This content originally appeared on CodeSource.io and was authored by Md Niaz Rahman Khan
In this article, you will learn about how to append columns in Pandas.
A Pandas DataFrame is nothing but a two-dimensional data structure or two-dimensional array that represents the data in rows and columns. It is open-source and potent, fast, and easy to use. Basically, while working with big data we need to analyze, manipulate and update them and the pandas’ library plays a lead role there. In Pandas, we may need to append a column. Here, append means adding a new column to the existing one. To perform this action, Pandas provide a method named append(). This method will help us to append columns in Pandas. In this article, we will explore this method and see how we can append columns in Pandas. Before doing so, let’s create a simple Pandas DataFrame in the below section:
import pandas as pd
student_df = pd.DataFrame({'Name' : ['Alex', 'Deven', 'John'],
'Age' : ['21', '23', '19']
})
student_df2 = pd.DataFrame({'Name' : ['Sam', 'Billy', 'Alia'],
'Age' : ['20', '18', '22']
})
print(student_df)
print(student_df2)
# Output:
# Name Age
# 0 Alex 21
# 1 Deven 23
# 2 John 19
# Name Age
# 0 Sam 20
# 1 Billy 18
# 2 Alia 22Here, you can see that we have two students DataFrame. You may ask why we have created two different DataFrame while the column names are the same. Let’s imagine the scenario, at first, we work with some students. Later on, a few more students arrived. Now, we need to work them together. In the next section, we will see the process of performing this action.
Example code: append columns in Pandas using append() method
We will use the append() method to perform this action in Pandas. This method will simply append the second DataFrame column right after the first one. Follow the below code example to understand it more clearly:
import pandas as pd
student_df = pd.DataFrame({'Name' : ['Alex', 'Deven', 'John'],
'Age' : ['21', '23', '19']
})
student_df2 = pd.DataFrame({'Name' : ['Sam', 'Billy', 'Alia'],
'Age' : ['20', '18', '22']
})
append_df = student_df.append(student_df2)
print(append_df)
# Output:
# Name Age
# 0 Alex 21
# 1 Deven 23
# 2 John 19
# 0 Sam 20
# 1 Billy 18
# 2 Alia 22Here, you can see that the second DataFrame column has been successfully appended right after the first DataFrame. But you may notice that the index number is not in the correct format. To fix this see the below code example:
import pandas as pd
student_df = pd.DataFrame({'Name' : ['Alex', 'Deven', 'John'],
'Age' : ['21', '23', '19']
})
student_df2 = pd.DataFrame({'Name' : ['Sam', 'Billy', 'Alia'],
'Age' : ['20', '18', '22']
})
append_df = student_df.append(student_df2, ignore_index = True)
print(append_df)
# Output:
# Name Age
# 0 Alex 21
# 1 Deven 23
# 2 John 19
# 3 Sam 20
# 4 Billy 18
# 5 Alia 22This time you can see that the index number has been set in the proper format. The reason behind this is that we set ignore_index = True. This is all about append columns in Pandas. Finally, you may follow this article to perform this action.
This content originally appeared on CodeSource.io and was authored by Md Niaz Rahman Khan
Md Niaz Rahman Khan | Sciencx (2022-10-03T09:52:31+00:00) How to append columns in Pandas. Retrieved from https://www.scien.cx/2022/10/03/how-to-append-columns-in-pandas/
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