In this tutorial, we will look at how to get (or access) the value of a specific cell in a Pandas dataframe with the help of some examples.
How to get the cell value in Pandas dataframe?

Use the Pandas dataframe iat
property to get the cell value of a dataframe using its row and column indices (integer positions). Alternatively, if you want to access the value of a cell using its row and column labels, use the at
property.
The following is the syntax –
# get cell value using row and column indices (integer positions) df.iat[row_position, column_position] # get cell value using row and column labels df.at[row_label, column_label]
It returns the single cell value for the given row/column pair.
Note that we use the iat
or the at
property to specifically access a single value for the given row and column indices (or labels). You can also use the iloc
and the loc
property to access the value of a single (and multiple cells) in a Pandas dataframe.
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Examples
Let’s now look at some examples of using the above syntax to access the value of a cell in a Pandas dataframe.
First, we will create a dataframe that we will use throughout this tutorial.
import pandas as pd # employee data data = { "Name": ["Jim", "Dwight", "Angela", "Tobi"], "Age": [26, 28, 27, 32], "Department": ["Sales", "Sales", "Accounting", "HR"] } # create pandas dataframe df = pd.DataFrame(data) # display the dataframe df
Output:

Here, we created a dataframe containing information about some employees in an office. The dataframe has 4 rows and 3 columns (“Name”, “Age”, and “Department”).
Example 1 – Access dataframe cell value using iat
property
Let’s get the department of the employee “Dwight”.
To access a cell value using the iat
property, you need to provide its row and column indices. Note that rows and columns in a Pandas dataframe are indexed starting from 0 by default.
# get cell value using row and column indices (integer position) df.iat[1, 2]
Output:
'Sales'
We get the value for the cell with row index 1 and column index 2 (which represents the department of the employee “Dwight”).
Example 2 – Access the dataframe cell value using the at
property
Let’s do the same exercise as above but use the row and column labels with the at
property this time.
The column label is the column name itself and since the above dataframe does not have explicitly defined row labels, we will use its row indices as the row label.
# get cell value using row and column labels df.at[1, "Department"]
Output:
'Sales'
We get the “Department” value in the row 1
(which represents the department of the employee “Dwight”).
Using iloc
and loc
to access a cell value in Pandas dataframe
The iloc
and loc
properties of a Pandas dataframe are used to access a group of rows and columns but you can also use them to access the value for a single cell.
Let’s do the same exercise as above.
# get cell value using row and column indices (integer position) df.iloc[1, 2]
Output:
'Sales'
Here, we get the value of the cell represented by row index 1 and column index 2 using the iloc
property.
# get cell value using row and column labels df.loc[1, "Department"]
Output:
'Sales'
Here, we get the value of the cell represented by the row label 1 and the column label “Department” using the loc
property.
Summary
In this tutorial, we looked at how to access the value of a cell in a Pandas dataframe. If you only want the value of a single cell use the iat
or the at
dataframe property.
- Use the
iat
property to access the cell value using its row and column index. - Use the
at
property to access the cell value using its row and column labels.
You can also use the iloc
and the loc
property but they are generally used to get the value of a group of rows and columns.
You might also be interested in –
- Pandas – Set Value of Specific Cell in DataFrame
- Pandas – Get DataFrame Size (Count Cells)
- Pandas – Create DataFrame Copy
- Pandas – Add Column From Another Dataframe
- Pandas – Add an Empty Column to a DataFrame
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