Get New pandas DataFrame from Existing Data in Python (2 Examples)

On this page you’ll learn how to create a new pandas DataFrame based on an existing DataFrame in Python programming.

Example Data

import pandas as pd                    # Import pandas
df = pd.DataFrame({'A':range(1, 7),    # Construct example pandas DataFrame
                     'B':['a', 'x', 'c', 'x', 'e', 'x'],
                     'C':[5, 9, 7, 8, 1, 1]})
print(df)
#    A  B  C
# 0  1  a  5
# 1  2  x  9
# 2  3  c  7
# 3  4  x  8
# 4  5  e  1
# 5  6  x  1

Example 1: Duplicating Entire pandas DataFrame in Python

df_A = df.copy()                       # Create duplicate of pandas Data Frame
print(df_A)                            # Print copy
#    A  B  C
# 0  1  a  5
# 1  2  x  9
# 2  3  c  7
# 3  4  x  8
# 4  5  e  1
# 5  6  x  1

Example 2: Extracting Specific Variables of pandas DataFrame in Python

df_B = df[['A', 'C']].copy()           # Get certain columns
print(df_B)
#    A  C
# 0  1  5
# 1  2  9
# 2  3  7
# 3  4  8
# 4  5  1
# 5  6  1

Further Resources & Related Articles

In addition, you might have a look at some of the other articles on statisticsglobe.com. You can find a selection of tutorials below.

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