Resampling Time Series data to Business day Frequency

Pandas Resampling and Frequency Conversion: Exercise-6 with Solution

Write a Pandas program to resample Time Series Data to Business day Frequency.

Sample Solution:

Python Code :

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

# Create a time series data with daily frequency including weekends
date_rng = pd.date_range(start='2020-01-01', end='2020-01-10', freq='D')
ts = pd.Series(np.random.randn(len(date_rng)), index=date_rng)

# Resample the time series to business day frequency
ts_bday = ts.resample('B').mean()

# Display the resampled time series
print(ts_bday) 

Output:

2020-01-01    0.464848
2020-01-02    0.110731
2020-01-03   -0.322476
2020-01-06    1.465602
2020-01-07   -0.410054
2020-01-08   -1.832310
2020-01-09    1.634878
2020-01-10   -0.236743
Freq: B, dtype: float64

Explanation:

• Import Pandas and NumPy libraries.
• Create a date range with daily frequency including weekends.
• Generate a random time series data with the created date range.
• Resample the time series data to business day frequency by calculating the mean.
• Print the resampled time series data.

Python Code Editor:

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