Performance comparison of Resampling time Series data in Pandas
13. Resample Method vs. Manual Resampling
Write a Pandas program to create a time series DataFrame and use the resample method to downsample the data. Measure the performance improvement over manual resampling.
Sample Solution :
Python Code :
Output:
Time taken using resample method: 0.029992 seconds Time taken using manual resampling: 0.021973 seconds
Explanation:
- Import Libraries:
- Import pandas, numpy, and time.
- Create Time Series DataFrame:
- Generate a time series DataFrame with 1,000,000 rows, each representing a minute.
- Set Resampling Frequency:
- Define the frequency for downsampling (e.g., 'H' for hourly).
- Time Measurement for resample Method:
- Measure the time taken to downsample the data using the resample method.
- Time Measurement for Manual Resampling:
- Measure the time taken to downsample the data manually using groupby and "pd.Grouper".
- Print Results:
- Print the time taken for each method.
For more Practice: Solve these Related Problems:
- Write a Pandas program to create a time series DataFrame and use the resample() method to downsample data, measuring performance.
- Write a Pandas program to implement manual resampling of a time series using for loops and compare the execution time with resample().
- Write a Pandas program to benchmark the performance of the resample() method against a custom resampling algorithm.
- Write a Pandas program to generate a downsampled time series using both resample() and manual iteration, then compare results and timing.
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Python-Pandas Code Editor:
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