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To insert a new index value at the first index from the last, use the index.insert() method. Set the last index value -1 and the value to be inserted as parameters.At first, import the required libraries -import pandas as pdCreating the Pandas index −index = pd.Index(['Car', 'Bike', 'Airplane', 'Ship', 'Truck']) Display the index −print("Pandas Index...", index)Insert a new value at the first index from the last using the insert() method. The first parameter in the insert() is the location where the new index value is placed. The -1 here means the new index value gets inserted at the first index ... 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
To insert a new index value at a specific position, use the index.insert() method in Pandas. At first, import the required libraries -import pandas as pdCreating the Pandas index −index = pd.Index(['Car', 'Bike', 'Airplane', 'Ship', 'Truck']) Display the index −print("Pandas Index...", index)Insert a new value at a specific position using the insert() method. The first parameter in the insert() is the location where the new index value is placed. The 2 here means the new index value gets inserted at index 2 i.e. position 3. The second parameter is the new index value to be inserted.print("After inserting a new index ... Read More
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 check whether the two Index objects have similar object attributes and types, use the index1.identical(index2) method.At first, import the required libraries -import pandas as pdCreating Pandas index1 and index2 −index1 = pd.Index([15, 25, 35, 45, 55]) index2 = pd.Index([15, 25, 35, 45, 55])Display the index1 and index2 −print("Pandas Index1...", index1) print("Pandas Index2...", index2)Check whether the two index objects have similar attributes and types or not −print("The two Index objects have similar attributes and types?" "", index1.identical(index2))ExampleFollowing is the code −import pandas as pd # Creating Pandas index1 and index2 index1 = pd.Index([15, 25, 35, 45, 55]) index2 = ... Read More
To convert given Timestamp to Period, use the timestamp.to_period() method. Within that, set the frequency using the freq parameter. For hourly frequency, set freq as H.At first, import the required libraries −import pandas as pdCreate the timestamp object in Pandastimestamp = pd.Timestamp(2021, 9, 18, 11, 50, 20, 33) Convert timestamp to Period. We have set the frequency as hourly using the "freq" parameter with value 'H'timestamp.to_period(freq='H')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) # convert ... Read More
To convert given Timestamp to Period, use the timestamp.to_period() method. Within that, set the frequency using the freq parameter. For quarterly frequency, set freq as Q.At first, import the required libraries −import pandas as pdCreate the timestamp object in Pandastimestamp = pd.Timestamp(2021, 9, 18, 11, 50, 20, 33) Convert timestamp to Period. We have set the frequency as quarterly using the "freq" parameter with value 'Q'timestamp.to_period(freq='Q') 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) # ... Read More
To convert given Timestamp to Period, use the timestamp.to_period() method. Within that, set the frequency using the freq parameter. For monthly frequency, set freq as M.At first, import the required libraries −import pandas as pdSet the timestamp object in Pandastimestamp = pd.Timestamp(2021, 9, 18, 11, 50, 20, 33) Convert timestamp to Period. We have set the frequency as monthly using the "freq" parameter with value 'M'timestamp.to_period(freq='M') 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) # ... Read More
To convert given Timestamp to Period, use the timestamp.to_period() method. Within that, set the frequency using the freq parameter. For weekly frequency, set freq as W.At first, import the required libraries −import pandas as pdCreate the timestamp object in Pandastimestamp = pd.Timestamp(2021, 9, 18, 11, 50, 20, 33) Convert timestamp to Period. We have set the frequency as weekly using the "freq" parameter with value 'W'timestamp.to_period(freq='W')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) # convert ... Read More