blocks|key|676718|text|numpy.savetxt将数组保存为文本文件。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|676719|import+numpy
a+=+numpy.asarray([+[1,2,3],+[4,5,6],+[7,8,9]+])
numpy.savetxt("foo.csv",+a,+delimiter=",")|code-block|syntax|javascript|676720|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.scipy.org/doc/numpy/reference/generated/numpy.savetxt.html^0|0|D|0|D|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@$9|T|A|U|B|C]]|D|@$9|V|A|W|1|X]]|E|$]]|$1|F|3|G|5|H|7|Y|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|Z|8|@]|D|@]|E|$]]]|L|$M|$5|N|O|P|E|$Q|R]]]]

<a href="http://docs.scipy.org/doc/numpy/reference/generated/numpy.savetxt.html" rel="noreferrer"><code>numpy.savetxt</code></a> saves an array to a text file.

<pre><code>import numpy
a = numpy.asarray([ [1,2,3], [4,5,6], [7,8,9] ])
numpy.savetxt("foo.csv", a, delimiter=",")
</code></pre>

blocks|key|676841|text|您可以使用pandas。它确实需要一些额外的内存，所以它并不总是可行的，但它非常快速且易于使用。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|676842|import+pandas+as+pd+
pd.DataFrame(np_array).to_csv("path/to/file.csv")|code-block|syntax|javascript|676843|如果不需要标头或索引，请使用to_csv("/path/to/file.csv",+header=None,+index=None)|676844|entityMap^0|5|6|0|0|E|1G|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|S|8|@$9|T|A|U|B|C]]|D|@]|E|$]]|$1|M|3|-4|5|6|7|V|8|@]|D|@]|E|$]]]|N|$]]

You can use <code>pandas</code>. It does take some extra memory so it's not always possible, but it's very fast and easy to use.

<pre><code>import pandas as pd 
pd.DataFrame(np_array).to_csv("path/to/file.csv")
</code></pre>

if you don't want a header or index, use <code>to_csv("/path/to/file.csv", header=None, index=None)</code>

blocks|key|893455|text|将记录数组写为带有头文件的CSV文件需要更多的工作。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|893456|此示例读取CSV文件(example.csv)并将其内容写入另一个CSV文件(out.csv)。|offset|length|style|CODE|893457|import+numpy+as+np

#+Write+an+example+CSV+file+with+headers+on+first+line
with+open('example.csv',+'w')+as+fp:
++++fp.write('''\
col1,col2,col3
1,100.1,string1
2,222.2,second+string
''')

#+Read+it+as+a+Numpy+record+array
ar+=+np.recfromcsv('example.csv',+encoding='ascii')
print(repr(ar))
#+rec.array([(1,+100.1,+'string1'),+(2,+222.2,+'second+string')],+
#+++++++++++dtype=[('col1',+'<i8'),+('col2',+'<f8'),+('col3',+'<U13')])

#+Write+as+a+CSV+file+with+headers+on+first+line
with+open('out.csv',+'w')+as+fp:
++++fp.write(','.join(ar.dtype.names)+%2B+'\n')
++++np.savetxt(fp,+ar,+'%25s',+',')|code-block|syntax|javascript|893458|请注意，上面的示例不能处理带逗号的字符串。要始终用引号将非数字值括起来，请使用csv内置模块：|893459|import+csv

with+open('out2.csv',+'w',+newline='')+as+fp:
++++writer+=+csv.writer(fp,+quoting=csv.QUOTE_NONNUMERIC)
++++writer.writerow(ar.dtype.names)
++++writer.writerows(ar.tolist())|893460|entityMap|0|LINK|mutability|MUTABLE|url|https://docs.python.org/3/library/csv.html^0|0|B|B|13|7|0|0|13|3|13|3|0|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|Z|8|@$D|10|E|11|F|G]|$D|12|E|13|F|G]]|9|@]|A|$]]|$1|H|3|I|5|J|7|14|8|@]|9|@]|A|$K|L]]|$1|M|3|N|5|6|7|15|8|@$D|16|E|17|F|G]]|9|@$D|18|E|19|1|1A]]|A|$]]|$1|O|3|P|5|J|7|1B|8|@]|9|@]|A|$K|L]]|$1|Q|3|-4|5|6|7|1C|8|@]|9|@]|A|$]]]|R|$S|$5|T|U|V|A|$W|X]]]]

Writing record arrays as CSV files with headers requires a bit more work.
This example reads from a CSV file (<code>example.csv</code>) and writes its contents to another CSV file (<code>out.csv</code>).
<pre><code>import numpy as np

# Write an example CSV file with headers on first line
with open('example.csv', 'w') as fp:
 fp.write('''\
col1,col2,col3
1,100.1,string1
2,222.2,second string
''')

