Issue with chainladder.Triangle Output - Column Misalignment in Python 3.11.5 & chainladder 0.8.23

[copythontest]

I'm 1st time using the chainladder library in Python (version 3.11.5, chainladder version 0.8.23) to process claims data. However, when I create a Triangle object, the output appears misaligned. The cumulative development periods seem to be shifted, with data appearing in the 24th column instead of the expected 12th column.

import os
import pandas as pd
import chainladder as cl

script_dir = os.getcwd()
file_path = os.path.join(script_dir, "test_file_data.xlsx")

df = pd.read_excel(file_path, sheet_name="Sheet1")

expected_columns = {"accident_year": "origin", "dev_period": "development", "claims_incurred": "values"}

missing_cols = [col for col in expected_columns.keys() if col not in df.columns]
if missing_cols:
raise ValueError(f"Missing required columns: {missing_cols}")

df.rename(columns=expected_columns, inplace=True)
df.dropna(subset=["origin", "development", "values"], inplace=True)

df["origin"] = pd.to_numeric(df["origin"], errors="coerce")
df["development"] = pd.to_numeric(df["development"], errors="coerce")
df["values"] = pd.to_numeric(df["values"], errors="coerce")

df["development"] = df["origin"] + df["development"]

triangle = cl.Triangle(df, origin="origin", development="development", values="values")
print(triangle)

Sample Data

accident_year	dev_period	claims_incurred
2013	10	5651.600965
2016	6	24.18696974
2016	6	22.35478661
2016	7	5331.37277
2016	7	641.7096825
2021	3	7780.388433
2017	2	3707.471613
2017	4	3494.854585
2017	5	3405.485586
2017	5	179252.9788

Unexpected Output
The output appears to have a shift, showing values under the 24th development period column instead of the 12th column: (output values are accurate, but in this format )

	12	24	36	48	60	72	84	96	108	120	132	144	156
2013-01-01 00:00:00		xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx
2014-01-01 00:00:00		xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx
2015-01-01 00:00:00		xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx
2016-01-01 00:00:00		xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx
2017-01-01 00:00:00		xxx	xxx	xxx	xxx	xxx	xxx	xxx	xxx
2018-01-01 00:00:00		xxx	xxx	xxx	xxx	xxx	xxx	xxx
2019-01-01 00:00:00		xxx	xxx	xxx	xxx	xxx	xxx
2020-01-01 00:00:00		xxx	xxx	xxx	xxx	xxx
2021-01-01 00:00:00		xxx	xxx	xxx	xxx
2022-01-01 00:00:00		xxx	xxx	xxx
2023-01-01 00:00:00		xxx	xxx
2024-01-01 00:00:00		xxx

Question
Why is my triangle output misaligned?
Is there an issue with how I'm defining the development period ?
What would be the correct way to ensure the development periods align properly in the Triangle object?
Any insights or suggestions would be greatly appreciated!

[jbogaardt]

Hard to tell with the above but the suggestions I would make are:

1. If you're creating a cl.Triangle using development lags as opposed to valuations, then it won't work. This is because a lag of 1 could mean 1 month, 1 quarter or 1 year. To remove ambiguity only valuation-like values (year, year-month, year-quarter, date) are accepted for defining development.
2. Off-by-one issues have been a problem since pandas 2.2 which had a few datetime behavior changes. We've made efforts to conform to pandas>2.2, so if you're on an earlier version, it might produce unintended behavior. I'd recommend upgrading pandas and chainladder to latest versions, and see if your problem persists.
   If neither of these suggestions help, let me know.

[copythontest]

Thank you for the suggestions!

1. I was initially defining development as origin + dev_period, which might be causing ambiguity. Based on your feedback, I’ve modified it to use actual valuation dates. I tried using apply() with pd.DateOffset(years=int(row["development"])) to ensure development is a proper valuation date rather than a numeric lag. However, I'm still facing unexpected output in the cl.Triangle structure. Could you confirm if this is the correct approach, or suggest a better way to define development?

2. Regarding the second point, I’m already using the latest versions: Python 3.11.5, chainladder 0.8.23, and pandas 2.2+, but I’m still experiencing the same issue.