{"id":4626,"date":"2023-10-25T11:41:05","date_gmt":"2023-10-25T06:11:05","guid":{"rendered":"https:\/\/python-programs.com\/?p=4626"},"modified":"2023-11-10T11:58:28","modified_gmt":"2023-11-10T06:28:28","slug":"how-to-get-check-data-types-of-dataframe-columns-in-python-pandas","status":"publish","type":"post","link":"https:\/\/python-programs.com\/how-to-get-check-data-types-of-dataframe-columns-in-python-pandas\/","title":{"rendered":"How to get &#038; check data types of Dataframe columns in Python Pandas"},"content":{"rendered":"<h2>How to get &amp; check data types of dataframes columns in python pandas ?<\/h2>\n<p>In this article we will discuss different ways to get the data type of single or multiple columns.<\/p>\n<h3>Use Dataframe.dtype to get data types of columns in Dataframe :<\/h3>\n<p>In python\u2019s pandas module provides Dataframe class as a container for storing and manipulating two-dimensional data which provides an attribute to get the data type information of each column.<\/p>\n<p>This <code>Dataframe.dtype<\/code> returns a series mentioned with the data type of each column.<\/p>\n<p>Let\u2019s try with an example:<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">#Program :\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n#list of tuples\r\ngame = [('riya',37,'delhi','cat','rose'),\r\n\u00a0\u00a0 ('anjali',28,'agra','dog','lily'),\r\n\u00a0\u00a0 ('tia',42,'jaipur','elephant','lotus'),\r\n\u00a0\u00a0 ('kapil',51,'patna','cow','tulip'),\r\n\u00a0\u00a0 ('raj',30,'banglore','lion','orchid')]\r\n#Create a dataframe object\r\ndf = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])\r\nprint(df)<\/pre>\n<pre>Output:\r\n \u00a0\u00a0\u00a0 Name\u00a0  Age\u00a0\u00a0\u00a0\u00a0 Place\u00a0\u00a0\u00a0  Animal\u00a0    Flower\r\na\u00a0\u00a0\u00a0 riya\u00a0\u00a0    37\u00a0\u00a0\u00a0\u00a0    delhi\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 cat\u00a0\u00a0\u00a0       rose\r\nb\u00a0  anjali\u00a0\u00a0  28\u00a0\u00a0\u00a0\u00a0\u00a0   agra\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 dog\u00a0\u00a0\u00a0       lily\r\nc\u00a0\u00a0\u00a0\u00a0 tia\u00a0\u00a0    42\u00a0\u00a0\u00a0     jaipur\u00a0   elephant\u00a0\u00a0   lotus\r\nd\u00a0\u00a0 kapil\u00a0\u00a0  51\u00a0\u00a0\u00a0\u00a0   patna\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 cow\u00a0\u00a0        tulip\r\ne\u00a0\u00a0\u00a0\u00a0 raj\u00a0\u00a0    30\u00a0    banglore\u00a0\u00a0\u00a0\u00a0\u00a0lion\u00a0      orchid<\/pre>\n<p>This is the contents of the dataframe. Now let\u2019s fetch the data types of each column in dataframe.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">#Program :\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n#list of tuples\r\ngame = [('riya',37,'delhi','cat','rose'),\r\n\u00a0\u00a0 ('anjali',28,'agra','dog','lily'),\r\n\u00a0\u00a0 ('tia',42,'jaipur','elephant','lotus'),\r\n\u00a0\u00a0 ('kapil',51,'patna','cow','tulip'),\r\n\u00a0\u00a0 ('raj',30,'banglore','lion','orchid')]\r\n#Create a dataframe object\r\ndf = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])\r\nDataType = df.dtypes\r\nprint('Data type of each column:')\r\nprint(DataType)<\/pre>\n<pre>Output:\r\nData type of each column:\r\nName\u00a0\u00a0\u00a0\u00a0\u00a0 object\r\nAge\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0   int64\r\nPlace\u00a0\u00a0\u00a0\u00a0   object\r\nAnimal\u00a0\u00a0\u00a0 object\r\nFlower\u00a0\u00a0\u00a0 object\r\ndtype:     object<\/pre>\n<h3>Get Data types of dataframe columns as dictionary :<\/h3>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">#Program :\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n#list of tuples\r\ngame = [('riya',37,'delhi','cat','rose'),\r\n\u00a0\u00a0 ('anjali',28,'agra','dog','lily'),\r\n\u00a0\u00a0 ('tia',42,'jaipur','elephant','lotus'),\r\n\u00a0\u00a0 ('kapil',51,'patna','cow','tulip'),\r\n\u00a0\u00a0 ('raj',30,'banglore','lion','orchid')]\r\n#Create a dataframe object\r\ndf = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])\r\n#get a dictionary containing the pairs of column names and data types object\r\nDataTypeDict = dict(df.dtypes)\r\nprint('Data type of each column :')\r\nprint(DataTypeDict)<\/pre>\n<pre>Output:\r\nData type of each column  :{'Name': dtype('O'), 'Age': dtype('int64'), 'Place': dtype('O'), 'Animal': dtype('O'), 'Flower': dtype('O')}<\/pre>\n<h3>Get the data type of a single column in dataframe :<\/h3>\n<p>By using<code> Dataframe.dtype<\/code>s we can also get the data type of a single column from a series of objects.