{"id":8112,"date":"2021-02-17T22:04:24","date_gmt":"2021-02-17T16:34:24","guid":{"rendered":"https:\/\/pynative.com\/?p=8112"},"modified":"2023-03-09T11:53:38","modified_gmt":"2023-03-09T06:23:38","slug":"convert-pandas-dataframe-to-dict","status":"publish","type":"post","link":"https:\/\/pynative.com\/convert-pandas-dataframe-to-dict\/","title":{"rendered":"Convert Pandas DataFrame to Python dictionary"},"content":{"rendered":"\n<p>In this article, you will learn how to convert <a href=\"https:\/\/pynative.com\/python-pandas-dataframe\/\">pandas DataFrame<\/a> into a <a href=\"https:\/\/pynative.com\/python-dictionaries\/\">Python dictionary<\/a>. It explains creating different kinds of dictionaries from pandas DataFrame.<\/p>\n\n\n\n<p>Data Analyst needs to collect the data from heterogeneous sources like CSV files or SQL tables or Python data structures like a dictionary, list, etc. Such data is converted into pandas DataFrame. <\/p>\n\n\n\n<p>After analyzing the data, we need to convert the resultant DataFrame back to its original format like CSV files or a dictionary. Or sometimes, we need to convert it into some other form. <\/p>\n\n\n\n<div class=\"wp-block-yoast-seo-table-of-contents yoast-table-of-contents\"><h2>Table of contents<\/h2><ul><li><a href=\"#h-the-dataframe-to_dict-function\" data-level=\"2\">The DataFrame.to_dict() function<\/a><ul><li><a href=\"#h-example-to-convert-pandas-dataframe-to-dict\" data-level=\"3\">Example to convert pandas DataFrame to dict<\/a><\/li><\/ul><\/li><li><a href=\"#h-dataframe-to-dict-with-a-list-of-values\" data-level=\"2\">DataFrame to dict with a list of values<\/a><\/li><li><a href=\"#h-dataframe-to-dict-with-pandas-series-of-values\" data-level=\"2\">DataFrame to dict with pandas series of values<\/a><\/li><li><a href=\"#h-dataframe-to-dict-without-header-and-index\" data-level=\"2\">DataFrame to dict without header and index<\/a><\/li><li><a href=\"#h-dataframe-to-dict-by-row\" data-level=\"2\">DataFrame to dict by row<\/a><\/li><li><a href=\"#h-dataframe-to-dict-by-row-index\" data-level=\"2\">DataFrame to dict by row index<\/a><\/li><li><a href=\"#h-dataframe-to-dict-with-one-column-as-the-key\" data-level=\"2\">DataFrame to dict with one column as the key<\/a><\/li><li><a href=\"#h-dataframe-to-dict-using-into-parameter\" data-level=\"2\">DataFrame to dict using into parameter<\/a><\/li><\/ul><\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-the-dataframe-to_dict-function\">The <code>DataFrame.to_dict()<\/code> function<\/h2>\n\n\n\n<p>Pandas have a <code>DataFrame.to_dict()<\/code> function to create a Python <code>dict<\/code> object from DataFrame.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code1\"  class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-1\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\">DataFrame.to_dict(orient=<span class=\"hljs-string\">'dict'<\/span>, into=&lt;<span class=\"hljs-class\"><span class=\"hljs-keyword\">class<\/span> '<span class=\"hljs-title\">dict<\/span>'&gt;)<\/span><\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-1\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code1', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><button class=\"hljs-run-button\" onclick=\"run_code('code1');\"><i class=\"far fa-play-circle\" aria-hidden=\"true\"><\/i> Run<\/button><\/div>\n\n\n<p><strong>Parameters:<\/strong><\/p>\n\n\n\n<ul>\n<li><strong><code>into<\/code><\/strong>: It is used to define the type of resultant <code>dict<\/code>. We can give an actual class or an empty instance.<\/li>\n\n\n\n<li><strong><code>orient<\/code><\/strong>: It defines the structure of key-value pairs in the resultant <code>dict<\/code>. The below table shows the input parameter, the format in which it creates the <code>dict<\/code> and key-value of the resultant <code>dict<\/code>.<\/li>\n<\/ul>\n\n\n\n<p><strong>Note<\/strong>: Abbreviations are allowed. s indicates series, sp indicates split, r indicates record likewise.