typeerror dataframe object is not callable : Quickly Fix It

Generally, this typeerror dataframe object is not a callable error that occurs when we use dataframe as a function, with or without arguments. In this article, we will see this error with an example. Firstly we will understand the root cause. After it, We will also explore ways to fix the same.

typeerror dataframe object is not callable : ( Scenarios )-

In order to justify this scenario, There is a prerequisite for creating a pandas dataframe. We will try to keep the rows minimal in order to keep this article and topic simple.

import pandas as pd
data = {
    'Name' : ['SAM', 'Aish', 'Mohan', 'Shivangi'],
    'Exp' : [23, 21, 22, 21]
       }

df = pd.DataFrame(data)
df

Scenario 1: Calling dataframe as function without arguments-

Now after creating this dataframe. If we run the below syntax we will get the dataframe object is not a callable error. Here in the above example dataframe, we will directly call as a method in the place of any attribute. Let’s see how –

typeerror dataframe object is not callable error

Scenario 2: Calling dataframe as function with arguments-

Nothing two different from above but suppose you want to check the variance of any dataframe columns. You can use var() function for the same. But if you do it syntactically wrong, Please refer to the below image.

dataframe as function - incorrect way to call — dataframe as function – incorrect way to call

Solution-

This is pretty state to fix this issue. The Path is very simple, we should correctly call the function. Let’s take the above example where we call df(“var”) function. The correct way is

Here we are calling the attribute of dataframe function. This will compute the variance of the numerical column of dataframe.

Specially Spark dataframe, when we call the same it will generate the same error. Basically, it is the same with each object when we call it a function instead of the object attribute. The Typeerror is one of the most common errors in the Python world. Hope now you can fix the same.

Thanks

Data Science Learner Team