[FIXED] ValueError: A given column is not a column of the dataframe

Issue

Everyone

I am trying to create a pipeline using the scikit-learn.

Basically, I have a jupyter-notebook that loading data using pandas, split dataset to train and test the model.

My problem occur in the line: clf.fit(X_train, y_train) you can see the whole code on my github repo jupyter-notebook

log error:

----------------------------------------------------------------------
KeyError                             Traceback (most recent call last)
~/anaconda3/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   2656             try:
-> 2657                 return self._engine.get_loc(key)
   2658             except KeyError:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'survived'

During handling of the above exception, another exception occurred:

KeyError                             Traceback (most recent call last)
~/anaconda3/lib/python3.7/site-packages/sklearn/utils/__init__.py in _get_column_indices(X, key)
    446             for col in columns:
--> 447                 col_idx = all_columns.get_loc(col)
    448                 if not isinstance(col_idx, numbers.Integral):

~/anaconda3/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   2658             except KeyError:
-> 2659                 return self._engine.get_loc(self._maybe_cast_indexer(key))
   2660         indexer = self.get_indexer([key], method=method, tolerance=tolerance)

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()

KeyError: 'survived'

The above exception was the direct cause of the following exception:

ValueError                           Traceback (most recent call last)
<ipython-input-16-17661ab0f723> in <module>
----> 1 clf.fit(X_train, y_train)
      2 print("model score: %.3f" % clf.score(X_test, y_test))

~/anaconda3/lib/python3.7/site-packages/sklearn/pipeline.py in fit(self, X, y, **fit_params)
    328         """
    329         fit_params_steps = self._check_fit_params(**fit_params)
--> 330         Xt = self._fit(X, y, **fit_params_steps)
    331         with _print_elapsed_time('Pipeline',
    332                                  self._log_message(len(self.steps) - 1)):

~/anaconda3/lib/python3.7/site-packages/sklearn/pipeline.py in _fit(self, X, y, **fit_params_steps)
    294                 message_clsname='Pipeline',
    295                 message=self._log_message(step_idx),
--> 296                 **fit_params_steps[name])
    297             # Replace the transformer of the step with the fitted
    298             # transformer. This is necessary when loading the transformer

~/anaconda3/lib/python3.7/site-packages/joblib/memory.py in __call__(self, *args, **kwargs)
    350 
    351     def __call__(self, *args, **kwargs):
--> 352         return self.func(*args, **kwargs)
    353 
    354     def call_and_shelve(self, *args, **kwargs):

~/anaconda3/lib/python3.7/site-packages/sklearn/pipeline.py in _fit_transform_one(transformer, X, y, weight, message_clsname, message, **fit_params)
    738     with _print_elapsed_time(message_clsname, message):
    739         if hasattr(transformer, 'fit_transform'):
--> 740             res = transformer.fit_transform(X, y, **fit_params)
    741         else:
    742             res = transformer.fit(X, y, **fit_params).transform(X)

~/anaconda3/lib/python3.7/site-packages/sklearn/compose/_column_transformer.py in fit_transform(self, X, y)
    527         self._validate_transformers()
    528         self._validate_column_callables(X)
--> 529         self._validate_remainder(X)
    530 
    531         result = self._fit_transform(X, y, _fit_transform_one)

~/anaconda3/lib/python3.7/site-packages/sklearn/compose/_column_transformer.py in _validate_remainder(self, X)
    325         cols = []
    326         for columns in self._columns:
--> 327             cols.extend(_get_column_indices(X, columns))
    328 
    329         remaining_idx = sorted(set(range(self._n_features)) - set(cols))

~/anaconda3/lib/python3.7/site-packages/sklearn/utils/__init__.py in _get_column_indices(X, key)
    454             raise ValueError(
    455                 "A given column is not a column of the dataframe"
--> 456             ) from e
    457 
    458         return column_indices

ValueError: A given column is not a column of the dataframe

I checked if the columns exist before of pass the dataframe to split in train and test.

Someone have some idea of how to solve this issue?

Thanks in advance! Cheers

Solution

The error comes from the fact that you from the very beginning drop the column survived when defining X. You only checked its presence in y_train.

Simply replace

X= df.drop('survived', axis=1)

by

X= df 

and your

clf.fit(X_train, y_train)
print("model score: %.3f" % clf.score(X_test, y_test))

returns

model score: 1.000

Answered By - Serge de Gosson de Varennes