blocks|key|237430|text|实际上，这可以很好地与filter配合使用|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|237431|import+csv
fp+=+open('samples.csv')
rdr+=+csv.DictReader(filter(lambda+row:+row[0]!='#',+fp))
for+row+in+rdr:
++++print(row)
fp.close()|code-block|syntax|javascript|237432|entityMap^0|B|6|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|P|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|Q|8|@]|D|@]|E|$]]]|L|$]]

Actually this works nicely with <code>filter</code>:

<pre><code>import csv
fp = open('samples.csv')
rdr = csv.DictReader(filter(lambda row: row[0]!='#', fp))
for row in rdr:
 print(row)
fp.close()
</code></pre>

blocks|key|4296120|text|问得好。Python的CSV库缺乏对注释的基本支持(在CSV文件的顶部并不少见)。虽然Dan+Stowell的解决方案适用于OP的特定情况，但它的局限性在于#必须作为第一个符号出现。更通用的解决方案是：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4296121|def+decomment(csvfile):
++++for+row+in+csvfile:
++++++++raw+=+row.split('#')[0].strip()
++++++++if+raw:+yield+raw

with+open('dummy.csv')+as+csvfile:
++++reader+=+csv.reader(decomment(csvfile))
++++for+row+in+reader:
++++++++print(row)|code-block|syntax|javascript|4296122|以下面的dummy.csv文件为例：|4296123|#+comment
+#+comment
a,b,c+#+comment
1,2,3
10,20,30
#+comment|4296124|返回|4296125|['a',+'b',+'c']
['1',+'2',+'3']
['10',+'20',+'30']|4296126|当然，这也适用于csv.DictReader()。|4296127|entityMap^0|26|1|0|0|4|9|0|0|0|0|8|G|0^^$0|@$1|2|3|4|5|6|7|W|8|@$9|X|A|Y|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|Z|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|10|8|@$9|11|A|12|B|C]]|D|@]|E|$]]|$1|M|3|N|5|H|7|13|8|@]|D|@]|E|$I|J]]|$1|O|3|P|5|6|7|14|8|@]|D|@]|E|$]]|$1|Q|3|R|5|H|7|15|8|@]|D|@]|E|$I|J]]|$1|S|3|T|5|6|7|16|8|@$9|17|A|18|B|C]]|D|@]|E|$]]|$1|U|3|-4|5|6|7|19|8|@]|D|@]|E|$]]]|V|$]]

Good question. Python's CSV library lacks basic support for comments (not uncommon at the top of CSV files). While Dan Stowell's solution works for the specific case of the OP, it is limited in that <code>#</code> must appear as the first symbol. A more generic solution would be:
<pre><code>def decomment(csvfile):
 for row in csvfile:
 raw = row.split('#')[0].strip()
 if raw: yield raw

with open('dummy.csv') as csvfile:
 reader = csv.reader(decomment(csvfile))
 for row in reader:
 print(row)
</code></pre>
As an example, the following <code>dummy.csv</code> file:
<pre><code># comment
 # comment
a,b,c # comment
1,2,3
10,20,30
# comment
</code></pre>
returns
<pre><code>['a', 'b', 'c']
['1', '2', '3']
['10', '20', '30']
</code></pre>
Of course, this works just as well with <code>csv.DictReader()</code>.

blocks|key|946629|text|读取CSV文件的另一种方法是使用pandas|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|946630|下面是一个示例代码：|946631|df+=+pd.read_csv('test.csv',
+++++++++++++++++sep=',',+++++#+field+separator
+++++++++++++++++comment='#',+#+comment
+++++++++++++++++index_col=0,+#+number+or+label+of+index+column
+++++++++++++++++skipinitialspace=True,
+++++++++++++++++skip_blank_lines=True,
+++++++++++++++++error_bad_lines=False,
+++++++++++++++++warn_bad_lines=True
+++++++++++++++++).sort_index()
print(df)
df.fillna('no+value',+inplace=True)+#+replace+NaN+with+'no+value'
print(df)|code-block|syntax|javascript|946632|对于此csv文件：|946633|a,b,c,d,e
1,,16,,55#,,65##77
8,77,77,,16#86,18#
#This+is+a+comment
13,19,25,28,82|946634|我们将得到以下输出：|946635|+++++++b+++c+++++d+++e
a+++++++++++++++++++++
1++++NaN++16+++NaN++55
8+++77.0++77+++NaN++16
13++19.0++25++28.0++82
+++++++++++b+++c+++++++++d+++e
a+++++++++++++++++++++++++++++
1+++no+value++16++no+value++55
8+++++++++77++77++no+value++16
13++++++++19++25++++++++28++82|946636|entityMap^0|G|6|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@$9|X|A|Y|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|Z|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|10|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|11|8|@]|D|@]|E|$]]|$1|O|3|P|5|J|7|12|8|@]|D|@]|E|$K|L]]|$1|Q|3|R|5|6|7|13|8|@]|D|@]|E|$]]|$1|S|3|T|5|J|7|14|8|@]|D|@]|E|$K|L]]|$1|U|3|-4|5|6|7|15|8|@]|D|@]|E|$]]]|V|$]]

