[fix] Raise ValueError when df contains not enough rows

[judussoari]

🔬 Background

• Fixes Unclear error when doing auto-regression with too small dataset #1294
• Closes Unclear error when doing auto-regression with too many forecasts and lags. #1257

When using auto-regression with a dataset that is smaller than n_forecasts + n_lags the fit method throws an IndexError. This hides the real problem, which is that the user is trying to train a model on not enough data.

🔮 Key changes

• raise an error which tells the user to lower the number of forecasts and/or lags, or asks for a larger dataset

📋 Review Checklist

• I have performed a self-review of my own code.
• I have commented my code, added docstrings and data types to function definitions.
• I have added pytests to check whether my feature / fix works.

[github-actions]

Model Benchmark

Benchmark	Metric	main	current	diff
AirPassengers	MAE_val	13.0626	13.0626	0.0%	✅
AirPassengers	RMSE_val	15.9453	15.9453	0.0%	✅
AirPassengers	Loss_val	0.00131	0.00131	0.0%	✅
AirPassengers	MAE	9.88156	9.88156	0.0%	✅
AirPassengers	RMSE	11.7354	11.7354	0.0%	✅
AirPassengers	Loss	0.00052	0.00052	0.0%	✅
AirPassengers	time	5.29164	4.82	-8.91%	🎉
YosemiteTemps	MAE_val	1.3442	1.3442	0.0%	✅
YosemiteTemps	RMSE_val	2.00245	2.00245	0.0%	✅
YosemiteTemps	Loss_val	0.00077	0.00077	0.0%	✅
YosemiteTemps	MAE	1.3192	1.3192	0.0%	✅
YosemiteTemps	RMSE	2.13518	2.13518	0.0%	✅
YosemiteTemps	Loss	0.00064	0.00064	0.0%	✅
YosemiteTemps	time	65.9804	60.19	-8.78%	🎉
PeytonManning	MAE_val	0.58159	0.58159	0.0%	✅
PeytonManning	RMSE_val	0.72216	0.72216	0.0%	✅
PeytonManning	Loss_val	0.01239	0.01239	0.0%	✅
PeytonManning	MAE	0.41671	0.41671	0.0%	✅
PeytonManning	RMSE	0.55961	0.55961	0.0%	✅
PeytonManning	Loss	0.00612	0.00612	0.0%	✅
PeytonManning	time	12.193	11.77	-3.47%	✅

Model training plots

Model Training

PeytonManning

YosemiteTemps

AirPassengers

[codecov-commenter]

Codecov Report

Merging #1300 (0a6f441) into main (b9ffa72) will increase coverage by 0.00%.
The diff coverage is 100.00%.

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@@           Coverage Diff           @@
##             main    #1300   +/-   ##
=======================================
  Coverage   89.87%   89.87%           
=======================================
  Files          38       38           
  Lines        5134     5136    +2     
=======================================
+ Hits         4614     4616    +2     
  Misses        520      520           

Impacted Files	Coverage Δ
neuralprophet/data/process.py	92.56% <100.00%> (+0.06%)	⬆️

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[leoniewgnr]

LGTM