{"id":57364,"date":"2019-06-10T17:48:20","date_gmt":"2019-06-10T12:18:20","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=57364"},"modified":"2019-06-12T10:23:56","modified_gmt":"2019-06-12T04:53:56","slug":"pandas-datetime","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/pandas-datetime\/","title":{"rendered":"Pandas Datetime Functionality | How Timedeltas &amp; Time Series Works"},"content":{"rendered":"<p>You will come across time and date series when working with data regularly. Pandas have often proved to be very useful when working with such data.\u00a0It provides you a number of tools which you can use to perform all necessary tasks on such data. This tutorial is specially designed to explore different types of operations performed with Pandas Datetime functionality.<\/p>\n<p>By the end of this article, you will be skilled with Pandas timedelta, time series, a DateTimeIndex object in pandas and many more. So, <em>don&#8217;t waste your time and grab the opportunity<\/em>.<\/p>\n<h2>1. How to create Pandas datetime object?<\/h2>\n<p>To create pandas datetime object, we will start with importing pandas-<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt;import pandas as pd<\/pre>\n<p>This allows us to create an index set according to the time frame.<\/p>\n<p>To create Pandas DateTime object we use the <strong>.date_range function<\/strong>. It has the following parameter:<\/p>\n<ul>\n<li><strong>First parameter<\/strong>: start= \u2018dd\/mm\/yyyy\u2019.<\/li>\n<li><strong>Second parameter:<\/strong> periods= n, where n is no of periods or date time elements you need.<\/li>\n<li><strong>Third parameter<\/strong>: freq= \u2018x\u2019, where \u2018x\u2019 can be \u2018H\u2019(hour), \u2018D\u2019(days), \u2018W\u2019(weeks), \u2018M\u2019(month), \u2018Y\u2019(years), etc.<\/li>\n<\/ul>\n<p><em><strong>Before moving ahead, you should know the <a href=\"https:\/\/data-flair.training\/blogs\/basic-functionality-in-pandas\/\">Basic Functionality of Pandas<\/a><\/strong><\/em><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair = pd.date_range(start='1\/1\/2011', periods = 10, freq ='H')\r\n&gt;&gt;&gt; dataflair<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p>DatetimeIndex([&#8216;2011-01-01 00:00:00&#8217;, &#8216;2011-01-01 01:00:00&#8217;,<br \/>\n&#8216;2011-01-01 02:00:00&#8217;, &#8216;2011-01-01 03:00:00&#8217;,<br \/>\n&#8216;2011-01-01 04:00:00&#8217;, &#8216;2011-01-01 05:00:00&#8217;,<br \/>\n&#8216;2011-01-01 06:00:00&#8217;, &#8216;2011-01-01 07:00:00&#8217;,<br \/>\n&#8216;2011-01-01 08:00:00&#8217;, &#8216;2011-01-01 09:00:00&#8242;],<br \/>\ndtype=&#8217;datetime64[ns]&#8217;, freq=&#8217;H&#8217;)<\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Create-pandas-datetime-object.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58702 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Create-pandas-datetime-object.jpg\" alt=\"Create pandas datetime object\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Create-pandas-datetime-object.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Create-pandas-datetime-object-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Create-pandas-datetime-object-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Create-pandas-datetime-object-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Create-pandas-datetime-object-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Create-pandas-datetime-object-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<h4>How to print date in yyyy-mm-dd format?<\/h4>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_rng = pd.DataFrame() \r\n&gt;&gt;&gt; dataflair_rng['date'] = pd.date_range('1\/1\/2011', periods = 72, freq ='H')\r\n&gt;&gt;&gt; dataflair_rng[:5]<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/print-data-in-format-in-Pandas.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58703 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/print-data-in-format-in-Pandas.jpg\" alt=\"print data in format in Pandas\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/print-data-in-format-in-Pandas.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/print-data-in-format-in-Pandas-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/print-data-in-format-in-Pandas-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/print-data-in-format-in-Pandas-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/print-data-in-format-in-Pandas-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/print-data-in-format-in-Pandas-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<p><em><strong>Don&#8217;t miss the opportunity to get a complete guide for<a href=\"https:\/\/data-flair.training\/blogs\/pandas-dataframe\/\"> Pandas Dataframe<\/a><\/strong><\/em><\/p>\n<h2>2. Breaking the time and date into separate features<\/h2>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_rng['year'] = dataflair_rng['date'].dt.year #creates \u2018year\u2019 column and extracts year \r\n&gt;&gt;&gt; dataflair_rng['month'] = dataflair_rng['date'].dt.month #creates \u2018month\u2019 column and extracts month\r\n&gt;&gt;&gt; dataflair_rng['day'] = dataflair_rng['date'].dt.day #creates \u2018day\u2019 column and extracts day\r\n&gt;&gt;&gt; dataflair_rng['hour'] = dataflair_rng['date'].dt.hour #creates \u2018hour\u2019 column and extracts hour\r\n&gt;&gt;&gt; dataflair_rng['minute'] = dataflair_rng['date'].dt.minute #creates \u2018minute\u2019 column and extracts minute\r\n&gt;&gt;&gt; dataflair_rng.head(3)<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Breaking-the-time-and-date-into-separate-features-in-Pandas.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58704 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Breaking-the-time-and-date-into-separate-features-in-Pandas.jpg\" alt=\"How to Break time and date into separate features\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Breaking-the-time-and-date-into-separate-features-in-Pandas.