How to add a Column to a Existing Data Frame | Data Frame | Pandas | Pandas Tutorial

Опубликовано: 07 Октябрь 2024
на канале: Parag Dhawan

330

In Pandas, you can add a column to an existing DataFrame using either bracket notation or the assign method. Here's an example using bracket notation:

python
Copy code
import pandas as pd

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

Add a new column 'C' with a list of values
df['C'] = [7, 8, 9]

Print the updated DataFrame
print(df)
In this example, we first create a DataFrame with two columns 'A' and 'B'. We then use bracket notation to add a new column 'C' with a list of values. The length of the list must match the number of rows in the DataFrame. Finally, we print the updated DataFrame to confirm that the new column has been added.

Alternatively, you can use the assign method to add a new column as a copy of an existing column with a modified value, like this:

python
Copy code
Add a new column 'D' as a copy of column 'A' multiplied by 2
df = df.assign(D=df['A'] * 2)

Print the updated DataFrame
print(df)
In this example, we use the assign method to create a new column 'D' as a copy of column 'A' multiplied by 2. The assign method returns a new DataFrame with the new column added, so we assign the result back to df. Finally, we print the updated DataFrame to confirm that the new column has been added.
code snippet
import pandas as pd
import numpy as np

d = {'one':pd.Series([1,2,3],index=['a','b','c']),
'two':pd.Series([1,2,3,4],index = ['a','b','c','d'])}

df = pd.DataFrame(d)

print(df)

print('adittion of a new column by adition of new Series:')

df['three'] = pd.Series([10,20,30],index=['a','b','c'])

print(df)

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