Access Value at specific Row/Column of DataFrame

To access item/value at specific Row/Column of DataFrame in Pandas, use pandas.DataFrame.at attribute. Specify the row and column in square brackets.

In this tutorial, we will learn how to access value at specific Row/Column of DataFrame in Pandas using DataFrame.at attribute.

Syntax

The syntax to access value/item at given row and column in DataFrame is

DataFrame.at[row, column]

where

  • row is the index of the item’s row.
  • column is the column label for the item.

We may read the value at specified row and column, or may set the value at specified row and column.

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Example

Read Value at [Row, Column] in DataFrame

In the following program, we take a DataFrame and read the value at second row and 'name' column.

Example.py

import pandas as pd

df = pd.DataFrame(
    {'name': ["apple", "banana", "cherry"], 'quant': [40, 50, 60]})
item = df.at[1, 'name']
print(item)
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Output

banana

Update Value at [Row, Column] in DataFrame

In the following program, we take a DataFrame and update the value at second row and 'name' column to 'mango'.

Example.py

import pandas as pd

df = pd.DataFrame(
    {'name': ["apple", "banana", "cherry"], 'quant': [40, 50, 60]})
df.at[1, 'name'] = "mango"
print(df)
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Output

name  quant
0   apple     40
1   mango     50
2  cherry     60

Conclusion

In this Pandas Tutorial, we learned how to access item/value at specific Row/Column of DataFrame using DataFrame().at attribute.