It looks like you are trying to call a column in a PySpark DataFrame as if it were a function, but the column is not a function. Instead, you can access the column by its name as an attribute of the DataFrame.
For example, if you have a DataFrame df
with a column col
, you can access the values in that column using df.col
or df['col']
.
You can also use the select
method to select a specific column or multiple columns from the DataFrame. For example: df.select('col')
or df.select(df.col, df.otherCol)
.
It’s also possible that the error is occurring because you have a variable or function in your code that is named the same as a column in your DataFrame. In that case, you can use the df.
prefix to access the column and avoid the conflict.
For example, if you have a variable col
in your code and you want to access the column in the DataFrame with the same name, you can use df.col
to access the column instead of just col
.
I hope this helps! Let me know if you have any other questions.