Python | Pandas Dataframe.at[ ] Last Updated : 16 Jul, 2021 Comments Improve Suggest changes 9 Likes Like Report Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas at[] is used to return data in a dataframe at the passed location. The passed location is in the format [position, Column Name]. This method works in a similar way to Pandas loc[ ] but at[ ] is used to return an only single value and hence works faster than it. Syntax: Dataframe.at[position, label]Parameters: position: Position of element in column label: Column name to be usedReturn type: Single element at passed position To download the data set used in following example, click here. In the following examples, the data frame used contains data of some NBA players. The image of data frame before any operations is attached below. Example #1: In this example, A dataframe is created by passing URL of csv to Pandas .read_csv() method. After that 2nd value in Name column is returned using .at[ ] method. Python3 # importing pandas module import pandas as pd # reading csv file from url data = pd.read_csv("https://media.geeksforgeeks.org/wp-content/uploads/nba.csv") # creating position and label variables position = 2 label = 'Name' # calling .at[] method output = data.at[position, label] # display print(output) Output: As shown in the output image, the output can be compared and it can be seen that the Value at 2nd position in the Name column is similar to output. Note: Unlike, .loc[ ], This method only returns single value. Hence dataframe.at[3:6, label] will return an error.Since this method only works for single values, it is faster than .loc[] method. Create Quiz Comment K Kartikaybhutani Follow 9 Improve K Kartikaybhutani Follow 9 Improve Article Tags : Python Python-pandas Python pandas-dataFrame Pandas-DataFrame-Methods Explore Python FundamentalsPython Introduction 2 min read Input and Output in Python 4 min read Python Variables 4 min read Python Operators 4 min read Python Keywords 2 min read Python Data Types 8 min read Conditional Statements in Python 3 min read Loops in Python - For, While and Nested Loops 5 min read Python Functions 5 min read Recursion in Python 4 min read Python Lambda Functions 5 min read Python Data StructuresPython String 5 min read Python Lists 4 min read Python Tuples 4 min read Python Dictionary 3 min read Python Sets 6 min read Python Arrays 7 min read List Comprehension in Python 4 min read Advanced PythonPython OOP Concepts 11 min read Python Exception Handling 5 min read File Handling in Python 4 min read Python Database Tutorial 4 min read Python MongoDB Tutorial 3 min read Python MySQL 9 min read Python Packages 10 min read Python Modules 3 min read Python DSA Libraries 15 min read List of Python GUI Library and Packages 3 min read Data Science with PythonNumPy Tutorial - Python Library 3 min read Pandas Tutorial 4 min read Matplotlib Tutorial 5 min read Python Seaborn Tutorial 3 min read StatsModel Library - Tutorial 3 min read Learning Model Building in Scikit-learn 6 min read TensorFlow Tutorial 2 min read PyTorch Tutorial 6 min read Web Development with PythonFlask Tutorial 8 min read Django Tutorial | Learn Django Framework 7 min read Django ORM - Inserting, Updating & Deleting Data 4 min read Templating With Jinja2 in Flask 6 min read Django Templates 5 min read Build a REST API using Flask - Python 3 min read Building a Simple API with Django REST Framework 3 min read Python PracticePython Quiz 1 min read Python Coding Practice 1 min read Python Interview Questions and Answers 15+ min read Like