Another way to read a CSV file is using <code>pandas</code>

Here's a sample code:

<pre><code>df = pd.read_csv('test.csv',
 sep=',', # field separator
 comment='#', # comment
 index_col=0, # number or label of index column
 skipinitialspace=True,
 skip_blank_lines=True,
 error_bad_lines=False,
 warn_bad_lines=True
 ).sort_index()
print(df)
df.fillna('no value', inplace=True) # replace NaN with 'no value'
print(df)
</code></pre>

For this csv file:

<pre><code>a,b,c,d,e
1,,16,,55#,,65##77
8,77,77,,16#86,18#
#This is a comment
13,19,25,28,82
</code></pre>

we will get this output:

<pre><code> b c d e
a 
1 NaN 16 NaN 55
8 77.0 77 NaN 16
13 19.0 25 28.0 82
 b c d e
a 
1 no value 16 no value 55
8 77 77 no value 16
13 19 25 28 82
</code></pre>

blocks|key|4778690|text|只是发布了@sigvaldm的解决方案中的错误修复。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4778691|def+decomment(csvfile):
for+row+in+csvfile:
++++raw+=+row.split('#')[0].strip()
++++if+raw:+yield+row

with+open('dummy.csv')+as+csvfile:
++++reader+=+csv.reader(decomment(csvfile))
++++for+row+in+reader:
++++++++print(row)|code-block|syntax|javascript|4778692|CSV行可以在带引号的字符串中包含"#“字符，并且完全有效。之前的解决方案是切断包含'#‘字符的字符串。|4778693|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|L|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|M|8|@]|9|@]|A|$]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

Just posting the bugfix from @sigvaldm's solution.

<pre><code>def decomment(csvfile):
for row in csvfile:
 raw = row.split('#')[0].strip()
 if raw: yield row

with open('dummy.csv') as csvfile:
 reader = csv.reader(decomment(csvfile))
 for row in reader:
 print(row)
</code></pre>

A CSV line can contain "#" characters in quoted strings and is perfectly valid. The previous solution was cutting off strings containing '#' characters.

Processing CSV files with <a href="http://docs.python.org/2/library/csv.html#csv.DictReader" rel="nofollow noreferrer">csv.DictReader</a> is great - but I have CSV files with comment lines (indicated by a hash at the start of a line), for example:
<pre class="lang-none prettyprint-override"><code># step size=1.61853
val0,val1,val2,hybridisation,temp,smattr
0.206895,0.797923,0.202077,0.631199,0.368801,0.311052,0.688948,0.597237,0.402763
-169.32,1,1.61853,2.04069e-92,1,0.000906546,0.999093,0.241356,0.758644,0.202382
# adaptation finished
</code></pre>
The csv module <a href="http://bugs.python.org/issue1225769" rel="nofollow noreferrer">doesn't include any way to skip such lines</a>.
I could easily do something hacky, but I imagine there's a nice way to wrap a <code>csv.DictReader</code> around some other iterator object, which preprocesses to discard the lines.

Python: skip comment lines marked with # in csv.DictReader

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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用处理CSV文件是很棒的--但是我的CSV文件有注释行(由行首的散列表示)，例如：# step size=1.61853val0,val1,val2,hybridisation,temp,smattr0.206895,0.797923,0.202077,0.631199,0.368801,0.311052,0.6889...

问Python:跳过csv.DictReader中标有#的注释行
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问Python:跳过csv.DictReader中标有#的注释行EN