Pandas DataFrame.transpose()

by Online Tutorials Library July 14, 2022

Pandas DataFrame.transpose()

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

Syntax

Parameters

copy: If its value is True, then the underlying data is being copied. Otherwise, by default, no copy is made, if possible.

*args, **kwargs: Both are additional keywords that do not affect, but has an acceptance that provide compatibility with a numpy.

Returns

It returns the transposed DataFrame.

Example1

  # importing pandas as pd   import pandas as pd     # Creating the DataFrame   info = pd.DataFrame({‘Weight’:[27, 44, 38, 10, 67],                      ‘Name’:[‘William’, ‘John’, ‘Smith’, ‘Parker’, ‘Jones’],                      ‘Age’:[22, 17, 19, 24, 27]})     # Create the index   index_ = pd.date_range(‘2010-10-04 06:15′, periods = 5, freq =’H’)    # Set the index  info.index = index_    # Print the DataFrame   print(info)   # return the transpose   result = info.transpose()     # Print the result   print(result)  

Output

                           Weight      Name     Age  2010-10-04 06:15:00           27      William   22  2010-10-04 07:15:00           44       John         7  2010-10-04 08:15:00           38       Smith     19  2010-10-04 09:15:00           10       Parker    24  2010-10-04 10:15:00           67       Jones      27         2010-10-04 06:15:00 2010-10-04 07:15:00 2010-10-04 08:15:00    Weight                  27               44                  38     Name               William         John               Smith     Age                     22                   7                   19              2010-10-04 09:15:00 2010-10-04 10:15:00    Weight                  10               67    Name                Parker      Jones    Age                     24                  27

Example2

  # importing pandas as pd   import pandas as pd   # Creating the DataFrame   info = pd.DataFrame({“A”:[8, 2, 7, None, 6],                       “B”:[4, 3, None, 9, 2],                       “C”:[17, 42, 35, 18, 24],                       “D”:[15, 18, None, 11, 12]})    # Create the index   index_ = [‘Row1’, ‘Row2’, ‘Row3’, ‘Row4’, ‘Row5’]   # Set the index   info.index = index_     # Print the DataFrame   print(info)   # return the transpose   result = info.transpose()     # Print the result   print(result)  

Output

          A       B      C       D  Row_1     8.0     4.0    17     15.0  Row_2     2.0     3.0    42     18.0  Row_3     7.0     NaN    35     NaN  Row_4     NaN     9.0    18     11.0  Row_5     6.0     2.0    24     12.0       Row1    Row2    Row3    Row4    Row5  A    8.0     2.0     7.0     NaN     6.0  B    4.0     3.0     NaN     9.0     2.0  C    17.0    42.0    35.0    18.0    24.0  D    15.0    18.0    NaN     11.0    12.0

Next TopicDataFrame.where()

Pandas DataFrame.transpose()

Pandas DataFrame.transpose()

Syntax

Parameters

Returns

Example1

Example2

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