blocks|key|192981|text|您可以使用pandas|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|192982|In+[1]:+import+pandas+as+pd

In+[2]:+a+=+[[1.2,'abc',3],[1.2,'werew',4],[1.4,'qew',2]]

In+[3]:+my_df+=+pd.DataFrame(a)

In+[4]:+my_df.to_csv('my_csv.csv',+index=False,+header=False)|code-block|syntax|javascript|192983|entityMap^0|5|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|$]]

You could use <code>pandas</code>:

<pre><code>In [1]: import pandas as pd

In [2]: a = [[1.2,'abc',3],[1.2,'werew',4],[1.4,'qew',2]]

In [3]: my_df = pd.DataFrame(a)

In [4]: my_df.to_csv('my_csv.csv', index=False, header=False)
</code></pre>

blocks|key|192904|text|import+csv
with+open(file_path,+'a')+as+outcsv:+++
++++#configure+writer+to+write+standard+csv+file
++++writer+=+csv.writer(outcsv,+delimiter=',',+quotechar='%7C',+quoting=csv.QUOTE_MINIMAL,+lineterminator='\n')
++++writer.writerow(['number',+'text',+'number'])
++++for+item+in+list:
++++++++#Write+item+to+outcsv
++++++++writer.writerow([item[0],+item[1],+item[2]])|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|192905|官方文档：http://docs.python.org/2/library/csv.html|unstyled|offset|length|192906|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.python.org/2/library/csv.html^0|0|5|15|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$B|C]]|$1|D|3|E|5|F|7|R|8|@]|9|@$G|S|H|T|1|U]]|A|$]]|$1|I|3|-4|5|F|7|V|8|@]|9|@]|A|$]]]|J|$K|$5|L|M|N|A|$O|P]]]]

<pre><code>import csv
with open(file_path, 'a') as outcsv: 
 #configure writer to write standard csv file
 writer = csv.writer(outcsv, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL, lineterminator='\n')
 writer.writerow(['number', 'text', 'number'])
 for item in list:
 #Write item to outcsv
 writer.writerow([item[0], item[1], item[2]])
</code></pre>

official docs: <a href="http://docs.python.org/2/library/csv.html" rel="noreferrer">http://docs.python.org/2/library/csv.html</a>

blocks|key|193124|text|在我非常大的列表中使用csv.writer需要相当长的时间。我决定使用熊猫，它更快，更容易控制和理解：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|193125|+import+pandas

+yourlist+=+[[...],...,[...]]
+pd+=+pandas.DataFrame(yourlist)
+pd.to_csv("mylist.csv")|code-block|syntax|javascript|193126|好的部分是你可以改变一些东西来制作一个更好的csv文件：|193127|+yourlist+=+[[...],...,[...]]
+columns+=+["abcd","bcde","cdef"]+#a+csv+with+3+columns
+index+=+[i[0]+for+i+in+yourlist]+#first+element+of+every+list+in+yourlist
+not_index_list+=+[i[1:]+for+i+in+yourlist]
+pd+=+pandas.DataFrame(not_index_list,+columns+=+columns,+index+=+index)

+#Now+you+have+a+csv+with+columns+and+index:
+pd.to_csv("mylist.csv")|193128|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|N|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|O|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|K|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|L|$]]

Using csv.writer in my very large list took quite a time. I decided to use pandas, it was faster and more easy to control and understand:

<pre><code> import pandas

 yourlist = [[...],...,[...]]
 pd = pandas.DataFrame(yourlist)
 pd.to_csv("mylist.csv")
</code></pre>

The good part you can change somethings to make a better csv file:

<pre><code> yourlist = [[...],...,[...]]
 columns = ["abcd","bcde","cdef"] #a csv with 3 columns
 index = [i[0] for i in yourlist] #first element of every list in yourlist
 not_index_list = [i[1:] for i in yourlist]
 pd = pandas.DataFrame(not_index_list, columns = columns, index = index)

