KeyError: "['cut'] not found in axis"

I am working with thousands of lines of data trying to narrow a search for certain grains. To do this, I have an 'Asset' column with about 20 different values, of which I need to receive the sum of all of the lines in the adjacent column 'Load'.

I would like to cut the unnecessary rows out of my data set. To start, I relabeled all of the extra assets as 'cut' (as shown in the example below) so that I could manage one .drop command. Here is how it is coded:

df14['Asset'] = df14["Asset"].str.replace('BEANS', 'cut')
df14.drop("cut", axis=0)
set(df14['Asset'])

This is the error I have received:

KeyError                                  Traceback (most recent call last)
<ipython-input-593-40006512df80> in <module>
----> 1 df14.drop("cut", axis=0)
      2 set(df14['Asset'])

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\frame.py in drop(self, labels, axis, index, columns, level, inplace, errors)
   4100             level=level,
   4101             inplace=inplace,
-> 4102             errors=errors,
   4103         )
   4104 

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\generic.py in drop(self, labels, axis, index, columns, level, inplace, errors)
   3912         for axis, labels in axes.items():
   3913             if labels is not None:
-> 3914                 obj = obj._drop_axis(labels, axis, level=level, errors=errors)
   3915 
   3916         if inplace:

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\generic.py in _drop_axis(self, labels, axis, level, errors)
   3944                 new_axis = axis.drop(labels, level=level, errors=errors)
   3945             else:
-> 3946                 new_axis = axis.drop(labels, errors=errors)
   3947             result = self.reindex(**{axis_name: new_axis})
   3948 

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\indexes\base.py in drop(self, labels, errors)
   5338         if mask.any():
   5339             if errors != "ignore":
-> 5340                 raise KeyError("{} not found in axis".format(labels[mask]))
   5341             indexer = indexer[~mask]
   5342         return self.delete(indexer)

KeyError: "['cut'] not found in axis"

I have tried several commands to remove said lines, like:

df14.drop(["cut"], inplace = True) 

df14[~df14['Asset'].isin(to_drop)]
df14[df14['Asset'].str.contains('cut', na = True)]

And all of them yield the same fruits.

When I code

df14 = df14[~df14["Asset"].str.contains('BEANS')]

It does not remove the Load number, which is the next column over, from my final calculations.

Is it possible to remove all rows of data with a certain label so I can trim from 20 assets to 7 assets?

Thank you

pd.drop works by column or row wise. You give column name to drop a column or index to drop a row. Andaxis=0 means index-wise. Since you don't have a index named "cut", it gives the error.

I recommend doing it by:

df = df.loc[df['Asset'] != 'cut']

I believe that df14.drop("cut", axis=0) is failing because it is looking for the value "cut" in the index of df14. You could potentially specify the asset column as an index, see the pandas documentation on drop for how, but I think a better solution might be something along lines of

df14 = df14.query('asset != "cut"') 

I can't say I know if this is the fastest solution since I usually work with small-ish datasets I've not had to worry about performance too much.

This should do the job.
Here you are basically selecting all rows other than 'cut'

df14 = df14.loc[df14['Asset'] != 'cut']