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Understanding inplace=True in Pandas
Learn about the inplace=True in Pandas, what is the use of it, and when we should inplace=True in Pandas.
Submitted by Pranit Sharma, on June 23, 2022
Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consist of rows, columns, and the data.
Whenever we apply a function to any column, row, or the entire DataFrame, we sometimes pass a parameter called inplace=True. The question is what is the significance of this parameter.
Whenever we make some changes to a column value or row value or the entire DataFrame either index-wise or axis-wise, we either use the method in which we change the original value and return the changed value or we use a method where we do not change the entire data set and do the specific changes wherever required.
inplace=True means the data will be modified without returning a copy of the data or the original data.
Syntax:
df.some_operation(inplace=True)
But if inplace=False is passed then it will modify the value and also it returns a copy of the data.
Syntax:
df.some_operation(inplace=False)
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