<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-regular\"><table><thead><tr><th>Parameter<\/th><th>Dict format<\/th><th>Key<\/th><th>Value<\/th><\/tr><\/thead><tbody><tr><td><code>'dict'<\/code>(Default)<\/td><td><code>{column_label : {row_index : data}}<\/code><\/td><td>column label<\/td><td>dict of row index and data<\/td><\/tr><tr><td><code>'list'<\/code><\/td><td><code>{column_label : [data]}<\/code><\/td><td>column label<\/td><td>list of data<\/td><\/tr><tr><td><code>'series<\/code>&#8216;<\/td><td><code>{column_label : Series(data)}<\/code><\/td><td>column label<\/td><td>series of data<\/td><\/tr><tr><td><code>'split'<\/code><\/td><td><code>{'row_index' : [index], \u2018column_label\u2019 : [columns], 'data' : [data]}<\/code><\/td><td>row index, column labels, data<\/td><td>list of row index, list of columns labels, list of data<\/td><\/tr><tr><td><code>'records'<\/code><\/td><td><code>[{column_label : data}, \u2026 , {column_label : data}]<\/code><\/td><td>column label<\/td><td>data<\/td><\/tr><tr><td><code>'index'<\/code><\/td><td><code>{row_index : {column_label : data}}<\/code><\/td><td>row index<\/td><td><code>dict <\/code>of column label and data<\/td><\/tr><\/tbody><\/table><figcaption class=\"wp-element-caption\"><code>DataFrame.to_dict()<\/code> function parameters<\/figcaption><\/figure>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"523\" height=\"573\" src=\"https:\/\/pynative.com\/wp-content\/uploads\/2021\/02\/pandas-dataframe-to-dictionary.png\" alt=\"Pandas DataFrame to Python Dictionary\" class=\"wp-image-8362\" srcset=\"https:\/\/pynative.com\/wp-content\/uploads\/2021\/02\/pandas-dataframe-to-dictionary.png 523w, https:\/\/pynative.com\/wp-content\/uploads\/2021\/02\/pandas-dataframe-to-dictionary-274x300.png 274w\" sizes=\"(max-width: 523px) 100vw, 523px\" \/><figcaption class=\"wp-element-caption\">Pandas DataFrame to Python Dict<\/figcaption><\/figure><\/div>\n\n\n<h3 class=\"wp-block-heading\" id=\"h-example-to-convert-pandas-dataframe-to-dict\"><strong>Example<\/strong> to convert pandas DataFrame to dict<\/h3>\n\n\n\n<p>In the below example, we read the input from the <a href=\"https:\/\/pynative.com\/wp-content\/uploads\/2021\/02\/StudentData.csv\">StudentData.csv<\/a> file and create a DataFrame object. It is then converted into the Python dictionary object.<\/p>\n\n\n\n<p>Input CSV file contains a simple dataset of student data with two columns, &#8220;<strong>Name<\/strong>&#8221; and &#8220;<strong>Marks<\/strong>&#8220;.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"196\" height=\"144\" src=\"https:\/\/pynative.com\/wp-content\/uploads\/2021\/02\/dataframe-csv.png\" alt=\"DataFrame from CSV\" class=\"wp-image-8147\"\/><\/figure><\/div>\n\n\n<p>DataFrame is converted into <code>dict<\/code> using the default <code>'dict' <\/code>parameter.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code2\"  id=\"norun\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-2\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n\n<span class=\"hljs-comment\"># create dataframe from csv<\/span>\nstudentDf = pd.read_csv(<span class=\"hljs-string\">\"StudentData.csv\"<\/span>)\nprint(studentDf)\n\n<span class=\"hljs-comment\"># create dict from dataframe<\/span>\nstudentDict = studentDf.to_dict()\nprint(studentDict)<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-2\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code2', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><\/div>\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">    Name  Marks\n0    Nat  70.88\n1  Harry  85.90\n2    Joe  91.45\n\nResult dict\n{'Name': {0: 'Nat', 1: 'Harry', 2: 'Joe'}, 'Marks': {0: 70.88, 1: 85.9, 2: 91.45}}<\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-dataframe-to-dict-with-a-list-of-values\">DataFrame to dict with a list of values<\/h2>\n\n\n\n<p>It is a case when we have DataFrame, which needs to be converted into the dictionary object such that column label should be the keys in the dictionary, and all the columns&#8217; data should be added into the resultant <code>dict<\/code> as a list of values against each key.