import cudf df = cudf.DataFrame({ 'name': ['Alice', 'Bob', 'Charlie'], 'age': [25, 30, 35], 'country': ['USA', 'Canada', 'UK'] })
import cudf df = cudf.DataFrame({ 'name': ['Alice', 'Bob', 'Charlie'], 'age': [25, 30, 35], 'country': ['USA', 'Canada', 'UK'] }) filtered_df = df[df['age'] > 30]
import cudf df = cudf.DataFrame({ 'name': ['Alice', 'Bob', 'Charlie', 'Diana', 'Eve'], 'age': [25, 30, 35, 25, 30], 'country': ['USA', 'Canada', 'UK', 'USA', 'Canada'] }) grouped_df = df.groupby('country').mean()This example groups the DataFrame by the country column and calculates the mean age for each group. Overall, the cudf.core DataFrame package library provides a powerful tool for working with large datasets on GPUs.