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.axes attribute access a group of rows and columns by label(s) or a boolean array in the given DataFrame.

Syntax: DataFrame.axes Parameter : None Returns : list

Example #1: Use DataFrame.axes attribute to return a list containing the axes labels of the 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_ = ['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.axes attribute to return the axes labels of the dataframe.

# return the axes labels of the dataframe
result = df.axes

# Print the result
print(result)

Output : As we can see in the output, the DataFrame.axes attribute has successfully returned a list containing the axes labels of the dataframe.   Example #2: Use DataFrame.axes attribute to return a list containing the axes labels of the 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.axes attribute to return the axes labels of the dataframe.

# return the axes labels of the dataframe
result = df.axes

# Print the result
print(result)

Output : As we can see in the output, the DataFrame.axes attribute has successfully returned a list containing the axes labels of the dataframe.