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 pdimport pandas as pd # Creating the Seriessr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio', 'Moscow']) # Create the Datetime Indexdidx = pd.DatetimeIndex(start ='2014-08-01 10:00', freq ='W', periods = 6, tz = 'Europe/Berlin') # set the indexsr.index = didx # Print the seriesprint(sr) |
Output :
Now we will use Series.transpose() function to find the transpose of the given series object.
# find the transposesr.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 pdimport pandas as pd # Creating the Dataframedf = 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 dataframeprint(df) |
Output :
Now we will use Dataframe.transpose() function to find the transpose of the given Dataframe.
# find the transposedf.transpose() |
Output :
As we can see in the output, the Dataframe.transpose() function has successfully returned the transpose of the given Dataframe object.
