Python | Pandas DataFrame.empty (original) (raw)

Last Updated : 30 Sep, 2022

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. PandasDataFrame.empty attribute checks if the dataframe is empty or not. It returns True if the dataframe is empty else it returns False in Python.

In this article we will see How to Check if Pandas DataFrame is Empty.

Pandas – Check if DataFrame is Empty

Syntax: DataFrame.empty

Parameter: None

Returns: Boolean Type

Creating a DataFrame

Python3

import pandas as pd

df = pd.DataFrame({ 'Weight' :[ 45 , 88 , 56 , 15 , 71 ],

`` 'Name' :[ 'Sam' , 'Andrea' , 'Alex' , 'Robin' , 'Kia' ],

`` 'Age' :[ 14 , 25 , 55 , 8 , 21 ]})

index_ = [ 'Row_1' , 'Row_2' , 'Row_3' , 'Row_4' , 'Row_5' ]

df.index = index_

print (df)

Output :

Use DataFrame.empty attribute

Example 1:

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

Python3

result = df.empty

print (result)

Output :

False

Note: As we can see in the output, the DataFrame.empty attribute has returned False indicating that the given dataframe is not empty.

Example 2:

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

Python3

import pandas as pd

df = pd.DataFrame(index = [ 'Row_1' , 'Row_2' ,

`` 'Row_3' , 'Row_4' ,

`` 'Row_5' ])

print (df)

result = df.empty

print (result)

Output :

True

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

Using dataframe.shape[0]

Here we are using the dataframe’s shape that gives us the count of number of rows and number of columns.

Python3

import pandas as pd

import numpy as np

df = pd.DataFrame({ 'A' : [np.nan]})

print (df.dropna().shape[ 0 ] = = 0 )

Output :

True