pandas to_csv output quoting issue

I'm having trouble getting the pandas dataframe.to_csv(...) output quoting strings right.

import pandas as pd


text = 'this is "out text"'
df = pd.DataFrame(index=['1'],columns=['1','2'])
df.loc['1','1']=123
df.loc['1','2']=text
df.to_csv('foo.txt',index=False,header=False)

The output is:

123,"this is ""out text"""

But I would like:

123,this is "out text"

Does anyone know how to get this right?

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最佳答案

You could pass quoting=csv.QUOTE_NONE, for example:

>>> df.to_csv('foo.txt',index=False,header=False)
>>> !cat foo.txt
123,"this is ""out text"""
>>> import csv
>>> df.to_csv('foo.txt',index=False,header=False, quoting=csv.QUOTE_NONE)
>>> !cat foo.txt
123,this is "out text"

but in my experience it's better to quote more, rather than less.

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Note: there is currently a small error in the Pandas to_string documentation. It says:

  • quoting : int, Controls whether quotes should be recognized. Values are taken from csv.QUOTE_* values. Acceptable values are 0, 1, 2, and 3 for QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONE, and QUOTE_NONNUMERIC,
    respectively.

But this reverses how csv defines the QUOTE_NONE and QUOTE_NONNUMERIC variables.

In [13]: import csv
In [14]: csv.QUOTE_NONE
Out[14]: 3
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To use quoting=csv.QUOTE_NONE, you need to set the escapechar, e.g. 

# Create a tab-separated file with quotes
$ echo abc$'\t'defg$'\t'$'"xyz"' > in.tsv
$ cat in.tsv
abc defg    "xyz"


# Gotcha the quotes disappears in `"..."`
$ python3
>>> import pandas as pd
>>> import csv
>>> df = pd.read("in.tsv", sep="\t")
>>> df = pd.read_csv("in.tsv", sep="\t")
>>> df
Empty DataFrame
Columns: [abc, defg, xyz]
Index: []




# When reading in pandas, to read the `"..."` quotes,
# you have to explicitly say there's no `quotechar`
>>> df = pd.read_csv("in.tsv", sep="\t", quotechar='\0')
>>> df
Empty DataFrame
Columns: [abc, defg, "xyz"]
Index: []


# To print out without the quotes.
>> df.to_csv("out.tsv", , sep="\t", quoting=csv.QUOTE_NONE, quotechar="",  escapechar="\\")
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To use without escapechar:

Replace comma char , (Unicode:U+002C) in your df with an single low-9 quotation mark character ‚ (Unicode: U+201A)

After this, you can simply use:

import csv df.to_csv('foo.txt', index=False, header=False, quoting=csv.QUOTE_NONE)

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If you don't want to bother with importing csv, you simply can use the following line

df.to_csv('foo.txt', index=False, header=False, quoting=3,sep=",",escapechar=",")


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