Pandas is a powerful data manipulation library in Python and comes with a number of useful built-in features and properties to work with tabular (2D) data. In this tutorial, we will look at how to get the size of a dataframe in pandas with the help of some examples.
What is size of a dataframe in Pandas?

The size of a pandas dataframe refers to the number of items (or cells) in the dataframe. Since a dataframe is a two-dimensional data structure, its size is the number of rows * number of columns. For example, the size a dataframe with 4 rows and 3 columns is 12.
How to get the size of a dataframe in Pandas?
You can use the pandas dataframe size
property to get the size of a dataframe. The following is the syntax –
# get dataframe size df.size
It returns an integer representing the objects (items) in the dataframe. That is, the number of rows * the number of columns.
You can access a pandas Serie’s size
property which return the count of values (length) in the series.
Highlighted programs for you
Flatiron School
Flatiron School
University of Maryland Global Campus
University of Maryland Global Campus
Creighton University
Creighton University
Examples
Let’s now look at some examples of using the above syntax on a dataframe in Pandas.
First, we will create a sample dataframe that we will be using throughout this tutorial.
import numpy as np import pandas as pd # employee data data = { "Name": ["Jim", "Dwight", "Angela", "Tobi"], "Age": [26, 28, 27, 32] } # create pandas dataframe df = pd.DataFrame(data) # display the dataframe df
Output:

Here, we created a dataframe having the “Name” and “Age” data of some employees in an office. You can see that the above dataframe has 4 rows and 2 columns.
Example 1 – Size of a pandas dataframe using size
property
Let’s get the size of the dataframe created above using its size
property.
# get dataframe size print(df.size)
Output:
8
We get the size of the above dataframe as 8 (which is 4*2, rows*colums).
Note that the size
property returns the size of a dataframe irrespective of values (whether they are NaN
or non-NaN
).
Let’s recreate the employee dataframe with the same number of rows and columns but this time having some values as NaN
and then compute its size.
# employee data with some NaN values data = { "Name": ["Jim", "Dwight", "Angela", "Tobi"], "Age": [26, np.nan, np.nan, 32] } # create pandas dataframe with some Nan values df = pd.DataFrame(data) # get dataframe size print(df.size)
Output:
8
We get the size of the dataframe as 8 (same as what we got above).
Example 2 – Size of a pandas dataframe using its shape
property
Alternatively, you can also calculate the size of a dataframe in pandas by accessing its .shape
property which return a tuple of (number of rows, number of columns). Multiply the two values together to the size.
# get dataframe shape print("Shape: ", df.shape) # get dataframe size print("Size: ", df.shape[0]*df.shape[1])
Output:
Shape: (4, 2) Size: 8
You can see that we get the shape of the dataframe df
as (4, 2)
and multiplying them together gives us the size of the dataframe.
Length of a dataframe in Pandas
Note that the size of a dataframe is different from its length. The size of a dataframe in pandas is the total number of objects (or cells) in the dataframe whereas the length of a dataframe is the total number of rows in the dataframe.
You can use the built-in len()
function in Python or the first value in the tuple returned by the shape
property to get a dataframe’s length.
# get dataframe length using len() function print(len(df)) # get dataframe length using .shape property print(df.shape[0])
Output:
4 4
We get the length of the dataframe df
as 4 (whereas we got its size as 8).
Pop Quiz
The following are some quick questions to test your understanding of the topics mentioned in this tutorial –
What does the size of a dataframe refer to?
The size of a dataframe in pandas refers to the number of items (or cells) in the dataframe. It is equal to the number of rows * the number of columns.
How to get the size of a pandas dataframe?
Use the pandas dataframe size
property to get the size of a dataframe in Pandas.
What is the difference between the length and size of a dataframe in pandas?
The length of a dataframe refers to the number of rows in the dataframe whereas its size represents the number of elements (or cells) in the dataframe which is the number of rows * the number of columns.
You might also be interested in –
- Pandas – Check if a DataFrame is Empty
- Get the number of rows in a Pandas DataFrame
- Understanding Joins in Pandas
- Reset Index in Pandas – With Examples
- Pandas – Rename Column Names
Subscribe to our newsletter for more informative guides and tutorials.
We do not spam and you can opt out any time.