Pandas copy()

import pandas as pd

# original DataFrame
data = {'A': [1, 2, 3],
        'B': [4, 5, 6]}

df = pd.DataFrame(data)

# creating a copy of the DataFrame
df_copy = df.copy()

print(df_copy)

'''
Output

   A  B
0  1  4
1  2  5
2  3  6
'''

copy() Syntax

The syntax of the copy() method in Pandas is:

df.copy(deep=True)

copy() Argument

The copy() method takes the following argument:

• deep (optional): specifies whether to make a deep copy or a shallow copy

copy() Return Value

The copy() method returns a new DataFrame or Series that is a copy of the original.

Example 1: Deep Copy

import pandas as pd

data = {'A': [1, 2, 3],
        'B': [4, 5, 6]}
df = pd.DataFrame(data)

# deep copy
deep_copy_df = df.copy()

# modifying the copy
deep_copy_df.iloc[2] = [10, 20]

print("Original DataFrame:")
print(df)
print("\nDeep Copy DataFrame:")
print(deep_copy_df)

Output

Original DataFrame:
   A  B
0  1  4
1  2  5
2  3  6

Deep Copy DataFrame:
    A   B
0   1   4
1   2   5
2  10  20

In this example, we created a deep copy of the DataFrame and modified the copied DataFrame.

In deep copy, changes in the copied DataFrame don't affect the original DataFrame.

Example 2: Shallow Copy

import pandas as pd

data = {'A': [1, 2, 3],
        'B': [4, 5, 6]}
df = pd.DataFrame(data)

# shallow copy
shallow_copy_df = df.copy(deep=False)

# modifying the copy
shallow_copy_df.iloc[2] = [10, 20]

print("Original DataFrame:")
print(df)
print("\nShallow Copy DataFrame:")
print(shallow_copy_df)

Output

Original DataFrame:
    A   B
0   1   4
1   2   5
2  10  20

Shallow Copy DataFrame:
    A   B
0   1   4
1   2   5
2  10  20

Here, we made a shallow copy of the original copy and modified the copied DataFrame.

In shallow copy, changes in the copied DataFrame shares the data with the original DataFrame and hence makes changes to the original DataFrame as well.