エラーどこパンダとカテゴリの列を持つ

Question

問題：カテゴリ列を持つデータフレームとの句はとValueErrorを生成どこ使用して：私はちょうど私が間違っているのかを把握することはできません寸法

の数が誤っています。

df=pd.read_csv("F:/python/projects/mail/Inbox_20160911-1646/rows.csv",header=0,sep=",",quotechar="'",quoting=1) 
df.where(df > 100) # WORKS !!!! 

for c in [x for x in df.columns[2:] if df[x].dtype == "object" ]: 
    cl="c"+c 
    df[cl]=df[c].astype("category") 

df.where(df > 100) # ---> ValueError: Wrong number of dimensions 

    df.where(df > 100) 
--------------------------------------------------------------------------- 
ValueError        Traceback (most recent call last) 
<ipython-input-278-7469c620cf83> in <module>() 
----> 1 df.where(df > 100) 

F:\python\anaconda3\lib\site-packages\pandas\core\ops.py in f(self, other) 
    1182    # straight boolean comparisions we want to allow all columns 
    1183    # (regardless of dtype to pass thru) See #4537 for discussion. 
-> 1184    res = self._combine_const(other, func, raise_on_error=False) 
    1185    return res.fillna(True).astype(bool) 
    1186 

F:\python\anaconda3\lib\site-packages\pandas\core\frame.py in _combine_const(self, other, func, raise_on_error) 
    3553 
    3554   new_data = self._data.eval(func=func, other=other, 
-> 3555         raise_on_error=raise_on_error) 
    3556   return self._constructor(new_data) 
    3557 

F:\python\anaconda3\lib\site-packages\pandas\core\internals.py in eval(self, **kwargs) 
    2909 
    2910  def eval(self, **kwargs): 
-> 2911   return self.apply('eval', **kwargs) 
    2912 
    2913  def quantile(self, **kwargs): 

F:\python\anaconda3\lib\site-packages\pandas\core\internals.py in apply(self, f, axes, filter, do_integrity_check, consolidate, raw, **kwargs) 
    2888 
    2889    kwargs['mgr'] = self 
-> 2890    applied = getattr(b, f)(**kwargs) 
    2891    result_blocks = _extend_blocks(applied, result_blocks) 
    2892 

F:\python\anaconda3\lib\site-packages\pandas\core\internals.py in eval(self, func, other, raise_on_error, try_cast, mgr) 
    1160    result = self._try_cast_result(result) 
    1161 
-> 1162   return [self.make_block(result, fastpath=True,)] 
    1163 
    1164  def where(self, other, cond, align=True, raise_on_error=True, 

F:\python\anaconda3\lib\site-packages\pandas\core\internals.py in make_block(self, values, placement, ndim, **kwargs) 
    179    ndim = self.ndim 
    180 
--> 181   return make_block(values, placement=placement, ndim=ndim, **kwargs) 
    182 
    183  def make_block_same_class(self, values, placement=None, fastpath=True, 

F:\python\anaconda3\lib\site-packages\pandas\core\internals.py in make_block(values, placement, klass, ndim, dtype, fastpath) 
    2516      placement=placement, dtype=dtype) 
    2517 
-> 2518  return klass(values, ndim=ndim, fastpath=fastpath, placement=placement) 
    2519 
    2520 # TODO: flexible with index=None and/or items=None 

F:\python\anaconda3\lib\site-packages\pandas\core\internals.py in __init__(self, values, ndim, fastpath, placement, **kwargs) 
    1661 
    1662   super(ObjectBlock, self).__init__(values, ndim=ndim, fastpath=fastpath, 
-> 1663           placement=placement, **kwargs) 
    1664 
    1665  @property 

F:\python\anaconda3\lib\site-packages\pandas\core\internals.py in __init__(self, values, placement, ndim, fastpath) 
    79    ndim = values.ndim 
    80   elif values.ndim != ndim: 
---> 81    raise ValueError('Wrong number of dimensions') 
    82   self.ndim = ndim 
    83 

とValueError：ここ寸法

Answer 1

の間違った数があなたのエラーを再現する小さなデモ、次のとおりです。

In [11]: df = pd.DataFrame(np.random.randint(0, 10, (5,3)), columns=list('abc')) 

In [12]: df 
Out[12]: 
    a b c 
0 9 9 8 
1 5 6 1 
2 2 9 8 
3 8 1 3 
4 1 5 1 

この作品：

In [13]: df > 1 
Out[13]: 
     a  b  c 
0 True True True 
1 True True False 
2 True True True 
3 True False True 
4 False True False 

In [14]: df['cat'] = df.c.astype('category') 

In [15]: df 
Out[15]: 
    a b c cat 
0 9 9 8 8 
1 5 6 1 1 
2 2 9 8 8 
3 8 1 3 3 
4 1 5 1 1 

これはWrong number of dimensions例外がスローされます：

In [16]: df > 1 
...skipped... 
ValueError: Wrong number of dimensions 

、これは以前のエラーのための本当の理由です：

In [19]: df.cat > 1 
...skipped... 
TypeError: Unordered Categoricals can only compare equality or not 

ソリューション：

In [22]: df.select_dtypes(include=['number']) > 1 
Out[22]: 
     a  b  c 
0 True True True 
1 True True False 
2 True True True 
3 True False True 
4 False True False 

In [23]: np.where(df.select_dtypes(exclude=['category']) > 1) 
Out[23]: 
(array([0, 0, 0, 1, 1, 2, 2, 2, 3, 3, 4], dtype=int64), 
array([0, 1, 2, 0, 1, 0, 1, 2, 0, 2, 1], dtype=int64))