Resampling Time Series data to Quarterly Frequency
Pandas Resampling and Frequency Conversion: Exercise-9 with Solution
Write a Pandas program to resample Time Series data to quarterly frequency.
Sample Solution:
Python Code :
# Import necessary libraries
import pandas as pd
import numpy as np
# Create a time series data with monthly frequency
date_rng = pd.date_range(start='2019-01-01', end='2019-12-01', freq='M')
ts = pd.Series(np.random.randn(len(date_rng)), index=date_rng)
# Resample the time series to quarterly frequency
ts_quarterly = ts.resample('Q').mean()
# Display the resampled time series
print(ts_quarterly)
Output:
2019-03-31 0.045935 2019-06-30 -1.032537 2019-09-30 0.062271 2019-12-31 1.227764 Freq: Q-DEC, dtype: float64
Explanation:
- Import Pandas and NumPy libraries.
- Create a date range with monthly frequency.
- Generate a random time series data with the created date range.
- Resample the time series data to quarterly frequency by calculating the mean.
- Print the resampled time series data.
Python Code Editor:
Have another way to solve this solution? Contribute your code (and comments) through Disqus.
Previous: Resampling Time Series data with Custom functions.
Next: Resampling Time Series data to Yearly Frequency.
What is the difficulty level of this exercise?
Test your Programming skills with w3resource's quiz.
- Weekly Trends and Language Statistics
- Weekly Trends and Language Statistics