Skip to content
Related Articles

Related Articles

Python | Pandas DataFrame.transpose

View Discussion
Improve Article
Save Article
Like Article
  • Last Updated : 21 Feb, 2019

Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. It can be thought of as a dict-like container for Series objects. This is the primary data structure of the Pandas.

Pandas DataFrame.transpose() function transpose index and columns of the dataframe. It reflect the DataFrame over its main diagonal by writing rows as columns and vice-versa.

Syntax: DataFrame.transpose(*args, **kwargs)

Parameter :
copy : If True, the underlying data is copied. Otherwise (default), no copy is made if possible.
*args, **kwargs : Additional keywords have no effect but might be accepted for compatibility with numpy.

Returns : The transposed DataFrame

Example #1: 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({'Weight':[45, 88, 56, 15, 71],
                   'Name':['Sam', 'Andrea', 'Alex', 'Robin', 'Kia'],
                   'Age':[14, 25, 55, 8, 21]})
  
# Create the index
index_ = pd.date_range('2010-10-09 08:45', periods = 5, freq ='H')
  
# Set the index
df.index = index_
  
# Print the DataFrame
print(df)


Output :

Now we will use DataFrame.transpose() function to find the transpose of the given dataframe.




# return the transpose
result = df.transpose()
  
# Print the result
print(result)


Output :

As we can see in the output, the DataFrame.transpose() function has successfully returned the transpose of the given dataframe.
 
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({"A":[12, 4, 5, None, 1], 
                   "B":[7, 2, 54, 3, None], 
                   "C":[20, 16, 11, 3, 8], 
                   "D":[14, 3, None, 2, 6]}) 
  
# Create the index
index_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5']
  
# Set the index
df.index = index_
  
# Print the DataFrame
print(df)


Output :

Now we will use DataFrame.transpose() function to find the transpose of the given dataframe.




# return the transpose
result = df.transpose()
  
# Print the result
print(result)


Output :

As we can see in the output, the DataFrame.transpose() function has successfully returned the transpose of the given dataframe.


My Personal Notes arrow_drop_up
Recommended Articles
Page :

Start Your Coding Journey Now!