Pandas DataFrame Copy Method

Introduction

In this lab, we will learn how to use the copy() method in the pandas DataFrame class. The copy() method allows us to make a copy of a DataFrame object without modifying the original DataFrame. We will explore the syntax and parameters of the copy() method and provide examples to illustrate its usage.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Create a DataFrame

First, we need to import the pandas library and create a DataFrame object.

import pandas as pd

df = pd.DataFrame({'A': ['a', 'b', 'c'], 'B': ['d', 'e', 'f']})
print(df)

Output:

   A  B
0  a  d
1  b  e
2  c  f

Copy the DataFrame using copy() Method

Next, we can use the copy() method to create a copy of the DataFrame object.

df1 = df.copy()
print(df1)

Output:

   A  B
0  a  d
1  b  e
2  c  f

Modify the Copied DataFrame

We can modify the copied DataFrame without affecting the original DataFrame.

df1['A'] = df1['A'].replace(['b'], 'x')
print(df1)
print(df)

Output:

   A  B
0  a  d
1  x  e
2  c  f

   A  B
0  a  d
1  b  e
2  c  f

Shallow Copy using copy() with deep=False

By default, the copy() method performs a deep copy, creating a new object with a copy of the data and indices. However, we can also create a shallow copy using the deep=False parameter.

df1 = df.copy(deep=False)
df1['A'] = df1['A'].replace(['b'], 'x')
print(df1)
print(df)

Output:

   A  B
0  a  d
1  x  e
2  c  f

   A  B
0  a  d
1  x  e
2  c  f

Summary

In this lab, we learned how to use the copy() method in the pandas DataFrame class. The copy() method allows us to create a copy of a DataFrame object without modifying the original DataFrame. We explored how to create a copy using the copy() method and how to modify the copied DataFrame. Additionally, we learned about the deep parameter, which controls whether a deep copy or shallow copy is created. By default, a deep copy is made, but a shallow copy can be created by setting deep=False. By understanding the copy() method, we can manipulate DataFrame objects without affecting the original data.