<\/p>\n\n\n\n<p>In that case, we can use <code>'list'<\/code> parameter of the <code>DataFrame.to_dict() <\/code>function.<\/p>\n\n\n<pre id=\"syntax\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-3\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\">{column_label : &#91;data]}<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-3\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p><strong>Example<\/strong><\/p>\n\n\n\n<p>Let&#8217;s see how we can use a <code>'list'<\/code> parameter to create DataFrame with a list of values.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code3\"  id=\"norun\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-4\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n\n<span class=\"hljs-comment\"># create dataframe from csv<\/span>\nstudentDf = pd.read_csv(<span class=\"hljs-string\">\"StudentData.csv\"<\/span>)\nprint(studentDf)\n\n<span class=\"hljs-comment\"># create dict from dataframe<\/span>\nstudentDict = studentDf.to_dict(<span class=\"hljs-string\">'list'<\/span>)\nprint(studentDict)<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-4\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code3', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><\/div>\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">    Name  Marks\n0    Nat  70.88\n1  Harry  85.90\n2    Joe  91.45\n\n{'Name': ['Nat', 'Harry', 'Joe'], 'Marks': [70.88, 85.9, 91.45]}<\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-dataframe-to-dict-with-pandas-series-of-values\">DataFrame to dict with pandas series of values<\/h2>\n\n\n\n<p>When we need to convert the DataFrame into <code>dict<\/code> whereas column name as a key of the <code>dict<\/code>. And row index and data as a value in the <code>dict<\/code> for the respective keys.<\/p>\n\n\n<pre id=\"syntax\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-5\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\">{column_label : Series(row_index data)}<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-5\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p>In that case, we can use the <code>'series'<\/code> parameter of <code>DataFrame.to_dict()<\/code> function.<\/p>\n\n\n\n<p><strong>Example<\/strong><\/p>\n\n\n\n<p>In the below example, <code>dict<\/code> is created with two entries, one for &#8216;<strong>Name<\/strong>&#8216; column and the other for the &#8216;<strong>Marks<\/strong>&#8216; column of the DataFrame.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code4\"  id=\"norun\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-6\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n\n<span class=\"hljs-comment\"># create dataframe from csv<\/span>\nstudentDf = pd.read_csv(<span class=\"hljs-string\">\"StudentData.csv\"<\/span>)\nprint(studentDf)\n\n<span class=\"hljs-comment\"># create dict from dataframe<\/span>\nstudentDict = studentDf.to_dict(<span class=\"hljs-string\">'series'<\/span>)\nprint(studentDict)\n<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-6\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code4', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><\/div>\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">    Name  Marks\n0    Nat  70.88\n1  Harry  85.90\n2    Joe  91.45\n\n{'Name': \n     0      Nat\n     1    Harry\n     2      Joe\n Name: Name, dtype: object, \n 'Marks': \n     0    70.88\n     1    85.90\n     2    91.45\n Name: Marks, dtype: float64}<\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-dataframe-to-dict-without-header-and-index\">DataFrame to dict without header and index<\/h2>\n\n\n\n<p>When we want to collect the data from DataFrame without the column headers or we need to separate the row index and header from the data, we can use the <code>'split'<\/code> parameter of <code>DataFrame.to_dict()<\/code> function. It splits the input DataFrame into three parts, i.e., row index, column labels, and actual data.