# Read it as a Numpy record array
ar = np.recfromcsv('example.csv', encoding='ascii')
print(repr(ar))
# rec.array([(1, 100.1, 'string1'), (2, 222.2, 'second string')], 
# dtype=[('col1', '&lt;i8'), ('col2', '&lt;f8'), ('col3', '&lt;U13')])

# Write as a CSV file with headers on first line
with open('out.csv', 'w') as fp:
 fp.write(','.join(ar.dtype.names) + '\n')
 np.savetxt(fp, ar, '%s', ',')
</code></pre>
Note that the above example cannot handle values which are strings with commas. To always enclose non-numeric values within quotes, use the <a href="https://docs.python.org/3/library/csv.html" rel="nofollow noreferrer"><code>csv</code></a> built-in module:
<pre><code>import csv

with open('out2.csv', 'w', newline='') as fp:
 writer = csv.writer(fp, quoting=csv.QUOTE_NONNUMERIC)
 writer.writerow(ar.dtype.names)
 writer.writerows(ar.tolist())
</code></pre>

blocks|key|676950|text|如前所述，将数组转储到CSV文件的最佳方法是使用.savetxt(...)方法。然而，有一些事情我们应该知道才能正确地做到这一点。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|676951|例如，如果您有一个dtype+=+np.int32为的numpy数组|676952|+++narr+=+np.array([[1,2],
+++++++++++++++++[3,4],
+++++++++++++++++[5,6]],+dtype=np.int32)|code-block|syntax|javascript|676953|并希望使用savetxt另存为|676954|np.savetxt('values.csv',+narr,+delimiter=",")|676955|它将以浮点指数格式将数据存储为|676956|1.000000000000000000e%2B00,2.000000000000000000e%2B00
3.000000000000000000e%2B00,4.000000000000000000e%2B00
5.000000000000000000e%2B00,6.000000000000000000e%2B00|676957|必须使用名为fmt的参数更改格式，如下所示|676958|np.savetxt('values.csv',+narr,+fmt="%25d",+delimiter=",")|676959|以原始格式存储数据|676960|以压缩的gz格式保存数据|676961|此外，savetxt还可用于以.gz压缩格式存储数据，这在通过网络传输数据时可能很有用。|676962|我们只需要更改文件的扩展名，因为.gz和numpy会自动处理所有事情|676963|np.savetxt('values.gz',+narr,+fmt="%25d",+delimiter=",")|676964|希望能有所帮助|676965|entityMap^0|O|D|0|9|G|0|0|5|7|0|0|0|0|6|3|0|0|0|0|3|7|F|3|0|G|3|0|0|0^^$0|@$1|2|3|4|5|6|7|1C|8|@$9|1D|A|1E|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1F|8|@$9|1G|A|1H|B|C]]|D|@]|E|$]]|$1|H|3|I|5|J|7|1I|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|1J|8|@$9|1K|A|1L|B|C]]|D|@]|E|$]]|$1|O|3|P|5|J|7|1M|8|@]|D|@]|E|$K|L]]|$1|Q|3|R|5|6|7|1N|8|@]|D|@]|E|$]]|$1|S|3|T|5|J|7|1O|8|@]|D|@]|E|$K|L]]|$1|U|3|V|5|6|7|1P|8|@$9|1Q|A|1R|B|C]]|D|@]|E|$]]|$1|W|3|X|5|J|7|1S|8|@]|D|@]|E|$K|L]]|$1|Y|3|Z|5|6|7|1T|8|@]|D|@]|E|$]]|$1|10|3|11|5|6|7|1U|8|@]|D|@]|E|$]]|$1|12|3|13|5|6|7|1V|8|@$9|1W|A|1X|B|C]|$9|1Y|A|1Z|B|C]]|D|@]|E|$]]|$1|14|3|15|5|6|7|20|8|@$9|21|A|22|B|C]]|D|@]|E|$]]|$1|16|3|17|5|J|7|23|8|@]|D|@]|E|$K|L]]|$1|18|3|19|5|6|7|24|8|@]|D|@]|E|$]]|$1|1A|3|-4|5|6|7|25|8|@]|D|@]|E|$]]]|1B|$]]

As already discussed, the best way to dump the array into a CSV file is by using <code>.savetxt(...)</code>method. However, there are certain things we should know to do it properly. 

For example, if you have a numpy array with <code>dtype = np.int32</code> as

<pre><code> narr = np.array([[1,2],
 [3,4],
 [5,6]], dtype=np.int32)
</code></pre>

and want to save using <code>savetxt</code> as

<pre><code>np.savetxt('values.csv', narr, delimiter=",")
</code></pre>

It will store the data in floating point exponential format as

<pre><code>1.000000000000000000e+00,2.000000000000000000e+00
3.000000000000000000e+00,4.000000000000000000e+00
5.000000000000000000e+00,6.000000000000000000e+00
</code></pre>

You will have to change the formatting by using a parameter called <code>fmt</code> as

<pre><code>np.savetxt('values.csv', narr, fmt="%d", delimiter=",")
</code></pre>

to store data in its original format

<h2>Saving Data in Compressed gz format</h2>

Also, <code>savetxt</code> can be used for storing data in <code>.gz</code> compressed format which might be useful while transferring data over network. 

