How to add new column?

 In Pandas, adding a new column to an existing DataFrame

Let's look at how to add new columns to an existing Pandas DataFrame. This task can be accomplished in a variety of ways.

The first method involves declaring a new list as a column.

# Add the pandas package to your project.

pandas as a pd import

# Create a dictionary containing information about students.

'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'], data =

[5.1, 6.2, 5.1, 5.2], [5.1, 6.2, 5.1, 5.2],

'Qualification': ['Msc', 'MA', 'Msc', 'Msc', 'Msc', 'Msc', 'Msc']

# Create a DataFrame from the vocabulary.

pd.DataFrame = df (data)

# Create a list that will be turned into a column.

['Delhi', 'Bangalore', 'Chennai', 'Patna'] address

# Using the column name 'Address' and equating it to the list

address = df['Address']

# Take note of the df Output:

It's important to note that the length of your list must equal the length of the index column; otherwise, an error will appear.

The second method is to use DataFrame.insert ()

It allows us to add a column at any point in the document, not just at the end. It also offers a variety of alternatives for entering column values.

# Add the pandas package to your project.

pandas as a pd import

# Create a dictionary containing information about students.

'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'], data =

[5.1, 6.2, 5.1, 5.2], [5.1, 6.2, 5.1, 5.2],

'Qualification': ['Msc', 'MA', 'Msc', 'Msc', 'Msc', 'Msc', 'Msc']

# Create a DataFrame from the vocabulary.

pd.DataFrame = df (data)

# Adding a column with DataFrame.insert()

df.insert df.insert df.inser (2, "Age", [21, 23, 24, 21], True)

# Take note of the df Output:

The third way is to use the Dataframe.assign() method.

This method will generate a new dataframe with the previous dataframe's new column added to it.

# Add the pandas package to your project.

pandas as a pd import

# Create a dictionary containing information about students.

'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'], data =

[5.1, 6.2, 5.1, 5.2], [5.1, 6.2, 5.1, 5.2],

'Qualification': ['Msc', 'MA', 'Msc', 'Msc', 'Msc', 'Msc', 'Msc']

# Create a DataFrame from the vocabulary.

pd.DataFrame = df (data)

# Using the column name 'Address' and equating it to the list

df2 = df.assign(address = ['Delhi, Bengaluru, Chennai, Patna])

# Take a look at the df2 output:

The fourth method is to use a dictionary.

To add a new column to a pandas DataFrame, we can use a Python dictionary. Use an existing column as the key value, and the values in that column will be the new column's values.

# Add the pandas package to your project.

pandas as a pd import

# Create a dictionary containing information about students.

'Name': ['Jai', 'Princi', 'Gaurav', 'Anuj'], data =

[5.1, 6.2, 5.1, 5.2], [5.1, 6.2, 5.1, 5.2],

'Qualification': ['Msc', 'MA', 'Msc', 'Msc', 'Msc', 'Msc', 'Msc']

# Create a dictionary with the key values of an existing column and their corresponding # value pairs as our new column's values.

address = 'Jai' in Delhi, 'Princi' in Bangalore,

'Gaurav' in Patna, 'Anuj' in Chennai

# Create a DataFrame from the vocabulary.

pd.DataFrame = df (data)

# Set the column name to 'Address'.

address = df['Address']

# Take note of the output df Output:

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