Reshaping DataFrame in Pandas: pivot_table vs. manual Loop

Last update on December 21 2024 07:42:50 (UTC/GMT +8 hours)

Pandas: Performance Optimization Exercise-16 with Solution

Write a Pandas program that uses the pivot_table method to reshape a DataFrame and compares the performance with manual reshaping using for loops.

Sample Solution :

Python Code :

# Import necessary libraries
import pandas as pd
import numpy as np
import time

# Create a sample DataFrame
num_rows = 1000000
df = pd.DataFrame({
    'A': np.random.choice(['foo', 'bar', 'baz'], size=num_rows),
    'B': np.random.choice(['one', 'two', 'three'], size=num_rows),
    'values': np.random.randn(num_rows)
})

# Measure time for pivot_table method
start_time = time.time()
pivot_table_result = df.pivot_table(index='A', columns='B', values='values', aggfunc='mean')
end_time = time.time()
pivot_table_time = end_time - start_time

# Measure time for manual reshaping using for loops
start_time = time.time()
result = {}
for a in df['A'].unique():
    result[a] = {}
    for b in df['B'].unique():
        result[a][b] = df[(df['A'] == a) & (df['B'] == b)]['values'].mean()

manual_reshape_result = pd.DataFrame(result).T
end_time = time.time()
manual_reshape_time = end_time - start_time

# Print the time taken for each method
print(f"Time taken using pivot_table method: {pivot_table_time:.6f} seconds")
print(f"Time taken using manual reshaping: {manual_reshape_time:.6f} seconds")

Output:

Time taken using pivot_table method: 0.130437 seconds
Time taken using manual reshaping: 1.244391 seconds

Explanation:

• Import Libraries:
• Import pandas, numpy, and time.
• Create DataFrame:
• Generate a sample DataFrame with 1,000,000 rows, with categorical columns 'A' and 'B', and a numerical column 'values'.
• Time Measurement for pivot_table Method:
• Measure the time taken to reshape the DataFrame using the pivot_table method.
• Time Measurement for Manual Reshaping:
• Measure the time taken to manually reshape the DataFrame using nested for loops and mean calculations.
• Print Results:
• Print the time taken for each method.

Python-Pandas Code Editor:

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