import dask.dataframe as dd

# Read a large CSV file into a Dask DataFrame
ddf = dd.read_csv('large_dataset.csv')

# Compute the mean of a column
mean_value = ddf['column_name'].mean().compute()
print(f'Mean value of column: {mean_value}')

# Filter rows based on a condition
filtered_ddf = ddf[ddf['column_name'] > 50]

# Compute the result and convert to a Pandas DataFrame
result_df = filtered_ddf.compute()
print(result_df.head())