pandas - Subsetting Rows with Categorical Variables

Data Import

Since there is no categorical variables in Boston dataset, I will just show you the example using dummy dataset.

Let's consider a hypothetical dataset called "employee_data" with a categorical variable "Department" and other numerical features. We will use this dataset to subset rows based on the "Department" category.

 

# Sample employee data with a categorical variable "Department"

data = {

    'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Ella'],

    'Age': [25, 30, 22, 27, 28],

    'Department': ['HR', 'IT', 'Finance', 'HR', 'IT'],

    'Salary': [50000, 60000, 45000, 55000, 58000]

}

employee_data = pd.DataFrame(data)

 

Subsetting rows based on the categorical variable "Department"

# Subsetting rows based on the categorical variable "Department"

hr_department = employee_data[employee_data['Department'] == 'HR']

it_department = employee_data[employee_data['Department'] == 'IT']

finance_department = employee_data[employee_data['Department'] == 'Finance']

print("HR Department:")

print(hr_department)

print("\nIT Department:")

print(it_department)

print("\nFinance Department:")

print(finance_department)

 

Filtering Categorical Variables using .isin()

Below is an example of using .isin() instead.

# Subsetting rows based on the categorical variable "Department" using isin() function

selected_departments = employee_data[employee_data['Department'].isin(['HR', 'IT'])]

finance_department = employee_data[employee_data['Department'].isin(['Finance'])]

print("HR and IT Departments:")

print(selected_departments)

print("\nFinance Department:")

print(finance_department)

 

 

https://ai-fin-tech.tistory.com/entry/Adding-New-Columns-and-Rows-to-DataFrame-with-pandas

Adding New Columns and Rows to DataFrame with pandas