Upsampling Time Series data from daily to Hourly Frequency

Last update on December 21 2024 07:54:58 (UTC/GMT +8 hours)

Pandas Resampling and Frequency Conversion: Exercise-2 with Solution

Write a Pandas program to upsample daily time series data to hourly frequency.

Sample Solution:

Python Code :

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

# Create a time series data with daily frequency
date_rng = pd.date_range(start='2021-01-01', end='2021-01-05', freq='D')
ts = pd.Series(np.random.randn(len(date_rng)), index=date_rng)

# Upsample the time series to hourly frequency
ts_hourly = ts.resample('H').ffill()

# Display the upsampled time series
print(ts_hourly)

Output:

2021-01-01 00:00:00    0.171632
2021-01-01 01:00:00    0.171632
2021-01-01 02:00:00    0.171632
2021-01-01 03:00:00    0.171632
2021-01-01 04:00:00    0.171632
  
2021-01-04 20:00:00    3.045198
2021-01-04 21:00:00    3.045198
2021-01-04 22:00:00    3.045198
2021-01-04 23:00:00    3.045198
2021-01-05 00:00:00   -1.323064
Freq: H, Length: 97, dtype: float64

Explanation:

• Import Pandas and NumPy libraries.
• Create a date range with daily frequency.
• Generate a random time series data with the created date range.
• Upsample the time series data to hourly frequency by forward filling the values.
• Print the upsampled time series data.

Python Code Editor:

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