python - Python Pandas数据透视表如何处理'\xc2\xa0'？

我有一个样本数据集，如下所示：

$python - Python Pandas数据透视表如何处理'\xc2\xa0'？-LMLPHP$

所以我想设置时间序列，因此将所有时间序列设置为列标题。所以我的脚本如下：

#!/usr/bin/python
import pandas as pd
import os
from os.path import basename


def generate_timeSeries(fileToProcess):

    df = pd.read_csv(fileToProcess)
    timestamps = df.pivot_table('C_Number',['A_Id', 'P_Id'], 'Time Stamp')

    return timestamps

def main():

    folder_path = "Input/"

    for files in os.listdir(folder_path):

        print "processing",files
        file_to_open = os.path.join(folder_path, files)
        unicoded_file = unicode(file_to_open).encode('utf8')
        TimeSeries_dataframe = generate_timeSeries(unicoded_file)


        TimeSeries_dataframe.to_csv('Output/%s_timeseries.csv' % os.path.splitext(files)[0], sep=',', encoding='utf-8')


if __name__ == "__main__":
    main()

当我尝试运行脚本时，出现以下错误：

pandas.core.groupby.DataError: No numeric types to aggregate

这是完整的错误跟踪：

Traceback (most recent call last):
  File "Error_AuthorTimeSeries.py", line 43, in <module>
    main()
  File "Error_AuthorTimeSeries.py", line 33, in main
    TimeSeries_dataframe = generate_timeSeries(unicoded_file)
  File "Error_AuthorTimeSeries.py", line 16, in generate_timeSeries
    timestamps = df.pivot_table('C_Number',['A_ID', 'P_ID'], 'Time Stamp')
  File "/usr/lib/python2.7/dist-packages/pandas/tools/pivot.py", line 104, in pivot_table
    agged = grouped.agg(aggfunc)
  File "/usr/lib/python2.7/dist-packages/pandas/core/groupby.py", line 437, in agg
    return self.aggregate(func, *args, **kwargs)
  File "/usr/lib/python2.7/dist-packages/pandas/core/groupby.py", line 1994, in aggregate
    return getattr(self, arg)(*args, **kwargs)
  File "/usr/lib/python2.7/dist-packages/pandas/core/groupby.py", line 452, in mean
    return self._cython_agg_general('mean')
  File "/usr/lib/python2.7/dist-packages/pandas/core/groupby.py", line 1917, in _cython_agg_general
    new_blocks = self._cython_agg_blocks(how, numeric_only=numeric_only)
  File "/usr/lib/python2.7/dist-packages/pandas/core/groupby.py", line 1964, in _cython_agg_blocks
    raise DataError('No numeric types to aggregate')
pandas.core.groupby.DataError: No numeric types to aggregate

附注：此问题几乎重复的是1，2和3。但是，他们没有为我的问题提供令人满意的答案。

我尝试使用fill_value和astype方法。他们没有运气。

编辑：
我试图通过添加以下内容来查找导致错误的原因（基于建议

pd.unique(df['C_number'].values)

并得到以下结果：

['163' '143' '51' '43' '34' '24' '20' '15' '14' '12' '11' '10' '9' '8' '7'
 '6' '5' '4' '3' '2' '1' '\xc2\xa0' '145' '35' '16' '164' '146' '36' '21'
 '165' '148' '37' '171' '154' '52' '44' '22' '17' '13' '158' '160' '147'
 '161']

因此，尽管反复在UTF-8中使用编码，但我相信“ \ xc2 \ xa0”是元凶。因此，我在函数generate_timeSeries()中添加了以下两行：

df.loc[df['Cited By Numbers']=='\xc2\xa0', 'Cited By Numbers' ] = '0'
df['Cited By Numbers'] = df['Cited By Numbers'].astype(int)

尽管对于具有'\xc2\xa0'的文件来说，这似乎是一个临时解决方案，但是对于不具有这些字符的文件，这似乎是一个问题，因为它会导致以下错误跟踪：

Traceback (most recent call last):
  File "imeSeries.py", line 66, in <module>
    main()
  File "TimeSeries.py", line 56, in main
    TimeSeries_dataframe = generate_timeSeries(unicoded_file)
  File "TimeSeries.py", line 23, in generate_timeSeries
    df.loc[df['C_Numbers']=='\xc2\xa0', 'C_Numbers' ] = '0'
  File "/usr/lib/python2.7/dist-packages/pandas/core/ops.py", line 563, in wrapper
    res = na_op(values, other)
  File "/usr/lib/python2.7/dist-packages/pandas/core/ops.py", line 532, in na_op
    raise TypeError("invalid type comparison")
TypeError: invalid type comparison

解决此问题的正确方法是什么？

任何帮助都感激不尽。

最佳答案

我设法通过将以下行添加到原始脚本中来解决此问题。

df = df.convert_objects(convert_numeric=True)

关于python - Python Pandas数据透视表如何处理'\xc2\xa0'？，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/33867408/

xA0

python - Python Pandas数据透视表如何处理'\xc2\xa0'？