Python 如何设置数据帧子集的样式？

我之前问过，我给出的玩具问题得到了完美的答案

原来我应该把玩具的问题和我真正的问题更接近一点。考虑一个数据栏超过1列的文本数据，我可以将其应用到：

作为pd进口熊猫 将numpy作为np导入 导入seaborn作为sns cm=sns。发散调色板-5，5，如cmap=真 df=pd.DataFramenp.random.randn3，4 df['text_column']='a' df['second_text_column']='b' df.style.background_gradientcmap=cm 但是，与上一个问题一样，我只希望将此样式应用于最后一行。对上一个问题的答复是：

df.style.background_gradientcmap=cm，subset=df.index[-1] 在这种情况下，会出现以下错误：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
/usr/local/miniconda/lib/python3.7/site-packages/IPython/core/formatters.py in __call__(self, obj)
    343             method = get_real_method(obj, self.print_method)
    344             if method is not None:
--> 345                 return method()
    346             return None
    347         else:

/usr/local/miniconda/lib/python3.7/site-packages/pandas/io/formats/style.py in _repr_html_(self)
    161         Hooks into Jupyter notebook rich display system.
    162         """
--> 163         return self.render()
    164 
    165     @Appender(_shared_docs['to_excel'] % dict(

/usr/local/miniconda/lib/python3.7/site-packages/pandas/io/formats/style.py in render(self, **kwargs)
    457         * table_attributes
    458         """
--> 459         self._compute()
    460         # TODO: namespace all the pandas keys
    461         d = self._translate()

/usr/local/miniconda/lib/python3.7/site-packages/pandas/io/formats/style.py in _compute(self)
    527         r = self
    528         for func, args, kwargs in self._todo:
--> 529             r = func(self)(*args, **kwargs)
    530         return r
    531 

/usr/local/miniconda/lib/python3.7/site-packages/pandas/io/formats/style.py in _apply(self, func, axis, subset, **kwargs)
    536         if axis is not None:
    537             result = data.apply(func, axis=axis,
--> 538                                 result_type='expand', **kwargs)
    539             result.columns = data.columns
    540         else:

/usr/local/miniconda/lib/python3.7/site-packages/pandas/core/frame.py in apply(self, func, axis, broadcast, raw, reduce, result_type, args, **kwds)
   6485                          args=args,
   6486                          kwds=kwds)
-> 6487         return op.get_result()
   6488 
   6489     def applymap(self, func):

/usr/local/miniconda/lib/python3.7/site-packages/pandas/core/apply.py in get_result(self)
    149             return self.apply_raw()
    150 
--> 151         return self.apply_standard()
    152 
    153     def apply_empty_result(self):

/usr/local/miniconda/lib/python3.7/site-packages/pandas/core/apply.py in apply_standard(self)
    255 
    256         # compute the result using the series generator
--> 257         self.apply_series_generator()
    258 
    259         # wrap results

/usr/local/miniconda/lib/python3.7/site-packages/pandas/core/apply.py in apply_series_generator(self)
    284             try:
    285                 for i, v in enumerate(series_gen):
--> 286                     results[i] = self.f(v)
    287                     keys.append(v.name)
    288             except Exception as e:

/usr/local/miniconda/lib/python3.7/site-packages/pandas/core/apply.py in f(x)
     76 
     77             def f(x):
---> 78                 return func(x, *args, **kwds)
     79         else:
     80             f = func

/usr/local/miniconda/lib/python3.7/site-packages/pandas/io/formats/style.py in _background_gradient(s, cmap, low, high, text_color_threshold)
    941             smin = s.values.min()
    942             smax = s.values.max()
--> 943             rng = smax - smin
    944             # extend lower / upper bounds, compresses color range
    945             norm = colors.Normalize(smin - (rng * low), smax + (rng * high))

TypeError: ("unsupported operand type(s) for -: 'str' and 'str'", 'occurred at index text_column')

<pandas.io.formats.style.Styler at 0x7f948dde7278>

对子集使用元组对我来说很有效，但不确定它是否是最优雅的解决方案：

df.style.background_gradient(cmap=cm, 
                             subset=(df.index[-1], df.select_dtypes(float).columns))

输出：

---

虽然我没有收到相同的错误，但感谢您为复制提供了必要的代码。你的python版本是什么？python 3.7.3版本0.24.2适合我！非常感谢你！这一整天都让我发疯：

df.style.background_gradient(cmap=cm, 
                             subset=(df.index[-1], df.select_dtypes(float).columns))