Python - Move a column to the first position in Pandas DataFrame?

Use pop() to remove a column and insert() to place it at the first position in a Pandas DataFrame. This technique allows you to reorder columns efficiently without creating a new DataFrame.

Creating the DataFrame

First, let's create a sample DataFrame with three columns ?

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame(
    {
        "Student": ['Jack', 'Robin', 'Ted', 'Marc', 'Scarlett', 'Kat', 'John'],
        "Result": ['Pass', 'Fail', 'Pass', 'Fail', 'Pass', 'Pass', 'Pass'],
        "Roll Number": [5, 10, 3, 8, 2, 9, 6]
    }
)

print("Original DataFrame:")
print(dataFrame)

Original DataFrame:
    Student Result  Roll Number
0      Jack   Pass            5
1     Robin   Fail           10
2       Ted   Pass            3
3      Marc   Fail            8
4  Scarlett   Pass            2
5       Kat   Pass            9
6      John   Pass            6

Moving Column to First Position

To move the "Roll Number" column to the first position, we use pop() to extract the column and insert() to place it at index 0 ?

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame(
    {
        "Student": ['Jack', 'Robin', 'Ted', 'Marc', 'Scarlett', 'Kat', 'John'],
        "Result": ['Pass', 'Fail', 'Pass', 'Fail', 'Pass', 'Pass', 'Pass'],
        "Roll Number": [5, 10, 3, 8, 2, 9, 6]
    }
)

print("Original DataFrame:")
print(dataFrame)

# Pop the column to extract it
shiftPos = dataFrame.pop("Roll Number")

# Insert column at the first position (index 0)
dataFrame.insert(0, "Roll Number", shiftPos)

print("\nDataFrame after moving 'Roll Number' to first position:")
print(dataFrame)

Original DataFrame:
    Student Result  Roll Number
0      Jack   Pass            5
1     Robin   Fail           10
2       Ted   Pass            3
3      Marc   Fail            8
4  Scarlett   Pass            2
5       Kat   Pass            9
6      John   Pass            6

DataFrame after moving 'Roll Number' to first position:
   Roll Number    Student Result
0            5       Jack   Pass
1           10      Robin   Fail
2            3        Ted   Pass
3            8       Marc   Fail
4            2   Scarlett   Pass
5            9        Kat   Pass
6            6       John   Pass

How It Works

The process involves two steps:

• pop("column_name"): Removes and returns the specified column as a Series
• insert(index, "column_name", data): Inserts the column at the specified position

The insert() method takes three parameters: the position index (0 for first), the column name, and the column data.

Alternative Method Using Column Reordering

You can also reorder columns by creating a new column list ?

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame(
    {
        "Student": ['Jack', 'Robin', 'Ted'],
        "Result": ['Pass', 'Fail', 'Pass'],
        "Roll Number": [5, 10, 3]
    }
)

# Reorder columns by specifying the desired order
cols = dataFrame.columns.tolist()
cols = [cols[2]] + cols[:2]  # Move last column to front
dataFrame = dataFrame[cols]

print("Reordered DataFrame:")
print(dataFrame)

Reordered DataFrame:
   Roll Number Student Result
0            5    Jack   Pass
1           10   Robin   Fail
2            3     Ted   Pass

Conclusion

Use pop() and insert() for moving columns to specific positions in Pandas DataFrames. This method modifies the DataFrame in-place and is efficient for column reordering operations.