Summary statistics
Recall from the previous lesson that NannyML provides five methods for tracking statistical changes in your features.
In this exercise, you will focus on examining the lead_time feature from the Hotel Booking dataset, which indicates how many days in advance a booking was made. By using summation, median, and standard deviation statistics, you can gain valuable insights into how customer booking behavior has evolved over time.
It's important to note that both the reference and analysis sets, as well as the nannyml library, are already pre-loaded and ready for use.
This exercise is part of the course
Monitoring Machine Learning in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Define analyzed column
analyzed_column = [____]
# Intialize sum values calculator
sum_calc = ____.____(
____=____,
chunk_period='m',
timestamp_column_name='timestamp'
)
# Fit, calculate and plot the results
sum_calc.fit(reference)
sum_calc_res = sum_calc.calculate(analysis)
sum_calc_res.plot().show()