pandas ValueError：无法在具有新类别的类别上设置项目，请先设置类别

Question

现在，我正在更改 DataFrame 内的信息，将 Yes 替换为 1，No 替换为 0。以前，我的代码工作正常，现在由于内存问题我做了一些更改。

以前的代码“出现下面提到的回溯错误”

df.loc[df[df.decision == 'Yes'].index, 'decision'] = 1
df.loc[df[df.decision == 'No'].index, 'decision'] = 0

更改为

df.loc['Yes', "decision"] = 1
df.loc['No', "decision"] = 0

尽管如此，问题仍然是一样的。

追溯

Traceback (most recent call last):
  File "/snap/pycharm-community/226/plugins/python-ce/helpers/pydev/pydevd.py", line 1477, in _exec
    pydev_imports.execfile(file, globals, locals)  # execute the script
  File "/snap/pycharm-community/226/plugins/python-ce/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "/home/khawar/deepface/tests/Ensemble-Face-Recognition.py", line 148, in <module>
    df.loc['Yes', "decision"] = 1
  File "/home/khawar/.local/lib/python3.6/site-packages/pandas/core/indexing.py", line 670, in __setitem__
    iloc._setitem_with_indexer(indexer, value)
  File "/home/khawar/.local/lib/python3.6/site-packages/pandas/core/indexing.py", line 1763, in _setitem_with_indexer
    isetter(loc, value)
  File "/home/khawar/.local/lib/python3.6/site-packages/pandas/core/indexing.py", line 1689, in isetter
    ser._mgr = ser._mgr.setitem(indexer=plane_indexer, value=v)
  File "/home/khawar/.local/lib/python3.6/site-packages/pandas/core/internals/managers.py", line 543, in setitem
    return self.apply("setitem", indexer=indexer, value=value)
  File "/home/khawar/.local/lib/python3.6/site-packages/pandas/core/internals/managers.py", line 409, in apply
    applied = getattr(b, f)(**kwargs)
  File "/home/khawar/.local/lib/python3.6/site-packages/pandas/core/internals/blocks.py", line 1688, in setitem
    self.values[indexer] = value
  File "/home/khawar/.local/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 2011, in __setitem__
    "Cannot setitem on a Categorical with a new "
ValueError: Cannot setitem on a Categorical with a new category, set the categories first
python-BaseException

按照建议我实现了新代码

df['decision'] = (df['decision'] == 'Yes').astype(int)

追溯

Traceback (most recent call last):
  File "/home/khawar/deepface/tests/Ensemble-Face-Recognition.py", line 174, in <module>
    gbm = lgb.train(params, lgb_train, num_boost_round=1000, early_stopping_rounds=15, valid_sets=lgb_test)
  File "/home/khawar/.local/lib/python3.6/site-packages/lightgbm/engine.py", line 231, in train
    booster = Booster(params=params, train_set=train_set)
  File "/home/khawar/.local/lib/python3.6/site-packages/lightgbm/basic.py", line 2053, in __init__
    train_set.construct()
  File "/home/khawar/.local/lib/python3.6/site-packages/lightgbm/basic.py", line 1325, in construct
    categorical_feature=self.categorical_feature, params=self.params)
  File "/home/khawar/.local/lib/python3.6/site-packages/lightgbm/basic.py", line 1123, in _lazy_init
    self.__init_from_np2d(data, params_str, ref_dataset)
  File "/home/khawar/.local/lib/python3.6/site-packages/lightgbm/basic.py", line 1162, in __init_from_np2d
    data = np.array(mat.reshape(mat.size), dtype=np.float32)
ValueError: could not convert string to float: 'deepface/tests/dataset/029A33.JPG'

Answer 1

在您的解决方案中存在问题，存在categorical列，因此如果仅替换某些行，熊猫希望将输出列设置为分类，并且因为0,1类别中不存在会引发错误。

带有分类列的示例数据：

df = pd.DataFrame({'decision':['Yes','No']})

df['decision'] = pd.Categorical(df['decision'])

Series.map具有分类输出的解决方案cat.rename_categories：

df['decision1'] = df['decision'].map({'Yes':1, 'No':0})
df['decision2'] = df['decision'].cat.rename_categories({'Yes':1, 'No':0})

如果只有Yes和No值可以通过比较Yes并转换为整数来重新创建所有值以True, False进行1,0映射，如提到的@arhr，则分类会丢失：

df['decision3'] = (df['decision'] == 'Yes').astype(int)
print (df)
  decision decision1  decision2 decision3
0      Yes         1          1         1
1       No         0          0         0

print (df.dtypes)
decision     category
decision1    category
decision2    category  
decision3       int32
dtype: object