pandas 类型错误：write() 中不支持类型 <type 'list'>
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TypeError: Unsupported type <type 'list'> in write()
提问by FaCoffee
I am trying to dump a bunch of dictsto an .xlsxfile by means of the following lines:
我试图通过以下几行将一堆转储dicts到.xlsx文件中：
H=0.5 #Used to name the xlsx file
fail_thre=0.2 #Used to name the xlsx file
dict_list=[dict1,dict2,dict3] #The list of dictionaries to be dumped
myindex=['event 1','event 2','event 3'] #Used to name rows
from itertools import izip_longest
stats_matrix=[ tuple('dict{}'.format(i+1) for i in range(len(dict_list))) ] + list( izip_longest(*([ v for k,v in sorted(d.items())] for d in dict_list)) )
import pandas as pd
column_names=['Dict1','Dict2','Dict3']
mydf=pd.DataFrame(stats_matrix,index=myindex,columns=column_names) #Creating a data frame for MS Excel visualization
mydf.columns = ['Dict1','Dict2','Dict3']
writer = pd.ExcelWriter('Lattice_stats_H_'+str(Hurst)+'FAIL_'+str(fail_thre)+'_FLOODING.xlsx', engine='xlsxwriter')
mydf.to_excel(writer, sheet_name='Lattice')
writer.save()
But I get this error (please note that the names in column_namesand mydf.columnsand etc. are the real names of my dicts, which are too long to be posted):
但是我得到这个错误（请注意，在名称column_names和mydf.columns等是我的类型的字典，这是太长发布者的真实名称）：
TypeError Traceback (most recent call last)
C:\Users\Francesco\Desktop\Scripts\Network_Scripts\Lattice_ForLoop_FLOODING.py in <module>()
399 mydf.columns = ['failed_nodes_1Stage','percent_failed_haz','act_nodes_1Stage','percent_active_haz','failed_nodes_2Stage','percent_failed_conn','failed_nodes_1plus2','percent_failed_1plus2','act_nodes_2Stage','percent_active_conn','total_failed_nodes','percent_total_failed_nodes','total_active_nodes','percent_total_active_nodes','giant_component','center_giant_comp','network_diam','connectedness','average_degree', 'graph_len']
400 writer = pd.ExcelWriter('Lattice_stats_H_'+str(Hurst)+'FAIL_'+str(fail_thre)+'_FLOODING.xlsx', engine='xlsxwriter')
--> 401 mydf.to_excel(writer, sheet_name='Lattice')
402 writer.save()
403
C:\Users\Francesco\AppData\Local\Enthought\Canopy32\User\lib\site-packages\pandas\core\frame.pyc in to_excel(self, excel_writer, sheet_name, na_rep, float_format, columns, header, index, index_label, startrow, startcol, engine, merge_cells, encoding, inf_rep)
1272 formatted_cells = formatter.get_formatted_cells()
1273 excel_writer.write_cells(formatted_cells, sheet_name,
-> 1274 startrow=startrow, startcol=startcol)
1275 if need_save:
1276 excel_writer.save()
C:\Users\Francesco\AppData\Local\Enthought\Canopy32\User\lib\site-packages\pandas\io\excel.pyc in write_cells(self, cells, sheet_name, startrow, startcol)
1337 wks.write(startrow + cell.row,
1338 startcol + cell.col,
-> 1339 cell.val, style)
1340
1341 def _convert_to_style(self, style_dict, num_format_str=None):
C:\Users\Francesco\AppData\Local\Enthought\Canopy32\User\lib\site-packages\xlsxwriter\worksheet.pyc in cell_wrapper(self, *args, **kwargs)
62 args = new_args
63
---> 64 return method(self, *args, **kwargs)
65
66 return cell_wrapper
C:\Users\Francesco\AppData\Local\Enthought\Canopy32\User\lib\site-packages\xlsxwriter\worksheet.pyc in write(self, row, col, *args)
429 pass
430 except TypeError:
--> 431 raise TypeError("Unsupported type %s in write()" % type(token))
432
433 # Finally try string.
TypeError: Unsupported type <type 'list'> in write()
What am I doing wrong?
我究竟做错了什么？
回答by davidshinn
Your mydfdataframe has elements of type listin the dataframe cells. It is likely due to how you built stats_matrix. See the the pandas docsfor the appropriate ways to call DataFrame. To find your problems, you could call mydf.applymap(type)and see where the lists reside in mydf.
您的mydf数据框list在数据框单元格中具有类型元素。这可能是由于您构建stats_matrix. 有关调用 DataFrame 的适当方法，请参阅pandas 文档。要找到您的问题，您可以致电mydf.applymap(type)并查看列表所在的位置mydf。
If you wanted to translate those list items into strings without the braces/brackets, you could use this function to convert the culprit column into a column that would work:
如果您想将这些列表项转换为没有大括号/方括号的字符串，您可以使用此函数将罪魁祸首列转换为可以工作的列：
def list_to_number_string(value):
if isinstance(value, (list, tuple)):
return str(value)[1:-1]
else:
return value
mydf[badcol] = mydf[badcol].apply(list_to_number_string)
