我使用以下代码循环浏览文本文件并对其进行一些更改,然后将它们保存到新文件夹中。由于某种原因,代码在我的txt文件列表中间停止运行。我有54个文件,在返回此错误之前,只有30个文件使用此代码进行操作:
IOError: Initializing from file failed
我使用的代码是:
import pandas as pd
import os
d={'Band 1$': '1984137',
'Band 2$': '1984185',
'Band 3$': '1984249',
'Band 4$': '1985139',
'Band 5$': '1985171',
'Band 6$': '1986206',
'Band 7$': '1986238',
'Band 8$': '1987241',
'Band 9$': '1987257',
'Band 10$': '1987273',
'Band 11$': '1988212'}
pth = r'D:\Sheyenne\Statistics\NDVI_allotment\Text' # path to files
new = os.path.join(pth,"new")
os.mkdir(new) # create new dir for new files
# loop over each file and update
for f in os.listdir(pth):
if not os.path.isfile(os.path.join(pth,f)):
df = pd.read_csv(os.path.join(pth, f), sep='\t', nrows=80, skiprows=2)
#replace string names
df=df.replace(d)
#sort data
df.sort(columns='Basic Stats', axis=0, ascending=True, inplace=True)
#save data to csv
df.to_csv(os.path.join(new, "new_{}".format(f)), index=False, sep="\t")
print 'Done Processing'
其中一个文本文件的前1000个字符的示例是:
'Filename: F:\\Sheyenne\\Atmospherically Corrected Landsat\\Indices\\Main\\NDVI\\NDVI_stack\nROI: EVF: Layer: Main_allotments.shp (allotment1=A. Annex) [White] 3984 points\n\nBasic Stats\t Min\t Max\t Mean\t Stdev\t Num\tEigenvalue\n Band 1\t 0.428944\t0.843916\t0.689923\t0.052534\t 1\t 0.229509\n Band 2\t-0.000000\t0.689320\t0.513170\t0.048885\t 2\t 0.119217\n Band 3\t 0.336438\t0.743478\t0.592622\t0.052544\t 3\t 0.059111\n Band 4\t 0.313259\t0.678561\t0.525667\t0.048047\t 4\t 0.051338\n Band 5\t 0.374522\t0.746828\t0.583513\t0.055989\t 5\t 0.027913\n Band 6\t-0.000000\t0.749325\t0.330068\t0.314351\t 6\t 0.022561\n Band 7\t-0.000000\t0.819288\t0.600136\t0.170060\t 7\t 0.018126\n Band 8\t-0.000000\t0.687823\t0.450559\t0.084678\t 8\t 0.012942\n Band 9\t 0.332637\t0.776398\t0.549870\t0.085212\t 9\t 0.009261\n Band 10\t 0.386589\t0.848977\t0.635024\t0.087712\t 10\t 0.006628\n Band 11\t 0.265165\t0.822361\t0.594286\t0.075730\t 11\t 0.004517\n Band 12\t 0.191882\t0.539559\t0.343836\t0.0'
编辑:
返回的完整错误是:
runfile('F:/docs/ESSP 502/Final Project/Codes/try2.py', wdir='F:/docs/ESSP 502/Final Project/Codes')
Traceback (most recent call last):
File "<ipython-input-7-95e6eea0c3e4>", line 1, in <module>
runfile('F:/docs/ESSP 502/Final Project/Codes/try2.py', wdir='F:/docs/ESSP 502/Final Project/Codes')
File "C:\Users\spotter\AppData\Local\Continuum\Anaconda\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 685, in runfile
execfile(filename, namespace)
File "C:\Users\spotter\AppData\Local\Continuum\Anaconda\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 71, in execfile
exec(compile(scripttext, filename, 'exec'), glob, loc)
File "F:/docs/ESSP 502/Final Project/Codes/try2.py", line 18, in <module>
df = pd.read_csv(os.path.join(pth, f), sep='\t', nrows=80, skiprows=2)
File "C:\Users\spotter\AppData\Local\Continuum\Anaconda\lib\site-packages\pandas\io\parsers.py", line 474, in parser_f
return _read(filepath_or_buffer, kwds)
File "C:\Users\spotter\AppData\Local\Continuum\Anaconda\lib\site-packages\pandas\io\parsers.py", line 250, in _read
parser = TextFileReader(filepath_or_buffer, **kwds)
File "C:\Users\spotter\AppData\Local\Continuum\Anaconda\lib\site-packages\pandas\io\parsers.py", line 566, in __init__
self._make_engine(self.engine)
File "C:\Users\spotter\AppData\Local\Continuum\Anaconda\lib\site-packages\pandas\io\parsers.py", line 705, in _make_engine
self._engine = CParserWrapper(self.f, **self.options)
File "C:\Users\spotter\AppData\Local\Continuum\Anaconda\lib\site-packages\pandas\io\parsers.py", line 1072, in __init__
self._reader = _parser.TextReader(src, **kwds)
File "pandas\parser.pyx", line 350, in pandas.parser.TextReader.__cinit__ (pandas\parser.c:3173)
File "pandas\parser.pyx", line 595, in pandas.parser.TextReader._setup_parser_source (pandas\parser.c:5926)
IOError: Initializing from file failed
答案 0 :(得分:1)
错误可能是由于在处理中包含输出目录并尝试将其作为csv处理。只需通过编辑for循环省略目录以包含检查以确保目录条目实际上是文件:
for f in os.listdir(pth):
if not os.path.isfile(os.path.join(pth,f)):
continue
df = pd.read_csv(os.path.join(pth, f), sep='\t', nrows=80, skiprows=2)
# ...