<\/p>\n\n\n<pre id=\"syntax\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-7\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\">{<span class=\"hljs-string\">'row_index'<\/span> : &#91;index], <span class=\"hljs-string\">'column_label'<\/span> : &#91;columns], <span class=\"hljs-string\">'data'<\/span> : &#91;data]}<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-7\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p><strong>Example<\/strong><\/p>\n\n\n\n<p>We can get the data without index or header from the resultant <code>dict<\/code> using key <strong>&#8220;data&#8221;<\/strong> as shown below.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code5\"  id=\"norun\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-8\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n\n<span class=\"hljs-comment\"># create dataframe from csv<\/span>\nstudentDf = pd.read_csv(<span class=\"hljs-string\">\"StudentData.csv\"<\/span>)\nprint(studentDf)\n\nstudentDict = studentDf.to_dict(<span class=\"hljs-string\">'split'<\/span>)\nprint(studentDict)\n\n<span class=\"hljs-comment\"># print only data<\/span>\nprint(studentDict&#91;<span class=\"hljs-string\">'data'<\/span>])<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-8\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code5', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><\/div>\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">    Name  Marks\n0    Nat  70.88\n1  Harry  85.90\n2    Joe  91.45\n\n{'index': [0, 1, 2], 'columns': ['Name', 'Marks'], 'data': [['Nat', 70.88], ['Harry', 85.9], ['Joe', 91.45]]}\n\nList of values from DF without index and header : \n[['Nat', 70.88], ['Harry', 85.9], ['Joe', 91.45]]<\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-dataframe-to-dict-by-row\">DataFrame to dict by row<\/h2>\n\n\n\n<p>When we have a DataFrame where <strong>each row<\/strong> contains data that needs to be store in a <strong>separate dictionary<\/strong> object, i.e., we need a data row-wise, we can use the&nbsp;<code>'records'<\/code>&nbsp;parameter of the <code>DataFrame.to_dict()<\/code> function.<\/p>\n\n\n\n<p>It returns a list of dictionary objects. A <code>dict<\/code> for each row, where the key is a column label, and the value is column data.<\/p>\n\n\n<pre id=\"syntax\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-9\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\">&#91;{column_label : data}, \u2026 , {column_label : data}]<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-9\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p><strong>Example<\/strong><\/p>\n\n\n\n<p>In the below example, we created list of dictionary for each student data.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code6\"  id=\"norun\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-10\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-comment\"># import pandas library<\/span>\n<span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n\n<span class=\"hljs-comment\"># create dataframe from csv<\/span>\nstudentDf = pd.read_csv(<span class=\"hljs-string\">\"StudentData.csv\"<\/span>)\nprint(studentDf)\n\n<span class=\"hljs-comment\"># create dict from dataframe<\/span>\nstudentDict = studentDf.to_dict(<span class=\"hljs-string\">'record'<\/span>)\nprint(studentDict)\n<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-10\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code6', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><\/div>\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">    Name  Marks\n0    Nat  70.88\n1  Harry  85.90\n2    Joe  91.45\n\n[{'Name': 'Nat', 'Marks': 70.88}, {'Name': 'Harry', 'Marks': 85.9}, {'Name': 'Joe', 'Marks': 91.45}]<\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-dataframe-to-dict-by-row-index\">DataFrame to dict by row index<\/h2>\n\n\n\n<p>When we have a DataFrame with row indexes and if we need to convert the data of each row from DataFrame to <code>dict<\/code>, we can use the&nbsp;<code>index<\/code>&nbsp;parameter of the <code>DataFrame.to_dict()<\/code> function.<\/p>\n\n\n\n<p>It returns a list of dictionary objects. A <code>dict<\/code> is created for each row. Where the key is a row index, and the value is <code>dict <\/code>of column label and data.