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 a new 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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