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fix(examples): handle NaNs in 14-transfer-learning air dataset #3116

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fix(examples): handle NaNs in 14-transfer-learning air dataset #3116

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2 changes: 2 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -13,6 +13,8 @@ but cannot always guarantee backwards compatibility. Changes that may **break co

**Fixed**

- Fixed `examples/14-transfer-learning.ipynb` raising a NaN error on the `air` dataset: the `load_air()` helper now calls `fill_missing_values(..., fill="auto")` after `longest_contiguous_slice()` to handle residual gaps in the raw `carrier_passengers.csv`. Closes [#2752](https://github.com/unit8co/darts/issues/2752).
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@jakubchlapek jakubchlapek May 16, 2026

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For future reference, refer to the PR number and link here :) also if you want take credit (by ...)

Suggested change
- Fixed `examples/14-transfer-learning.ipynb` raising a NaN error on the `air` dataset: the `load_air()` helper now calls `fill_missing_values(..., fill="auto")` after `longest_contiguous_slice()` to handle residual gaps in the raw `carrier_passengers.csv`. Closes [#2752](https://github.com/unit8co/darts/issues/2752).
- Fixed `examples/14-transfer-learning.ipynb` raising a NaN error on the `air` dataset by calling `fill_missing_values(..., fill="auto")` to handle residual gaps in the raw `carrier_passengers.csv`. Closes [#3116](https://github.com/unit8co/darts/pull/3116).


**Dependencies**

### For developers of the library:
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8 changes: 7 additions & 1 deletion examples/14-transfer-learning.ipynb
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Expand Up @@ -130,7 +130,8 @@
" RandomForestModel,\n",
" Theta,\n",
")\n",
"from darts.utils.losses import SmapeLoss"
"from darts.utils.losses import SmapeLoss\n",
"from darts.utils.missing_values import fill_missing_values"
]
},
{
Expand Down Expand Up @@ -244,6 +245,11 @@
" series = series.longest_contiguous_slice()\n",
" except Exception:\n",
" continue\n",
" # Fill any residual missing values inside the chosen slice. The raw\n",
" # carrier_passengers.csv occasionally has gaps that survive the\n",
" # longest_contiguous_slice() call (e.g. zero-rows), which produce NaNs\n",
" # downstream and break model training. See issue #2752.\n",
" series = fill_missing_values(series, fill=\"auto\")\n",
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@jakubchlapek jakubchlapek May 16, 2026

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bit too verbose compared to the rest of the notebook
should be fine with just

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" # downstream and break model training. See issue #2752.\n",
" series = fill_missing_values(series, fill=\"auto\")\n",
" # fill missing values\n",
" series = fill_missing_values(series, fill=\"auto\")\n",

" # remove static covariates\n",
" series = series.with_static_covariates(None)\n",
" # remove short series\n",
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