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Breaking-the-time-and-date-into-separate-features-in-Pandas-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Breaking-the-time-and-date-into-separate-features-in-Pandas-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Breaking-the-time-and-date-into-separate-features-in-Pandas-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Breaking-the-time-and-date-into-separate-features-in-Pandas-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Breaking-the-time-and-date-into-separate-features-in-Pandas-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<h2>3. How to get the present time as a timestamp in Pandas?<\/h2>\n<p>The function <strong>.Timestamp.now()<\/strong> gives us the current time and date details.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_time = pd.Timestamp.now()\r\n&gt;&gt;&gt; dataflair_time<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/time-as-a-timestamp-in-Pandas.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58705 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/time-as-a-timestamp-in-Pandas.jpg\" alt=\"time as a timestamp in Pandas\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/time-as-a-timestamp-in-Pandas.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/time-as-a-timestamp-in-Pandas-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/time-as-a-timestamp-in-Pandas-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/time-as-a-timestamp-in-Pandas-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/time-as-a-timestamp-in-Pandas-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/time-as-a-timestamp-in-Pandas-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<h3>3.1 Getting all the features separately from the timestamp<\/h3>\n<p>Using the<strong> .year, .month, .week, .day, .hour, .minute functions<\/strong>, we can extract the respective features from the Pandas timestamp.<\/p>\n<p><strong>3.1.1. Year<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_time.year<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p>2019<\/p>\n<p><strong>3.1.2. Month<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_time.month<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<h5><strong>6<\/strong><\/h5>\n<p><strong>3.1.3. Day<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_time.day<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<h5><strong>6<\/strong><\/h5>\n<p><strong>3.1.4. Hour<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_time.hour<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<h5><strong>19<\/strong><\/h5>\n<p><strong>3.1.5. Minute<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_time.minute<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<h5><strong>49<\/strong><\/h5>\n<p><strong>3.1.6. Second<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_time.second \r\n<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p>27<\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/features-separately-from-the-timestamp-in-Pandas.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58706 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/features-separately-from-the-timestamp-in-Pandas.jpg\" alt=\"features separately from the timestamp in Pandas\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/features-separately-from-the-timestamp-in-Pandas.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/features-separately-from-the-timestamp-in-Pandas-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/features-separately-from-the-timestamp-in-Pandas-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/features-separately-from-the-timestamp-in-Pandas-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/features-separately-from-the-timestamp-in-Pandas-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/features-separately-from-the-timestamp-in-Pandas-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<h2>4.\u00a0Pandas DateTimeIndex object<\/h2>\n<p>Extracting the elements of date and time from the DateTimeIndex object in Pandas.\u00a0We can extract the date and time values present in each entry of the object.<\/p>\n<p>First, we create a Pandas DateTimeIndex object.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_dx = pd.DatetimeIndex(start ='2000-01-10 06:30', freq ='W',periods = 3, tz ='Asia\/Calcutta') \r\n&gt;&gt;&gt; dataflair_dx<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Creating-Pandas-DateTimeIndex-object.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58707 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Creating-Pandas-DateTimeIndex-object.jpg\" alt=\"Creating Pandas DateTimeIndex object\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Creating-Pandas-DateTimeIndex-object.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Creating-Pandas-DateTimeIndex-object-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Creating-Pandas-DateTimeIndex-object-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Creating-Pandas-DateTimeIndex-object-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Creating-Pandas-DateTimeIndex-object-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Creating-Pandas-DateTimeIndex-object-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<ul>\n<li><strong>Printing the date attributes<\/strong><\/li>\n<\/ul>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_dx.date<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-Print-the-date-attributes-in-Pandas.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58710 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-Print-the-date-attributes-in-Pandas.jpg\" alt=\"Print the date attributes in Pandas\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-Print-the-date-attributes-in-Pandas.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-Print-the-date-attributes-in-Pandas-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-Print-the-date-attributes-in-Pandas-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-Print-the-date-attributes-in-Pandas-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-Print-the-date-attributes-in-Pandas-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-Print-the-date-attributes-in-Pandas-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<ul>\n<li><strong>Printing the time attributes<\/strong><\/li>\n<\/ul>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_dx.time<\/pre>\n<p>\ufffc<strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-print-the-time-attributes-in-Pandas-Datetime.