Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.
Pandas Series.transpose()
function return the transpose, which is by definition self.
Syntax: Series.transpose(*args, **kwargs)
Parameter : None
Returns : self
Example #1: Use Series.transpose()
function to find the transpose of the given Series object.
# importing pandas as pd import pandas as pd
# Creating the Series sr = pd.Series([ 'New York' , 'Chicago' , 'Toronto' , 'Lisbon' , 'Rio' , 'Moscow' ])
# Create the Datetime Index didx = pd.DatetimeIndex(start = '2014-08-01 10:00' , freq = 'W' ,
periods = 6 , tz = 'Europe/Berlin' )
# set the index sr.index = didx
# Print the series print (sr)
|
Output :
Now we will use Series.transpose()
function to find the transpose of the given series object.
# find the transpose sr.transpose() |
Output :
As we can see in the output, the Series.transpose()
function has returned the same object as the transpose of the given series object, which is by definition self.
Example #2: Use Dataframe.transpose()
function to find the transpose of the given Dataframe.
# importing pandas as pd import pandas as pd
# Creating the Dataframe df = pd.DataFrame({ 'Date' :[ '10/2/2011' , '11/2/2011' , '12/2/2011' , '13/2/2011' ],
'Event' :[ 'Music' , 'Poetry' , 'Theatre' , 'Comedy' ],
'Cost' :[ 10000 , 5000 , 15000 , 2000 ]})
# Print the dataframe print (df)
|
Output :
Now we will use Dataframe.transpose()
function to find the transpose of the given Dataframe.
# find the transpose df.transpose() |
Output :
As we can see in the output, the Dataframe.transpose()
function has successfully returned the transpose of the given Dataframe object.