We just need to change the extension of the file as <code>.gz</code> and numpy will take care of everything automatically

<pre><code>np.savetxt('values.gz', narr, fmt="%d", delimiter=",")
</code></pre>

Hope it helps

blocks|key|893661|text|在Python中，我们使用csv.writer()模块将数据写入csv文件。此模块类似于csv.reader()模块。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|893662|import+csv

person+=+[['SN',+'Person',+'DOB'],
['1',+'John',+'18/1/1997'],
['2',+'Marie','19/2/1998'],
['3',+'Simon','20/3/1999'],
['4',+'Erik',+'21/4/2000'],
['5',+'Ana',+'22/5/2001']]

csv.register_dialect('myDialect',
delimiter+=+'%7C',
quoting=csv.QUOTE_NONE,
skipinitialspace=True)

with+open('dob.csv',+'w')+as+f:
++++writer+=+csv.writer(f,+dialect='myDialect')
++++for+row+in+person:
+++++++writer.writerow(row)

f.close()|code-block|syntax|javascript|893663|分隔符是用于分隔字段的字符串。默认值为逗号(，)。|893664|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|$]]

In Python we use csv.writer() module to write data into csv files. This module is similar to the csv.reader() module.

<pre><code>import csv

person = [['SN', 'Person', 'DOB'],
['1', 'John', '18/1/1997'],
['2', 'Marie','19/2/1998'],
['3', 'Simon','20/3/1999'],
['4', 'Erik', '21/4/2000'],
['5', 'Ana', '22/5/2001']]

csv.register_dialect('myDialect',
delimiter = '|',
quoting=csv.QUOTE_NONE,
skipinitialspace=True)

with open('dob.csv', 'w') as f:
 writer = csv.writer(f, dialect='myDialect')
 for row in person:
 writer.writerow(row)

f.close()
</code></pre>

A delimiter is a string used to separate fields. The default value is comma(,).

blocks|key|676757|text|如果你想把你的numpy数组(例如your_array+=+np.array([[1,2],[3,4]]))保存到一个单元格，你可以先用your_array.tolist()转换它。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|676758|然后以正常的方式将其保存到一个单元格，使用delimiter=';'，csv文件中的单元格将如下所示：[[1,+2],+[2,+4]]|676759|然后你可以像这样恢复你的数组：your_array+=+np.array(ast.literal_eval(cell_string))|676760|entityMap^0|H|10|1W|J|0|L|D|1F|G|0|F|1G|0^^$0|@$1|2|3|4|5|6|7|L|8|@$9|M|A|N|B|C]|$9|O|A|P|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|Q|8|@$9|R|A|S|B|C]|$9|T|A|U|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|V|8|@$9|W|A|X|B|C]]|D|@]|E|$]]|$1|J|3|-4|5|6|7|Y|8|@]|D|@]|E|$]]]|K|$]]

If you want to save your numpy array (e.g. <code>your_array = np.array([[1,2],[3,4]])</code>) to one cell, you could convert it first with <code>your_array.tolist()</code>.

Then save it the normal way to one cell, with <code>delimiter=';'</code>
and the cell in the csv-file will look like this <code>[[1, 2], [2, 4]]</code>

Then you could restore your array like this:
<code>your_array = np.array(ast.literal_eval(cell_string))</code>

blocks|key|676883|text|您也可以使用纯python而不使用任何模块来完成此任务。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|676884|#+format+as+a+block+of+csv+text+to+do+whatever+you+want
csv_rows+=+["{},{}".format(i,+j)+for+i,+j+in+array]
csv_text+=+"\n".join(csv_rows)

#+write+it+to+a+file
with+open('file.csv',+'w')+as+f:
++++f.write(csv_text)|code-block|syntax|javascript|676885|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|$]]

You can also do it with pure python without using any modules.

<pre><code># format as a block of csv text to do whatever you want
csv_rows = ["{},{}".format(i, j) for i, j in array]
csv_text = "\n".join(csv_rows)

# write it to a file
with open('file.csv', 'w') as f:
 f.write(csv_text)
</code></pre>

Is there a way to dump a NumPy array into a CSV file? I have a 2D NumPy array and need to dump it in human-readable format.

Dump a NumPy array into a csv file

数据存储

Python

有没有办法将NumPy数组转储到CSV文件中？我有一个2D NumPy数组，需要将其转储为人类可读的格式。

问将NumPy阵列转储到csv文件中
EN

回答 7

Stack Overflow用户

Stack Overflow用户

Stack Overflow用户

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问将NumPy阵列转储到csv文件中EN

回答 7

Stack Overflow用户

Stack Overflow用户

Stack Overflow用户

社区

活动

资源

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问将NumPy阵列转储到csv文件中
EN