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.
# 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.empty
attribute to check if the given dataframe is empty or not.
# check if there is any element # in the given dataframe or not result = df.empty # Print the result print (result) |
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.
# 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) |
Output :
Now we will use DataFrame.empty
attribute to check if the given dataframe is empty or not.
# check if there is any element # in the given dataframe or not result = df.empty # Print the result print (result) |
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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