 #Now you have a csv with columns and index:
 pd.to_csv("mylist.csv")
</code></pre>

blocks|key|411188|text|如果出于某种原因想要手动完成(不使用csv、pandas、numpy等模块)：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|411189|with+open('myfile.csv','w')+as+f:
++++for+sublist+in+mylist:
++++++++for+item+in+sublist:
++++++++++++f.write(item+%2B+',')
++++++++f.write('\n')|code-block|syntax|javascript|411190|当然，滚动自己的版本很容易出错，效率也很低……这就是为什么会有这样一个模块的原因。但有时编写自己的代码可以帮助您理解它们是如何工作的，有时它只是更简单。|411191|entityMap^0|I|3|M|6|T|5|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]|$9|R|A|S|B|C]|$9|T|A|U|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|V|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|W|8|@]|D|@]|E|$]]|$1|M|3|-4|5|6|7|X|8|@]|D|@]|E|$]]]|N|$]]

If for whatever reason you wanted to do it manually (without using a module like <code>csv</code>,<code>pandas</code>,<code>numpy</code> etc.):

<pre><code>with open('myfile.csv','w') as f:
 for sublist in mylist:
 for item in sublist:
 f.write(item + ',')
 f.write('\n')
</code></pre>

Of course, rolling your own version can be error-prone and inefficient ... that's usually why there's a module for that. But sometimes writing your own can help you understand how they work, and sometimes it's just easier.

blocks|key|411285|text|如果您不想为此导入csv模块，则可以仅使用Python内置功能将列表列表写入csv文件|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|411286|with+open("output.csv",+"w")+as+f:
++++for+row+in+a:
++++++++f.write("%25s\n"+%25+','.join(str(col)+for+col+in+row))|code-block|syntax|javascript|411287|entityMap^0|9|3|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|$]]

If you don't want to import <code>csv</code> module for that, you can write a list of lists to a csv file using only Python built-ins

<pre><code>with open("output.csv", "w") as f:
 for row in a:
 f.write("%s\n" % ','.join(str(col) for col in row))
</code></pre>

blocks|key|411105|text|Ambers的解决方案也适用于numpy数组：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|411106|from+pylab+import+*
import+csv

array_=arange(0,10,1)
list_=[array_,array_*2,array_*3]
with+open("output.csv",+"wb")+as+f:
++++writer+=+csv.writer(f)
++++writer.writerows(list_)|code-block|syntax|javascript|411107|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Ambers's solution also works well for numpy arrays:

<pre><code>from pylab import *
import csv

array_=arange(0,10,1)
list_=[array_,array_*2,array_*3]
with open("output.csv", "wb") as f:
 writer = csv.writer(f)
 writer.writerows(list_)
</code></pre>

blocks|key|193150|text|如何将列表列表转储到pickle中并使用pickle+module恢复它？这很方便。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|193151|>>>+import+pickle
>>>+
>>>+mylist+=+[1,+'foo',+'bar',+{1,+2,+3},+[+[1,4,2,6],+[3,6,0,10]]]
>>>+with+open('mylist',+'wb')+as+f:
...+++++pickle.dump(mylist,+f)+


>>>+with+open('mylist',+'rb')+as+f:
...++++++mylist+=+pickle.load(f)
>>>+mylist
[1,+'foo',+'bar',+{1,+2,+3},+[[1,+4,+2,+6],+[3,+6,+0,+10]]]
>>>+|code-block|syntax|javascript|193152|entityMap|0|LINK|mutability|MUTABLE|url|https://www.quora.com/How-do-you-save-and-restore-lists-in-Python^0|K|D|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@$A|R|B|S|1|T]]|C|$]]|$1|D|3|E|5|F|7|U|8|@]|9|@]|C|$G|H]]|$1|I|3|-4|5|6|7|V|8|@]|9|@]|C|$]]]|J|$K|$5|L|M|N|C|$O|P]]]]

How about dumping the list of list into pickle and restoring it with <a href="https://www.quora.com/How-do-you-save-and-restore-lists-in-Python" rel="noreferrer">pickle module</a>? It's quite convenient. 