<\/p>\n\n\n<pre id=\"syntax\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-11\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\">{row_index : {column_label : data}}<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-11\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p><strong>Example<\/strong><\/p>\n\n\n\n<p>In the below example <code>dict<\/code> object is created for each row of student data.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code7\"  id=\"norun\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-12\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n\n<span class=\"hljs-comment\"># create dataframe from csv<\/span>\nstudentDf = pd.read_csv(<span class=\"hljs-string\">\"StudentData.csv\"<\/span>)\nprint(studentDf)\n\n<span class=\"hljs-comment\"># create dict from dataframe<\/span>\nstudentDict = studentDf.to_dict(<span class=\"hljs-string\">'index'<\/span>)\nprint(studentDict)<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-12\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code7', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><\/div>\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">    Name  Marks\n0    Nat  70.88\n1  Harry  85.90\n2    Joe  91.45\n\n{0: {'Name': 'Nat', 'Marks': 70.88}, 1: {'Name': 'Harry', 'Marks': 85.9}, 2: {'Name': 'Joe', 'Marks': 91.45}}<\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-dataframe-to-dict-with-one-column-as-the-key\">DataFrame to dict with one column as the key<\/h2>\n\n\n\n<p>In this section, we target the use case when we need to create a <code>dict<\/code> from DataFrame where one column as a key of <code>dict<\/code> and other columns as the value of the <code>dict<\/code>.<\/p>\n\n\n\n<p>Suppose we have student DataFrame with two columns, student&#8217;s <strong>Name,<\/strong> and student&#8217;s <strong>Marks<\/strong>. And we need to store each student&#8217;s data in the <code>dict<\/code> where the student name is the Key and their marks as a Value of the <code>dict<\/code>. <\/p>\n\n\n\n<p>We can do it in various ways, as shown below.<\/p>\n\n\n\n<ul>\n<li>Using <code>df.set_index('Col1').to_dict()['Col2']<\/code><\/li>\n\n\n\n<li>Using <code>zip(df.Col1, df.Col2)<\/code><\/li>\n\n\n\n<li>Using <code>df.set_index('Col1').T.to_dict('list')<\/code><\/li>\n<\/ul>\n\n\n\n<p><strong>Example<\/strong><\/p>\n\n\n\n<p>Below example uses <code>df.set_index('Col1').to_dict()['Col2']<\/code> to get the expected output.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code8\"  id=\"norun\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-13\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n\n<span class=\"hljs-comment\"># create dataframe from csv<\/span>\nstudentDf = pd.read_csv(<span class=\"hljs-string\">\"StudentData.csv\"<\/span>)\nprint(studentDf)\n\n<span class=\"hljs-comment\"># create dict with Name as key and marks as value<\/span>\nstudentDict = studentDf.set_index(<span class=\"hljs-string\">'Name'<\/span>).to_dict()&#91;<span class=\"hljs-string\">'Marks'<\/span>]\n\nprint(studentDict)\n<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-13\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code8', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><\/div>\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">    Name  Marks\n0    Nat  70.88\n1  Harry  85.90\n2    Joe  91.45\n\n{'Nat': 70.88, 'Harry': 85.9, 'Joe': 91.45}<\/pre>\n\n\n\n<p>We can also achieve the same result using <code>zip()<\/code> the function.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code9\"  id=\"norun\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-14\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-comment\"># create dict with Name as key and marks as value<\/span>\nstudentDict = dict(zip(studentDf.Name, studentDf.Marks))<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-14\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code9', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><\/div>\n\n\n<p>If we want to collect the <strong>column data into the list<\/strong>, it can be done by applying <strong>transpose<\/strong> operation on the DataFrame and then converting it into dict.