How to Create a New dataframe with selected columns : Methods

Suppose you have an existing dataframe with an “n ” number of columns. And if you want to create a new dataframe with the selected columns then how you will do so? In this tutorial, you will learn how to create new pandas dataframe from an existing dataframe with selected columns using various methods.

Sample Dataframe

Let’s first create a sample dataframe that will be used to extract specific columns from the existing dataframe and create a new one.

Execute the below lines of code to create it.

import pandas as pd
data = {"col1":[10,20,30,40,50],"col2":[1,2,3,4,5],"col3":[11,12,13,14,15],"col4":[110,120,130,140,150]}
df = pd.DataFrame(data)
print(df)

Output

 col1 col2 col3 col4
0 10 1 11 110
1 20 2 12 120
2 30 3 13 130
3 40 4 14 140
4 50 5 15 150

Method to create a new dataframe with selected columns

Let’s know all the methods to create a new dataframe from the old dataframe with the selected columns.

Method 1: Using the copy() function

The first method is to copy the old datframe with the specific columns. Just choose the columns list inside the square bracket and copy it.

new_df = df[["col1","col3","col4"]].copy()

import pandas as pd
data = {"col1":[10,20,30,40,50],"col2":[1,2,3,4,5],"col3":[11,12,13,14,15],"col4":[110,120,130,140,150]}
df = pd.DataFrame(data)
new_df = df[["col1","col3","col4"]].copy()
print(new_df)

Output

Method 2: Create a new dataframe with selected columns using the filter() function

The second to create a new dataframe is by using the filter() function. Here you have to just pass the columns you want to extract and set the value of the axis to 1.

new_df = df.filter(["col1","col3","col4"],axis=1)

Run the below lines of code and see the output.

import pandas as pd
data = {"col1":[10,20,30,40,50],"col2":[1,2,3,4,5],"col3":[11,12,13,14,15],"col4":[110,120,130,140,150]}
df = pd.DataFrame(data)
new_df = df.filter(["col1","col3","col4"],axis=1)
print(new_df)

Method 3: Remove the columns

new_df = df[df.columns.drop(["col2"])]

import pandas as pd
data = {"col1":[10,20,30,40,50],"col2":[1,2,3,4,5],"col3":[11,12,13,14,15],"col4":[110,120,130,140,150]}
df = pd.DataFrame(data)
new_df = df[df.columns.drop(["col2"])]
print(new_df)

Conclusion

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