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Python | Pandas DataFrame.axes

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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.



Last Updated : 20 Feb, 2019
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