content of data entered based on column names or line reference labels using Dataframe.sort_index (). 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