09_tabular: Value Error: Unable to coerce to Series, length must be 1: given 0

Part 1 (2020)
6

I don’t know if this is the best answer, but don’t think it is right to remove the Normalize processor from procs_nn or to remove cont_nn from the Tabular Pandas call. We need the ‘saleElapsed’ continuous variable and we need to normalize it.

I did notice that

df_nn_final.dtypes

YearMade                 int64
ProductSize           category
Coupler_System          object
fiProductClassDesc      object
Hydraulics_Flow         object
ModelID                  int64
saleElapsed             object
fiSecondaryDesc         object
fiModelDesc             object
Enclosure               object
Hydraulics              object
ProductGroup            object
fiModelDescriptor       object
Drive_System            object
Tire_Size               object
SalePrice              float64
dtype: object

After I changed ‘saleElapsed’ to int64, I was about to move past TabularPandas without the error.

df_nn_final.dtypes

YearMade                 int64
ProductSize           category
Coupler_System          object
fiProductClassDesc      object
Hydraulics_Flow         object
ModelID                  int64
saleElapsed              int64
fiSecondaryDesc         object
fiModelDesc             object
Enclosure               object
Hydraulics              object
ProductGroup            object
fiModelDescriptor       object
Drive_System            object
Tire_Size               object
SalePrice              float64
dtype: object

The rest of the neural networks section ran to conclusion and gave a r_mse of 0.226128

preds,targs = learn.get_preds()
r_mse(preds,targs)
0.226128

Not sure if this is the correct answer to this problem, but it gives a better result than removing cont_nn, which gives a r_mse of 0.270476

preds,targs = learn.get_preds()
r_mse(preds,targs)
0.270476

Can someone more experienced weigh in on this? Perhaps @muellerzr?

Thanks,
Jeff

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