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58709 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-print-the-time-attributes-in-Pandas-Datetime.jpg\" alt=\"How to print the time attributes in Pandas Datetime\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-print-the-time-attributes-in-Pandas-Datetime.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-print-the-time-attributes-in-Pandas-Datetime-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-print-the-time-attributes-in-Pandas-Datetime-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-print-the-time-attributes-in-Pandas-Datetime-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-print-the-time-attributes-in-Pandas-Datetime-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-print-the-time-attributes-in-Pandas-Datetime-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<h2>5. Pandas TimeDelta<\/h2>\n<p><em>TimeDelta denotes the difference or change in time, in terms of days, hours, minutes and seconds<\/em>. Using <a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/version\/0.23.4\/generated\/pandas.Timedelta.html\">Pandas TimeDelta<\/a> functions, we can convert strings and integers to TimeDeltas.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt;dataflair_time= pd.Timedelta('17 days 7 hours 45 minutes 56 seconds') #with strings\r\n&gt;&gt;&gt;dataflair_time<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-use-Pandas-TimeDelta.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58711 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-use-Pandas-TimeDelta.jpg\" alt=\"Using Pandas Timedeltas\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-use-Pandas-TimeDelta.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-use-Pandas-TimeDelta-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-use-Pandas-TimeDelta-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-use-Pandas-TimeDelta-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-use-Pandas-TimeDelta-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/How-to-use-Pandas-TimeDelta-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_time2= pd.Timedelta(19,unit=\u2019h\u2019)\r\n&gt;&gt;&gt; dataflair_time2<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/convert-strings-and-integers-to-TimeDeltas.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58721 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/convert-strings-and-integers-to-TimeDeltas.jpg\" alt=\"convert strings and integers to TimeDeltas\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/convert-strings-and-integers-to-TimeDeltas.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/convert-strings-and-integers-to-TimeDeltas-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/convert-strings-and-integers-to-TimeDeltas-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/convert-strings-and-integers-to-TimeDeltas-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/convert-strings-and-integers-to-TimeDeltas-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/convert-strings-and-integers-to-TimeDeltas-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<p><strong>We can use data offsets with TimeDeltas in Pandas<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_time3= pd.Timedelta(days=\u20199\u2019,minutes=\u201945\u2019)\r\n&gt;&gt;&gt; dataflair_time3<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/data-offsets-with-TimeDeltas-in-Pandas.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58720 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/data-offsets-with-TimeDeltas-in-Pandas.jpg\" alt=\"data offsets with TimeDeltas in Pandas\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/data-offsets-with-TimeDeltas-in-Pandas.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/data-offsets-with-TimeDeltas-in-Pandas-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/data-offsets-with-TimeDeltas-in-Pandas-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/data-offsets-with-TimeDeltas-in-Pandas-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/data-offsets-with-TimeDeltas-in-Pandas-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/data-offsets-with-TimeDeltas-in-Pandas-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<p><em><strong>It&#8217;s time to know about <a href=\"https:\/\/data-flair.training\/blogs\/pandas-series\/\">Pandas Series<\/a><\/strong><\/em><\/p>\n<h2>6. Pandas Time Series<\/h2>\n<p>To index data by timestamps, we require Pandas time series. Let&#8217;s discuss the below example to understand it-<\/p>\n<p>Let&#8217;s take a dataset:<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_dict= {'date': ['2018-06-02 12:30:04', '2018-07-02 01:27:03', '2018-07-15 17:23:12', '2018-07-30 05:34:05', '2018-08-04 19:17:23', '2018-08-12 03:12:34', '2018-09-03 09:42:05', '2018-09-03 15:54:08', '2018-09-04 18:47:16', '2018-09-04 17:37:25'], 'Sales': [134, 225, 216, 65, 15, 114, 236, 215, 92, 61]}\r\n&gt;&gt;&gt; dataflair_df = pd.DataFrame(dataflair_dict, columns = ['date', 'sales'])\r\n&gt;&gt;&gt; dataflair_df<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Pandas-Time-Series.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58722 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Pandas-Time-Series.jpg\" alt=\"Pandas Time Series\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Pandas-Time-Series.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Pandas-Time-Series-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Pandas-Time-Series-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Pandas-Time-Series-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Pandas-Time-Series-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Pandas-Time-Series-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<h4>6.1 How to convert the dates to a TimeSeries object in Pandas?