Incorrect as-of-date year in Postmodeling plots?

In `dirtyduck` the last prediction `as-of-date` is `2017-12-01`. The following table is a fragment of the final models from the inspections part of `dirtyduck`:

```| model_group_id | model_type | hyperparameters | feature_groups | models | times | precision@10% |
|--------------+-----------------------------------------+-----------------------------------------------------------------------------------------+----------------------------------------+-------------+------------------------------------+------------------------------|
| 1 | sklearn.dummy.DummyClassifier | {"strategy": "prior"} | {inspections} | {1,4,7} | {2015-12-01,2016-12-01,2017-12-01} | {" 0.295"," 0.242"," 0.251"} |
| 2 | sklearn.dummy.DummyClassifier | {"strategy": "uniform"} | {inspections} | {2,5,8} | {2015-12-01,2016-12-01,2017-12-01} | {" 0.295"," 0.242"," 0.251"} |
| 3 | sklearn.dummy.DummyClassifier | {"strategy": "most_frequent"} | {inspections} | {3,6,9} | {2015-12-01,2016-12-01,2017-12-01} | {" 0.295"," 0.242"," 0.251"} |

```

Creating the plot for performance over time:

```python
audited_models_class.plot_prec_across_time(param_type='rank_pct',
param=10,
baseline=True,
baseline_query=params.baseline_query,
metric='precision@',
figsize=params.figsize)
```

Gives you the following plot:


Note the years.

`Audition` makes a similar plot: