Resampling Time Series data to daily Frequency
Pandas Resampling and Frequency Conversion: Exercise-1 with Solution
Write a Pandas program to resample time series data to daily frequency.
Sample Solution:
Python Code :
# Import necessary libraries
import pandas as pd
import numpy as np
# Create a time series data with hourly frequency
date_rng = pd.date_range(start='2023-01-01', end='2023-01-05', freq='H')
ts = pd.Series(np.random.randn(len(date_rng)), index=date_rng)
# Resample the time series to daily frequency
ts_daily = ts.resample('D').mean()
# Display the resampled time series
print(ts_daily)
Output:
2023-01-01 0.079969 2023-01-02 -0.174736 2023-01-03 0.052439 2023-01-04 0.097063 2023-01-05 0.437323 Freq: D, dtype: float64
Explanation:
- Import Pandas and NumPy libraries.
- Create a date range with hourly frequency.
- Generate a random time series data with the created date range.
- Resample the time series data to daily frequency by calculating the mean.
- Print the resampled time series data.
Python Code Editor:
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Next: Upsampling Time Series data from daily to Hourly Frequency.
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