<\/h4>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_df['date'] = pd.to_datetime(dataflair_df['date'])\r\n&gt;&gt;&gt; dataflair_df.index = dataflair_df['date']\r\n&gt;&gt;&gt; del dataflair_df['date']\r\n&gt;&gt;&gt; dataflair_df<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Convert-the-dates-to-a-TimeSeries-object.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58723 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Convert-the-dates-to-a-TimeSeries-object.jpg\" alt=\"Convert the dates to a TimeSeries object\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Convert-the-dates-to-a-TimeSeries-object.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Convert-the-dates-to-a-TimeSeries-object-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Convert-the-dates-to-a-TimeSeries-object-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Convert-the-dates-to-a-TimeSeries-object-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Convert-the-dates-to-a-TimeSeries-object-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Convert-the-dates-to-a-TimeSeries-object-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<p><strong>We can use TimeSeries properties to view specific events, like:<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_df['2018-08']<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Using-use-TimeSeries-properties.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58724 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Using-use-TimeSeries-properties.jpg\" alt=\" use TimeSeries properties\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Using-use-TimeSeries-properties.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Using-use-TimeSeries-properties-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Using-use-TimeSeries-properties-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Using-use-TimeSeries-properties-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Using-use-TimeSeries-properties-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/Using-use-TimeSeries-properties-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<p><strong>To view our TimeSeries object, we can use:<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"null\">&gt;&gt;&gt; dataflair_df.index<\/pre>\n<p><strong>Output-<\/strong><\/p>\n<p><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/view-our-TimeSeries-object-in-Pandas.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-58725 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/view-our-TimeSeries-object-in-Pandas.jpg\" alt=\"view our TimeSeries object in Pandas\" width=\"1366\" height=\"740\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/view-our-TimeSeries-object-in-Pandas.jpg 1366w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/view-our-TimeSeries-object-in-Pandas-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/view-our-TimeSeries-object-in-Pandas-300x163.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/view-our-TimeSeries-object-in-Pandas-768x416.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/view-our-TimeSeries-object-in-Pandas-1024x555.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2019\/06\/view-our-TimeSeries-object-in-Pandas-520x282.jpg 520w\" sizes=\"auto, (max-width: 1366px) 100vw, 1366px\" \/><\/a><\/p>\n<h2>Summary<\/h2>\n<p>These were all the functions that you can manipulate with the help of Pandas datetime functionality. In addition, we discussed the timedelta and time series with the help of examples. Hope, you liked the article and practiced it well.<\/p>\n<p><em><strong>You can represent your data in the form of charts with the help of <a href=\"https:\/\/data-flair.training\/blogs\/pandas-visualization-tutorial\/\">Pandas Visualization<\/a>.<\/strong><\/em><\/p>\n<p>Don&#8217;t forget to comment below. We will be glad to know about your experience with us!<span hidden class=\"__iawmlf-post-loop-links\" data-iawmlf-links=\"[{&quot;id&quot;:1513,&quot;href&quot;:&quot;https:\\\/\\\/pandas.pydata.org\\\/pandas-docs\\\/version\\\/0.23.4\\\/generated\\\/pandas.Timedelta.html&quot;,&quot;archived_href&quot;:&quot;http:\\\/\\\/web-wp.archive.org\\\/web\\\/20250428093249\\\/https:\\\/\\\/pandas.pydata.org\\\/pandas-docs\\\/version\\\/0.23.4\\\/generated\\\/pandas.Timedelta.html&quot;,&quot;redirect_href&quot;:&quot;&quot;,&quot;checks&quot;:[{&quot;date&quot;:&quot;2025-12-09 09:53:32&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-02-13 12:18:18&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-03-04 16:45:47&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-04-22 15:02:01&quot;,&quot;http_code&quot;:404}],&quot;broken&quot;:false,&quot;last_checked&quot;:{&quot;date&quot;:&quot;2026-04-22 15:02:01&quot;,&quot;http_code&quot;:404},&quot;process&quot;:&quot;done&quot;}]\"><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>You will come across time and date series when working with data regularly. Pandas have often proved to be very useful when working with such data.\u00a0It provides you a number of tools which you&#46;&#46;&#46;<\/p>\n","protected":false},"author":5,"featured_media":58729,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19475],"tags":[20077,20080,20078,20079],"class_list":["post-57364","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-pandas","tag-pandas-datetime-tutorial","tag-pandas-time-series","tag-pandas-timestamp","tag-timedelta-in-pandas"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Pandas Datetime Functionality | How Timedeltas &amp; Time Series Works - DataFlair<\/title>\n<meta name=\"description\" content=\"Learn how Pandas datetime functionality works with examples to manipualte your data. Also, explore Pandas time series, timedeltas, timestamps with their practical applications\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/pandas-datetime\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas Datetime Functionality | How Timedeltas &amp; Time Series Works - DataFlair\" \/>\n<meta property=\"og:description\" content=\"Learn how Pandas datetime functionality works with examples to manipualte your data. 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