Gyan Sangrah

inplace attribute in pandas

In this article, we will discuss about inplace attribute in pandas.

Purpose

There are 2 values of inplace attribute

1. True – Performs an operation on the object.

2. False – Performs an operation on the copy of the object.

Example

Consider the following example

import numpy as np
import pandas as pd

df = pd.DataFrame(np.random.randn(5,4),['A', 'B', 'C', 'D', 'E'],['W', 'X', 'Y', 'Z'])

print("\nDataFrame before deleting new column\n")
print(df)

df.drop('X', axis=1, inplace=False)

print("\nDataFrame after deleting new column\n")
print(df)

In the above example, the value of inplace is false. So, the drop operation is performed on the copy on an object ‘df’. So, after drop operation the column ‘X’ is not removed from ‘df’ object. Here is the output of above program

Now let us change the value from False to True.

import numpy as np
import pandas as pd


df = pd.DataFrame(np.random.randn(5,4),['A', 'B', 'C', 'D', 'E'],['W', 'X', 'Y', 'Z'])



print("\nDataFrame before deleting new column\n")
print(df)

df.drop('X', axis=1, inplace=True)

print("\nDataFrame after deleting new column\n")
print(df)

Output of the above code is

Posted By -	Karan Gupta

Posted On -	Monday, April 15, 2019

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