Pandas DataFrame transpose() Method: Swap Rows and Columns

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 dictionary-like container for the Series objects. This is the primary data structure of the Pandas.

Pandas DataFrame transpose() method transposes the index and columns of the DataFrame. It reflects 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

Examples

Let us look at some Python codes and understand the DataFrame transpose() method of Pandas library with these examples:

Example 1

Use the transpose() function to find the transpose of the given DataFrame.

Python3

# 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 the DataFrame transpose() function to find the transpose of the given DataFrame.

Python3

# 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 the DataFrame transpose() function to find the transpose of the given DataFrame.

Python3

# 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 the DataFrame transpose() function to find the transpose of the given DataFrame.

Python3

# 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.