Class 12 Remove Columns and rows in dataframe

 To remove columns and rows in a DataFrame using the Pandas library in Python, you can use the drop method. Here are the steps and examples for each:

Removing Columns

To remove one or more columns from a DataFrame, use the drop method with the axis parameter set to 1 (or columns).

Example:

import pandas as pd

# Sample DataFrame
data = {
    'Year': [2020, 2021, 2022, 2023],
    'Subject': ['Math', 'Physics', 'Chemistry', 'Biology'],
    'Question': [
        'Q1',
        'Q2',
        'Q3',
        'Q4'
    ]
}
df = pd.DataFrame(data)
# Remove a single column
df = df.drop('Question', axis=1)
# Remove multiple columns
#df = df.drop(['Year', 'Subject'], axis=1)
print(df)

Remove Single Columns

Remove Multiple Columns

Removing Rows

To remove one or more rows from a DataFrame, use the drop method with the axis parameter set to 0 (or index).

Example:

# Sample DataFrame
df = pd.DataFrame(data)
# Remove a single row by index
df = df.drop(1, axis=0)
# Remove multiple rows by index
df = df.drop([0, 2], axis=0)
print(df)





Single Row

import pandas as pd
# Sample DataFrame
data = {
    'Year': [2020, 2021, 2022, 2023],
    'Subject': ['Math', 'Physics', 'Chemistry', 'Biology'],
    'Question': [
        'Q1',
        'Q2',
        'Q3',
        'Q4'
    ]
}
df = pd.DataFrame(data)
# print DataFrame
print(df,"\n")
# Remove a single row by index
df = df.drop(1, axis=0)
# Remove multiple rows by index
#df = df.drop([0, 2], axis=0)
print(df)

Removing Multiple Rows

import pandas as pd

# Sample DataFrame

data = {

    'Year': [2020, 2021, 2022, 2023],

    'Subject': ['Math', 'Physics', 'Chemistry', 'Biology'],

    'Question': [

        'Q1',

        'Q2',

        'Q3',

        'Q4'

    ]

}

df = pd.DataFrame(data)

# print DataFrame

print(df,"\n")

# Remove a single row by index

#df = df.drop(1, axis=0)

# Remove multiple rows by index

df = df.drop([0, 2], axis=0)

print(df)

Removing Rows/Columns In-Place

To make changes directly to the original DataFrame without creating a new one, use the inplace parameter set to True.

Example:

# Sample DataFrame
df = pd.DataFrame(data)
# Remove a column in-place
df.drop('Question', axis=1, inplace=True)
# Remove a row in-place
df.drop(1, axis=0, inplace=True)
print(df)