ValueError:DataFrame 的真值不明确.使用 a.empty、a.bool()、a.item()、a.any() 或 a.all() [英] ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

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问题描述

我尝试将数据转发到 excel,但收到主题错误.

I try to forward a data to excel but received the subject error.

我想将一些excel文件合并成一个excel文件.首先,我创建了 all_info 数组以将所有数据收集到.

I want to combine some of excel files into one excel file. First I created all_info array in order to collect all data into.

all_info = []

之后我阅读了每个excel文件.Excel文件如下;样本 1、样本 2 等.

After that I read every excel files. Excel files follows; sample1, sample2, and so on.

data = pd.read_excel('sample1.xlsx', 'Sheet1')

我将每个 excel 文件的数据添加到 all_info 数组中,如下所示.

I add each excel files' data into all_info array with below.

for i in range(0, len(data)):
    all_info.append(data)

在我合并 all_info 数组中的所有数据后,我执行了下面的代码,但收到了主题错误.

After I combine all data within all_info array, I executed below code but received the subject error.

df = pd.DataFrame(all_info)
df.to_excel("all_info.xlsx")

您可能会在下方看到错误详情.

You may see error details below.

ValueError                                Traceback (most recent call last)
<ipython-input-85-5bff7d788042> in <module>()
  1 df = pd.DataFrame(all_tweets)
----> 2 df.to_excel("all_info.xlsx")

 /usr/lib/python2.7/dist-packages/pandas/core/frame.pyc in to_excel(self, excel_writer, sheet_name, na_rep, float_format, cols, header, index, index_label, startrow, startcol, engine, merge_cells)
1202         formatted_cells = formatter.get_formatted_cells()
1203         excel_writer.write_cells(formatted_cells, sheet_name,
-> 1204                                  startrow=startrow, startcol=startcol)
1205         if need_save:
1206             excel_writer.save()

/usr/lib/python2.7/dist-packages/pandas/io/excel.pyc in write_cells(self, cells, sheet_name, startrow, startcol)
525             colletter = get_column_letter(startcol + cell.col + 1)
526             xcell = wks.cell("%s%s" % (colletter, startrow + cell.row + 1))
--> 527             xcell.value = _conv_value(cell.val)
528             style = None
529             if cell.style:

/usr/lib/pymodules/python2.7/openpyxl/cell.pyc in _set_value(self, value)
339     def _set_value(self, value):
340         """Set the value and infer type and display options."""
--> 341         self.bind_value(value)
342 
343     value = property(_get_value, _set_value,

/usr/lib/pymodules/python2.7/openpyxl/cell.pyc in bind_value(self, value)
278     def bind_value(self, value):
279         """Given a value, infer type and display options."""
--> 280         self._data_type = self.data_type_for_value(value)
281         if value is None:
282             self.set_value_explicit('', self.TYPE_NULL)

/usr/lib/pymodules/python2.7/openpyxl/cell.pyc in data_type_for_value(self, value)
260         elif isinstance(value, (datetime.datetime, datetime.date, datetime.time, datetime.timedelta)):
261             data_type = self.TYPE_NUMERIC
--> 262         elif not value:
263             data_type = self.TYPE_STRING
264         elif isinstance(value, basestring) and value[0] == '=':

/usr/lib/python2.7/dist-packages/pandas/core/generic.pyc in __nonzero__(self)
674         raise ValueError("The truth value of a {0} is ambiguous. "
675                          "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
--> 676                          .format(self.__class__.__name__))
677 
678     __bool__ = __nonzero__

ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

推荐答案

您是否想做这样的事情?

Do you maybe want to do something like this?

fnames = ['sample1.xls', 'sample2.xls']
all_info = [pd.read_excel(f, 'Sheet1') for f in fnames]
df = pd.concat(all_info)
df.to_excel("all_info.xlsx")

这里,all_info 是一个 DataFrame 列表,其中每个元素都保存着不同的 Excel 数据.然后将它们连接成一个 DataFrame 并保存到磁盘...

Here, all_info is a list of DataFrames, where each elements is holding the different Excel Data. Then they are concatenated into one DataFrame and saved to disk...

这篇关于ValueError:DataFrame 的真值不明确.使用 a.empty、a.bool()、a.item()、a.any() 或 a.all()的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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