w3resource

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:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous:Pandas Resampling Frequency Conversion Exercises Home.
Next: Upsampling Time Series data from daily to Hourly Frequency.

What is the difficulty level of this exercise?

Test your Programming skills with w3resource's quiz.



Become a Patron!

Follow us on Facebook and Twitter for latest update.

It will be nice if you may share this link in any developer community or anywhere else, from where other developers may find this content. Thanks.

https://198.211.115.131/python-exercises/pandas/resampling-frequency-conversion/resampling-time-series-data-to-daily-frequency-with-pandas.php