Write a program in Python to remove one or more than one columns in a given DataFrame

Sometimes you need to remove one or more columns from a Pandas DataFrame. Python provides several methods to accomplish this: using del statement, pop() method, and drop() method.

Using del Statement

The del statement permanently removes a single column from the DataFrame ?

import pandas as pd

data = [[1, 2, 3], [4, 5, 6]]
df = pd.DataFrame(data, columns=('one', 'two', 'three'))
print("Before deletion:")
print(df)

del df['one']
print("\nAfter deletion:")
print(df)

Before deletion:
   one  two  three
0    1    2      3
1    4    5      6

After deletion:
   two  three
0    2      3
1    5      6

Using pop() Method

The pop() method removes a column and returns its values as a Series ?

import pandas as pd

data = [[1, 2, 3], [4, 5, 6]]
df = pd.DataFrame(data, columns=('one', 'two', 'three'))
print("Before deletion:")
print(df)

removed_column = df.pop('one')
print("\nRemoved column:")
print(removed_column)
print("\nAfter deletion:")
print(df)

Before deletion:
   one  two  three
0    1    2      3
1    4    5      6

Removed column:
0    1
1    4
Name: one, dtype: int64

After deletion:
   two  three
0    2      3
1    5      6

Using drop() Method for Multiple Columns

The drop() method is most flexible and can remove one or multiple columns. Use inplace=True to modify the original DataFrame ?

import pandas as pd

data = [[1, 2, 3], [4, 5, 6]]
df = pd.DataFrame(data, columns=('one', 'two', 'three'))
print("Before deletion:")
print(df)

df.drop(columns=['one', 'two'], inplace=True)
print("\nAfter deleting two columns:")
print(df)

Before deletion:
   one  two  three
0    1    2      3
1    4    5      6

After deleting two columns:
   three
0      3
1      6

Comparison

Conclusion

Use del for simple single column removal, pop() when you need the removed data, and drop() for removing multiple columns or more control over the operation.