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 iat[] method is used to return data in a dataframe at the passed location. The passed location is in the format [position in the row, position in the column]. This method works similarly to Pandas iloc[] but iat[] is used to return only a single value and hence works faster than it.
Syntax: Dataframe.iat[row, column]
Parameters:Â
position: Position of element in columnÂ
label: Position of element in row
Return type: Single element at passed positionÂ
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To download the data set used in the 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:Â
In this example, A dataframe is created by passing URL of csv to Pandas .read_csv() method. After that 3 is passed as column position and 7 as the position in row and value at that position is returned using .iat[ ] method.Â
Python3
# importing pandas module import pandas as pdÂ
# reading csv file from url Â
# creating column and row variablescolumn = 7row = 3Â Â Â Â Â # calling .iat[] methodoutput = data.iat[row, column]Â
# displayprint(output)Â
# df displaydata.head() |
Output:Â
As shown in the output image, the output can be compared and it can be seen that the Value of the 3rd element in the 7th column was returned.Â
Note:Â Â
- Unlike, .iloc[ ], This method only returns single value. Hence, dataframe.at[3:6, 4:2] will return an error
- Since this method only works for single values, it is faster than .iloc[] method
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