<pre><code>&gt;&gt;&gt; import pickle
&gt;&gt;&gt; 
&gt;&gt;&gt; mylist = [1, 'foo', 'bar', {1, 2, 3}, [ [1,4,2,6], [3,6,0,10]]]
&gt;&gt;&gt; with open('mylist', 'wb') as f:
... pickle.dump(mylist, f) 


&gt;&gt;&gt; with open('mylist', 'rb') as f:
... mylist = pickle.load(f)
&gt;&gt;&gt; mylist
[1, 'foo', 'bar', {1, 2, 3}, [[1, 4, 2, 6], [3, 6, 0, 10]]]
&gt;&gt;&gt; 
</code></pre>

blocks|key|411225|text|确保在创建编写器时指示lineterinator='\n'；否则，当数据源来自其他csv文件时，可能会在每个数据行之后向文件中写入额外的空行...|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|411226|以下是我的解决方案：|411227|with+open('csvfile',+'a')+as+csvfile:
++++spamwriter+=+csv.writer(csvfile,+delimiter='++++',quotechar='%7C',+quoting=csv.QUOTE_MINIMAL,+lineterminator='\n')
for+i+in+range(0,+len(data)):
++++spamwriter.writerow(data[i])|code-block|syntax|javascript|411228|entityMap^0|B|I|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|R|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|S|8|@]|D|@]|E|$K|L]]|$1|M|3|-4|5|6|7|T|8|@]|D|@]|E|$]]]|N|$]]

Make sure to indicate <code>lineterinator='\n'</code> when create the writer; otherwise, an extra empty line might be written into file after each data line when data sources are from other csv file...

Here is my solution:

<pre><code>with open('csvfile', 'a') as csvfile:
 spamwriter = csv.writer(csvfile, delimiter=' ',quotechar='|', quoting=csv.QUOTE_MINIMAL, lineterminator='\n')
for i in range(0, len(data)):
 spamwriter.writerow(data[i])
</code></pre>

blocks|key|193177|text|我在这个页面上甚至没有看到一个答案，其中包括如何包含头文件以及创建文件。这里也有一个结合了这一点的方法。方法在python+3中工作得很好。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|193178|csv_filename+=+'abc.csv'
fieldnames+=+['Col_1','Col_2','Col_3','Col_4']
with+open(csv_filename,+mode='w')+as+csv_file:
++++writer+=+csv.DictWriter(csv_file,+fieldnames=fieldnames)
++++writer.writeheader()
++++for+i+in+my_list:
++++++++writer.writerow({fieldnames[0]:+i[0],+fieldnames[1]:+i[1],+fieldnames[2]:+i[2],fieldnames[3]:+i[3]})+|code-block|syntax|javascript|193179|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Didn't see even a single answer on this page that includes how to include header as well to create the file. Here is a method incorporating that as well. Method works great with python 3
<pre><code>csv_filename = 'abc.csv'
fieldnames = ['Col_1','Col_2','Col_3','Col_4']
with open(csv_filename, mode='w') as csv_file:
 writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
 writer.writeheader()
 for i in my_list:
 writer.writerow({fieldnames[0]: i[0], fieldnames[1]: i[1], fieldnames[2]: i[2],fieldnames[3]: i[3]}) 
</code></pre>

I have a long list of lists of the following form ---

<pre><code>a = [[1.2,'abc',3],[1.2,'werew',4],........,[1.4,'qew',2]]
</code></pre>

i.e. the values in the list are of different types -- float,int, strings.How do I write it into a csv file so that my output csv file looks like

<pre><code>1.2,abc,3
1.2,werew,4
.
.
.
1.4,qew,2
</code></pre>

Writing a Python list of lists to a csv file

Python

我有一个长长的列表，列表如下a = [[1.2,'abc',3],[1.2,'werew',4],........,[1.4,'qew',2]]例如，列表中的值具有不同的类型-- float、int、strings.How。我是否将其写入csv文件，以便我的输出csv文件如下所示1.2,abc,31.2,werew,4...1.4,qew,2

问将Python列表列表写入csv文件
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回答 9

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