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Delete one or multiple columns from Pandas Dataframe

There are several methods that can be used to remove one or multiple columns from a Pandas Dataframe. Some of them are explained here.
import pandas as pd

subjects = {
  "name": ["Math", "Physics", "Chemistry", "English", "Hindi"],
  "score": [98, 91, 78, 80, 76],
  "code": ["M01", "P02", "C04", "E02", "H08"]
}

# Create the dataframe
df = pd.DataFrame(subjects)

print(df)

# Delete a column
df = df.drop(columns=['name'])

print(df)
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Output

        name  score code
0       Math     98  M01
1    Physics     91  P02
2  Chemistry     78  C04
3    English     80  E02
4      Hindi     76  H08


   score code
0     98  M01
1     91  P02
2     78  C04
3     80  E02
4     76  H08

Delete Dataframe column using drop() function

The drop() function of Pandas Dataframe can be used to delete single or multiple columns from the Dataframe. You can pass the column names array in it and it will remove the columns based on that.

Syntax

df.drop(columns=["COUMN_NAME_1", "COUMN_NAME_2"])

Remove single column from Dataframe

import pandas as pd

subjects = {
  "name": ["Math", "Physics", "Chemistry", "English", "Hindi"],
  "score": [98, 91, 78, 80, 76],
  "code": ["M01", "P02", "C04", "E02", "H08"]
}

# Create the dataframe
df = pd.DataFrame(subjects)

print(df)

# Delete a column
df = df.drop(columns=['score'])

print(df)

Output

        name  score code
0       Math     98  M01
1    Physics     91  P02
2  Chemistry     78  C04
3    English     80  E02
4      Hindi     76  H08


        name code
0       Math  M01
1    Physics  P02
2  Chemistry  C04
3    English  E02
4      Hindi  H08

Remove multiple columns from Dataframe

import pandas as pd

subjects = {
  "name": ["Math", "Physics", "Chemistry", "English", "Hindi"],
  "score": [98, 91, 78, 80, 76],
  "code": ["M01", "P02", "C04", "E02", "H08"]
}

# Create the dataframe
df = pd.DataFrame(subjects)

# Delete two column
df = df.drop(columns=['name', 'score'])

print(df)

Output

  code
0  M01
1  P02
2  C04
3  E02
4  H08

If you do not want to reassign Dataframe, you can use inplace=True in the drop() function.

df.drop(columns=['name', 'score'], inplace=True)

Delete Dataframe column using del keyword

The del keyword can also be used to delete a column from Pandas Dataframe. You need to place the del keyword before the Dataframe variable along with the column name that you want to delete.

Syntax

del df['COLUMN_NAME']

Code Example

import pandas as pd

data = {
  "column 1": [10, 20, 30, 40],
  "column 2": ['a', 'b', 'c', 'd'],
  "column 3": [1, 2, 3, 4]
}

df = pd.DataFrame(data)

del df['column 3']

print(df)

Output

   column 1 column 2
0        10        a
1        20        b
2        30        c
3        40        d

Using the above code example, we have removed "column 3" from the Dataframe using del keyword

import pandas as pd

data = {
  "column 1": [5, 10, 15, 20],
  "column 2": ['a', 'b', 'c', 'd'],
  "column 3": [1, 2, 3, 4]
}

df = pd.DataFrame(data)

df.pop('column 1')

print(df)

#   column 2  column 3
# 0        a         1
# 1        b         2
# 2        c         3
# 3        d         4
We can also use the pop() function of Dataframe to delete a column from pandas Dataframe. It takes the column name that you want to delete as a parameter.
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