Python | Pandas DataFrame.empty

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.empty attribute checks if the dataframe is empty or not. It return True if the dataframe is empty else it return False.

Syntax: DataFrame.empty



Parameter : None

Returns : bool

Example #1: Use DataFrame.empty attribute to check if the given dataframe is empty or not.

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# 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)

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Output :

Now we will use DataFrame.empty attribute to check if the given dataframe is empty or not.

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# check if there is any element
# in the given dataframe or not
result = df.empty
  
# Print the result
print(result)

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Output :

As we can see in the output, the DataFrame.empty attribute has returned False indicating that the given dataframe is not empty.
 
Example #2: Use DataFrame.empty attribute to check if the given dataframe is empty or not.

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# importing pandas as pd
import pandas as pd
  
# Creating an empty DataFrame
df = pd.DataFrame(index = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5'])
  
# Print the DataFrame
print(df)

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Output :

Now we will use DataFrame.empty attribute to check if the given dataframe is empty or not.

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# check if there is any element
# in the given dataframe or not
result = df.empty
  
# Print the result
print(result)

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Output :

As we can see in the output, the DataFrame.empty attribute has returned True indicating that the given dataframe is empty.



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