Hello, when importing the variables to build the PD Model, it returns me the following error pointing the problem to the line ·127 ‘mths_since_last_record:>86’]]”
KeyError: 'Passing list-likes to .loc or [] with any missing labels is no longer supported, see https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike'
HI Edu,
Did you use the code provided in the lecture?
If you made some changes, could you please share them with us?
Best,
The 365 Team
Hello 365 Team ,its been 7 months and no concrete information on this issue has been shared from your team. PLease ANSWER Volkmar question as everyone is facing same issue. I have also posted many questions but seems like 365 Team only cares about payment , once payment is done they are least bothered
I had the same problem, even when I copied and pasted the lecture code.
It turns out that using .loc[ ] with one or more missing labels is now deprecated (starting in version 0.2.1.0). The documentation (https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#indexing-deprecate-loc-reindex-listlike) suggests using .reindex() instead.
This worked for me:
inputs_train_with_ref_cat = loan_data_inputs_train.reindex([ list of column names ], axis=1)
Hello all,
I replaced .loc with .reindex and I get after
inputs_train = inputs_train_with_ref_cat.drop(ref_categories, axis = 1)
inputs_train.head()
Many NaN:
grade:A 0 grade:B 0 grade:C 0 grade:D 0 grade:E 0
... mths_since_last_record:3-20 373028 mths_since_last_record:21-31 373028 mths_since_last_record:32-80 373028 mths_since_last_record:81-86 373028 mths_since_last_record:>=86 373028 Length: 104, dtype: int64
It seems, that it doesn't work really with .reindex.
If I open the data loan_data_inputs_train.csv and all other, I do not find any NaN. All data are normal.
Any idea?
Best regard
Volkmar Meiller
Yes, I agree with Volkmar about retaining the indexes.
The best approach to this is using List comprehensions instead of Columns List . My solution can be found on the below link :
https://stackoverflow.com/a/65146867/14605502
Hope it helps!