Data analysis and manipulation have become increasingly essential in today’s business world, and for good reason. By analyzing data, businesses can make informed decisions that can lead to growth and success. However, analyzing and manipulating data can be time-consuming and complicated, especially when it comes to large datasets. This is where Pandas, a popular data manipulation library in Python, comes in handy. 

In this article, we will show you how to unlock the power of Pandas by demonstrating how to move columns in your DataFrame with ease.

What is Pandas Dataframe?

Before diving into the specifics of importing a sample Pandas dataframe, let’s define a Pandas dataframe. A dataframe is a two-dimensional labeled data structure in which both rows and columns are labelled with their respective identities. It resembles a spreadsheet or a SQL table, where each column represents a variable or a characteristic and each row represents an observation or a sample.

Understanding the Pandas pop and insert Methods

  • The pop() method in Pandas is used to remove and return the last column of a DataFrame or the last row of a Series. This method takes an optional argument key that can be used to remove a specific column or row based on its label. The pop() method modifies the original DataFrame or Series and returns the popped column or row.

  • The insert() method in Pandas is used to insert a new column into a DataFrame at a specific location. This method takes three arguments: loc, column, and value. The loc argument is the integer location where the new column will be inserted, the column argument is the label of the new column, and the value argument is the data that will be inserted into the new column.

How to Move a Pandas DataFrame Column to the Front

To move a Pandas DataFrame column to the front, you can use the pop() and insert() methods in combination.

Here’s an example:

				
					import pandas as pd

# create a sample DataFrame
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})

# pop the column you want to move to the front
column_to_move = df.pop('B')

# insert the column at the front
df.insert(0, 'B', column_to_move)

print(df)

Output:

				
					#    B  A  C
# 0  4  1  7
# 1  5  2  8
# 2  6  3  9

In this example, we first create a sample DataFrame with three columns: A, B, and C. We then use the pop() method to remove the B column from the DataFrame and store it in a variable called column_to_move. Finally, we use the insert() method to insert the B column at the front of the DataFrame by specifying a loc value of 0.

How to Move a Pandas DataFrame Column to the Front

To move a Pandas DataFrame column to the end, you can use the pop() method to remove the column and then use the [] indexing operator to add it back to the DataFrame at the end.

Here’s an example:

				
					import pandas as pd

# create a sample DataFrame
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})

# pop the column you want to move to the end
column_to_move = df.pop('B')

# add the column back to the DataFrame at the end
df['B'] = column_to_move

print(df)

Output:

				
					#    A  C  B
# 0  1  7  4
# 1  2  8  5
# 2  3  9  6

In this example, we first create a sample DataFrame with three columns: A, B, and C. We then use the pop() method to remove the B column from the DataFrame and store it in a variable called column_to_move. Finally, we add the B column back to the DataFrame using df['B'] = column_to_move, which will add it to the end of the DataFrame.

How to Move a Pandas DataFrame Column to a Specific Position

To move a Pandas DataFrame column to a specific position, you can use the pop() method to remove the column and then use the insert() method to insert it at the desired location.

Here’s an example:

				
					import pandas as pd

# create a sample DataFrame
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})

# pop the column you want to move to a specific position
column_to_move = df.pop('B')

# insert the column at the desired position
df.insert(1, 'B', column_to_move)

print(df)

Output:

				
					#    A  B  C
# 0  1  4  7
# 1  2  5  8
# 2  3  6  9

In this example, we first create a sample DataFrame with three columns: A, B, and C. We then use the pop() method to remove the B column from the DataFrame and store it in a variable called column_to_move. Finally, we use the insert() method to insert the B column at position 1 in the DataFrame, shifting the columns to the right of it one position to the right.

Wrap up

In this tutorial, you learned how to transfer a Pandas DataFrame column to a particular position, such as the beginning or the end. The ability to reorder columns improves the legibility of your data significantly.

You initially learned how to advance a Pandas column to the front using the .pop() and .insert() methods. Then, you discovered how to replicate the procedure for adding a column to the end of a DataFrame. You have finally learned how to move a column to a particular location.

Here you find Pandas Official Docummentation
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.pop.html


Thanks for reading. Happy coding!