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">#Program :\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n#list of tuples\r\ngame = [('riya',37,'delhi','cat','rose'),\r\n\u00a0\u00a0 ('anjali',28,'agra','dog','lily'),\r\n\u00a0\u00a0 ('tia',42,'jaipur','elephant','lotus'),\r\n\u00a0\u00a0 ('kapil',51,'patna','cow','tulip'),\r\n\u00a0\u00a0 ('raj',30,'banglore','lion','orchid')]\r\n#Create a dataframe object\r\ndf = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])\r\n#get a dictionary containing the pairs of column names and data types object\r\nDataTypeObj = df.dtypes['Age']\r\nprint('Data type of each column Age : ')\r\nprint(DataTypeObj)<\/pre>\n<pre>Output :\r\nData type of each column Age :int64<\/pre>\n<h3>Get list of pandas dataframe column names based on data types :<\/h3>\n<p>Suppose, we want a list of column names based on datatypes. Let&#8217;s take an example program whose data type is object(string).<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import pandas as pd\r\nimport numpy as np\r\n#list of tuples\r\ngame = [('riya',37,'delhi','cat','rose'),\r\n('anjali',28,'agra','dog','lily'),\r\n('tia',42,'jaipur','elephant','lotus'),\r\n('kapil',51,'patna','cow','tulip'),\r\n('raj',30,'banglore','lion','orchid')]\r\n#Create a dataframe object\r\ndf = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])\r\n\r\n# Get\u00a0 columns whose data type is object means string\r\nfilteredColumns = df.dtypes[df.dtypes == np.object]\r\n# list of columns whose data type is object means string\r\nlistOfColumnNames = list(filteredColumns.index)\r\nprint(listOfColumnNames)<\/pre>\n<pre>Output:\r\n['Name', 'Place', 'Animal', 'Flower']<\/pre>\n<h3>Get data types of a dataframe using Dataframe.info() :<\/h3>\n<p><code>Dataframe.info()<\/code> function is used to get simple summary of a dataframe. By using this method we can get information about a dataframe including the index dtype and column dtype, non-null values and memory usage.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">#program :\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n#list of tuples\r\ngame = [('riya',37,'delhi','cat','rose'),\r\n('anjali',28,'agra','dog','lily'),\r\n('tia',42,'jaipur','elephant','lotus'),\r\n('kapil',51,'patna','cow','tulip'),\r\n('raj',30,'banglore','lion','orchid')]\r\n#Create a dataframe object\r\ndf = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])\r\ndf.info()<\/pre>\n<pre>Output:\r\n&lt;class 'pandas.core.frame.DataFrame'&gt;\r\nIndex: 5 entries, a to e\r\nData columns (total 5 columns): \r\n#\u00a0\u00a0 Column\u00a0 Non-Null Count\u00a0 Dtype \r\n---\u00a0 ------\u00a0 --------------\u00a0 -----  \r\na \u00a0 Name\u00a0\u00a0\u00a0  5 non-null\u00a0\u00a0\u00a0\u00a0\u00a0 object \r\nb \u00a0 Age\u00a0\u00a0\u00a0\u00a0    5 non-null\u00a0\u00a0\u00a0\u00a0\u00a0 int64  \r\nc \u00a0 Place\u00a0\u00a0    5 non-null\u00a0\u00a0\u00a0\u00a0\u00a0 object \r\nd \u00a0 Animal\u00a0  5 non-null\u00a0\u00a0\u00a0\u00a0\u00a0 object \r\ne \u00a0 Flower\u00a0  5 non-null\u00a0\u00a0\u00a0\u00a0\u00a0 object\r\ndtypes: int64(1), object(4)\r\nmemory usage: 240.0+ bytes<\/pre>\n","protected":false},"excerpt":{"rendered":"<p>How to get &amp; check data types of dataframes columns in python pandas ? In this article we will discuss different ways to get the data type of single or multiple columns. Use Dataframe.dtype to get data types of columns in Dataframe : In python\u2019s pandas module provides Dataframe class as a container for storing &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/python-programs.com\/how-to-get-check-data-types-of-dataframe-columns-in-python-pandas\/\"> <span class=\"screen-reader-text\">How to get &#038; check data types of Dataframe columns in Python Pandas<\/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>How to get &amp; check data types of Dataframe columns in Python Pandas - 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\/how-to-get-check-data-types-of-dataframe-columns-in-python-pandas\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How to get &amp; check data types of Dataframe columns in Python Pandas - Python Programs\" \/>\n<meta property=\"og:description\" content=\"How to get &amp; check data types of dataframes columns in python pandas ? 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In this article we will discuss different ways to get the data type of single or multiple columns. 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