我在Mac上使用Pandas来读写CSV文件,奇怪的是当使用完整路径时,它有错误,当只使用一个文件名时,它可以工作。我在下面的评论中发布了我的代码,哪些有效,哪些不起作用,还有详细的错误消息。有什么好主意吗?在
sourceDf = pd.read_csv(path_to_csv)
sourceDf['nameFull'] = sourceDf['nameFirst'] + ' ' + sourceDf['nameLast']
sourceDf.to_csv('newMaster.csv') # working
sourceDf.to_csv('~/Downloads/newMaster.csv') # not working
Traceback (most recent call last):
File "/Users/foo/PycharmProjects/DataWranglingTest/CSVTest1.py", line 36, in <module>
add_full_name(path_to_csv, path_to_new_csv)
File "/Users/foo/PycharmProjects/DataWranglingTest/CSVTest1.py", line 28, in add_full_name
sourceDf.to_csv('~/Downloads/newMaster.csv')
File "/usr/local/Cellar/python/2.7.8/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/frame.py", line 1189, in to_csv
formatter.save()
File "/usr/local/Cellar/python/2.7.8/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/format.py", line 1442, in save
encoding=self.encoding)
File "/usr/local/Cellar/python/2.7.8/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/common.py", line 2831, in _get_handle
f = open(path, mode)
IOError: [Errno 2] No such file or directory: '~/Downloads/newMaster.csv'
Tried to use prefix r, but not working,
path_to_csv = r'~/Downloads/Master.csv'
path_to_new_csv = r'~/Downloads/Master_new.csv'
File "/usr/local/Cellar/python/2.7.8/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/frame.py", line 1189, in to_csv
formatter.save()
File "/usr/local/Cellar/python/2.7.8/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/format.py", line 1442, in save
encoding=self.encoding)
File "/usr/local/Cellar/python/2.7.8/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/core/common.py", line 2831, in _get_handle
f = open(path, mode)
IOError: [Errno 2] No such file or directory: '~/Downloads/Master_new.csv'
提前谢谢你, 林
您没有指定python版本。 在3.4中,可以使用pathlib,否则使用
os.path.join()
或引用:注意r。 问题是/n是newline,这在路径中是不允许的。在
尝试使用
os.path.join()
。在使用相同的方法将
pandas.read_csv()
指向正确的方向。在相关问题 更多 >
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