The pandas library in Python is a robust and powerful tool for data analysis. In this shot, we will go over some ways to utilize the library to create a new column in an existing data frame.
The simplest way to add a new column to an existing panda’s data frame is to index the data frame with the new column’s name and assign a list to it:
import pandas as pd # Create a new DataFrame df = pd.DataFrame({'Name': ['Ali', 'Aqsa', 'Armaan', 'Arij'], 'Age': [34, 26, 56, 44], 'Position': ['Senior Engineer', 'Junior Engineer', 'HR Officer', 'COO']}) print("Dataframe before adding new column:") print(df) # Adding salary column by indexing and assigning a list df['salary'] = [200000, 70000, 110000, 670000] print("Dataframe after adding new column:") print(df)
Another way of introducing a column in the data frame is by using the in-built assign
method, which creates a new data frame with the added column. The Python code below shows how this can be done:
import pandas as pd # Create a new DataFrame df = pd.DataFrame({'Name': ['Ali', 'Aqsa', 'Armaan', 'Arij'], 'Age': [34, 26, 56, 44], 'Position': ['Senior Engineer', 'Junior Engineer', 'HR Officer', 'COO']}) print("Dataframe before adding new column:") print(df) # Adding salary column using the assign method df2 = df.assign(salary = [200000, 70000, 110000, 670000]) print("Dataframe after adding new column:") print(df2)
The insert
method is another useful data frame method that can be used to create a new column. Unlike the previous techniques, which simply appended a column to the end of the data frame, the insert
method allows you to add the new column in any specified position. Here’s how the method is used:
import pandas as pd # Create a new DataFrame df = pd.DataFrame({'Name': ['Ali', 'Aqsa', 'Armaan', 'Arij'], 'Age': [34, 26, 56, 44], 'Position': ['Senior Engineer', 'Junior Engineer', 'HR Officer', 'COO']}) print("Dataframe before adding new column:") print(df) # Adding salary column to the first index using the insert method df.insert(1, "salary", [200000, 70000, 110000, 670000]) print("Dataframe after adding new column:") print(df)
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