To get the UTC Offset Time, use the timestamp.utcoffset(). At first, import the required libraries −import pandas as pdCreating a timestamptimestamp = pd.Timestamp('2021-10-16T15:12:34.261811624', tz='UTC') New timestamp with UTC day and timetimestamp.utcnow()Get the UTC offset timetimestamp.utcoffset() ExampleFollowing is the code import pandas as pd # creating a timestamp timestamp = pd.Timestamp('2021-10-16T15:12:34.261811624', tz='UTC') # display the Timestamp print("Timestamp...", timestamp) # new timestamp with UTC day and time print("UTC day and time...", timestamp.utcnow()) # Get the UTC offset time print("UTC offset time...", timestamp.utcoffset())OutputThis will produce the following code Timestamp...  2021-10-16 15:12:34.261811624+00:00 UTC day and time... 2021-10-03 07:56:44.685816+00:00 ... Read More

To return a new Timestamp representing UTC day and time, use the timestamp.utcnow() method. At first, import the required libraries −import pandas as pdCreating a timestamptimestamp = pd.Timestamp('2021-10-16T15:12:34.261811624', tz='UTC') New timestamp with UTC day and timetimestamp.utcnow()ExampleFollowing is the code import pandas as pd # creating a timestamp timestamp = pd.Timestamp('2021-10-16T15:12:34.261811624', tz='UTC') # display the Timestamp print("Timestamp...", timestamp) # new timestamp with UTC day and time print("UTC day and time...", timestamp.utcnow())OutputThis will produce the following code Timestamp... 2021-10-16 15:12:34.261811624+00:00 UTC day and time... 2021-10-03 07:56:08.901294+00:00Read More

To construct a naive UTC datetime from a POSIX timestamp, use the timestamp.utcfromtimestamp() method. Pass the POSIX as an argument.At first, import the required libraries −import pandas as pdCreate a timestamptimestamp = pd.Timestamp('2021-09-14T15:12:34.261811624') Constructing a naive UTC datetime from a POSIX timestamp. POSIX is passed as an argumenttimestamp.utcfromtimestamp(1631717502)ExampleFollowing is the code import pandas as pd # creating a timestamp timestamp = pd.Timestamp('2021-09-14T15:12:34.261811624') # display the Timestamp print("Timestamp...", timestamp) # constructing a naive UTC datetime from a POSIX timestamp # POSIX is passed as an argument print("Construct UTC Datetime...", timestamp.utcfromtimestamp(1631717502))OutputThis will produce the following code Timestamp...  2021-09-14 15:12:34.261811624 ... Read More

To convert naive Timestamp to local time zone, use the timestamp.tz_locale(). Within that, set the timezone using the tz parameter.At first, import the required libraries −import pandas as pdCreating a naive timestamptimestamp = pd.Timestamp('2021-09-14T15:12:34.261811624') Add the timezonetimestamp.tz_localize(tz='Australia/Brisbane')ExampleFollowing is the code import pandas as pd # creating a naive timestamp timestamp = pd.Timestamp('2021-09-14T15:12:34.261811624') # display the Timestamp print("Timestamp...", timestamp) # add a timezone print("Timestamp to local time zone...", timestamp.tz_localize(tz='Australia/Brisbane'))OutputThis will produce the following code Timestamp... 2021-09-14 15:12:34.261811624 Timestamp to local time zone... 2021-09-14 15:12:34.261811624+10:00Read More

Convert Timestamp to another time zone, use the timestamp.tz_convert(). Set the time zone as the parameter. At first, import the required libraries −import pandas as pdCreate the timestamp object in Pandas. We have also set the timezonetimestamp = pd.Timestamp('2021-10-14T15:12:34.261811624', tz='US/Eastern') Convert timezone of timestamptimestamp.tz_convert('Australia/Brisbane'))ExampleFollowing is the code import pandas as pd # set the timestamp object in Pandas # we have also set the timezone timestamp = pd.Timestamp('2021-10-14T15:12:34.261811624', tz='US/Eastern') # display the Timestamp print("Timestamp...", timestamp) # convert timezone print("Convert the Timestamp timezone...", timestamp.tz_convert('Australia/Brisbane'))OutputThis will produce the following code Timestamp... 2021-10-14 15:12:34.261811624-04:00 Convert the Timestamp timezone... ... Read More

