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Description
Describe the bug
The origin periods are incorrect when creating a quarterly triangle object with non-standard Quarter periods (Feb-Apr, May-Jul, Aug-Oct, Nov-Jan). IN my example below, I have non-standard quarter periods and when I try to create a Triangle object from the data, I get incorrect origin periods. The amounts seem to lagging. Compare the below image with the pandas dataframe.
To Reproduce
Steps to reproduce the behavior. Code should be self-contained and runnable against publicly available data. For example:
import chainladder as cl
import pandas as pd
data= pd.DataFrame([
["5/1/2023", 12, '4/30/2024', 100],
["8/1/2023", 9, "4/30/2024", 130],
["11/1/2023", 6, "4/30/2024", 160],
["2/1/2024", 3, "4/30/2024", 140]],
columns = ['origin', 'development', 'valuation', 'EarnedPremium'])
triangle = cl.Triangle(
data, origin='origin', origin_format='%Y-%m-%d', development='valuation', columns='EarnedPremium', trailing=True, cumulative=True
)
data_from_tri = triangle.to_frame(origin_as_datetime=True)
Expected behavior:
The periods seem to not match with the original data. The expected result should look something like this:
Desktop (please complete the following information):
- Numpy Version 1.26.4
- Pandas Version 2.2.2
- Chainladder Version 0.8.20