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code10\"  id=\"norun\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-15\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n\n<span class=\"hljs-comment\"># create dataframe from csv<\/span>\nstudentDf = pd.read_csv(<span class=\"hljs-string\">\"StudentData.csv\"<\/span>)\nprint(studentDf)\n\n<span class=\"hljs-comment\"># create dict with Name as key and marks as value<\/span>\nstudentDict = studentDf.set_index(<span class=\"hljs-string\">'Name'<\/span>).T.to_dict(<span class=\"hljs-string\">'list'<\/span>)\nprint(studentDict)<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-15\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code10', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><\/div>\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">    Name  Marks\n0    Nat  70.88\n1  Harry  85.90\n2    Joe  91.45\n\n{'Nat': [70.88], 'Harry': [85.9], 'Joe': [91.45]}<\/pre>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-dataframe-to-dict-using-into-parameter\">DataFrame to dict using <code>into<\/code> parameter<\/h2>\n\n\n\n<p>While converting a DataFrame to <code>dict<\/code> if we need output <code>dict<\/code> to be of a particular type, we can use the parameter&nbsp;into&nbsp;of <code>DataFrame.to_dict()<\/code> function. We can specify the class name or the instance of the class for the resultant <code>dict<\/code>.<\/p>\n\n\n\n<p><strong>Example<\/strong><\/p>\n\n\n\n<p>In the below example, we converted DataFrame to the <code>dict<\/code> of type <strong>OrderedDict<\/strong>.<\/p>\n\n\n<div class=\"hljstoolbar\"><pre id=\"code11\"  id=\"norun\" class=\"wp-block-code language-python\" aria-describedby=\"shcb-language-16\" data-shcb-language-name=\"Python\" data-shcb-language-slug=\"python\"><span><code class=\"hljs language-python\"><span class=\"hljs-comment\"># import pandas library<\/span>\n<span class=\"hljs-keyword\">from<\/span> collections <span class=\"hljs-keyword\">import<\/span> OrderedDict\n<span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n\n<span class=\"hljs-comment\"># create dataframe from csv<\/span>\nstudentDf = pd.read_csv(<span class=\"hljs-string\">\"StudentData.csv\"<\/span>)\nprint(studentDf)\n\n<span class=\"hljs-comment\"># convert dataframe to ordered dict<\/span>\nstudentDict = studentDf.to_dict(into=OrderedDict)\nprint(studentDict)\n<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-16\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">Python<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">python<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre><button class=\"hljs-copy-button\" onclick=\"copy_code('code11', this);\"><i class=\"far fa-copy1\" aria-hidden=\"true\"><\/i><\/button><\/div>\n\n\n<p><strong>Output:<\/strong><\/p>\n\n\n\n<pre class=\"wp-block-preformatted\">    Name  Marks\n0    Nat  70.88\n1  Harry  85.90\n2    Joe  91.45\n\nOrderedDict([('Name', OrderedDict([(0, 'Nat'), (1, 'Harry'), (2, 'Joe')])), ('Marks', OrderedDict([(0, 70.88), (1, 85.9), (2, 91.45)]))])<\/pre>\n","protected":false},"excerpt":{"rendered":"<p>In this article, you will learn how to convert pandas DataFrame into a Python dictionary. It explains creating different kinds of dictionaries from pandas DataFrame. Data Analyst needs to collect the data from heterogeneous sources like CSV files or SQL tables or Python data structures like a dictionary, list, etc. Such data is converted into [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","footnotes":""},"categories":[21,22],"tags":[40],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.6 (Yoast SEO v22.6) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Convert Pandas DataFrame to Python dictionary<\/title>\n<meta name=\"description\" content=\"Convert pandas DataFrame into a Python dictionary. 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