To return proleptic Gregorian ordinal, use the timestamp.toordinal() method. At first, import the required libraries −import pandas as pdCreate the timestamp object in Pandastimestamp = pd.Timestamp(2021, 9, 18, 11, 50, 20, 33) Return proleptic Gregorian ordinal. Example: January 1 of year 1 is day 1timestamp.toordinal()ExampleFollowing is the code import pandas as pd # set the timestamp object in Pandas timestamp = pd.Timestamp(2021, 9, 18, 11, 50, 20, 33) # display the Timestamp print("Timestamp...", timestamp) # Return proleptic Gregorian ordinal. # Example: January 1 of year 1 is day 1. print("Gregorian ordinal...", timestamp.toordinal())OutputThis will produce the following code Timestamp... 2021-09-18 11:50:20.000033 Gregorian ordinal... 738051

Get the current date and time from Timestamp object, use the timestamp.today() method.At first, import the required libraries −import pandas as pd import datetimeCreate the timestamp in Pandastimestamp = pd.Timestamp(datetime.datetime(2021, 10, 10)) Display the Timestampprint("Timestamp: ", timestamp)Getting the current date and timeres = timestamp.today() ExampleFollowing is the code import pandas as pd import datetime # set the timestamp in Pandas timestamp = pd.Timestamp(datetime.datetime(2021, 10, 10)) # display the Timestamp print("Timestamp: ", timestamp) # display the day from given timestamp print("Day Name:", timestamp.day_name()) # getting the current date and time res = timestamp.today() # display the ... Read More

To convert a Timestamp object to a native Python datetime object, use the timestamp.to_pydatetime() method.At first, import the required libraries −import pandas as pdCreate the timestamp object in Pandastimestamp = pd.Timestamp('2021-09-11T13:12:34.261811') Convert timestamp to native Python datetime objecttimestamp.to_pydatetime()ExampleFollowing is the code import pandas as pd # set the timestamp object in Pandas timestamp = pd.Timestamp('2021-09-11T13:12:34.261811') # display the Timestamp print("Timestamp...", timestamp) # convert timestamp to native Python datetime object print("Convert Timestamp...", timestamp.to_pydatetime())OutputThis will produce the following code Timestamp... 2021-09-11 13:12:34.261811 Convert Timestamp... 2021-09-11 13:12:34.261811Read More

To groupby columns and count the occurrences of each combination in Pandas, we use the DataFrame.groupby() with size(). The groupby() method separates the DataFrame into groups.At first, let us import the pandas library with an alias pd −import pandas as pdInitialize the data of lists −# initializing the data mylist = {'Car': ['BMW', 'Mercedes', 'Lamborgini', 'Audi', 'Mercedes', 'Porche', 'RollsRoyce', 'BMW'], 'Place': ['Delhi', 'Hyderabad', 'Chandigarh', 'Bangalore', 'Hyderabad', 'Mumbai', 'Mumbai', 'Delhi'], 'Sold': [95, 80, 80, 75, 90, 90, 95, 50 ]}Next, we will create a DataFrame −# DataFrame dataFrame = pd.DataFrame(mylist, columns=['Car', 'Place', 'Sold'])Now, use the groupby() to count the occurrence with ... Read More

To combine two series into a DataFrame in Pandas, we can take two series and concatenate them using concat() method.StepsCreate series 1 with two elements, where index is ['a', 'b'] and name is Series 1.Print Series 1.Make Series 2 with two elements, where index is ['a', 'b'] and name is Series 2.Print Series 2.Concatenate Pandas objects along a particular axis with optional set logic along the other axes.Print the resultant DataFrame.Example Live Demoimport pandas as pd s1 = pd.Series([4, 16], index=['a', 'b'], name='Series 1') print "Input series 1 is: ", s1 s2 = pd.Series([3, 9], index=['a', 'b'], name='Series 2') print "Input series 2 is: ... Read More