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How to output chinese characters in Python?

The column ['douban_info'] in my dataset is info about movies in Chinese which stored in JSON, so when I do df['douban_info'][0] , it returns:

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The Chinese characters are all changed into things like \破\晓\者 , which I can't read with ease. Is it possible to make Python to turn them into the original Chinese when outputting?

I'm using Python 2.7 in Jupyter Notebook.

This is how Python 2 works. It by default displays the repr() when generating display strings for lists and strings. You have to print strings to see the Unicode characters:

>>> D = {u'aka': [u'2019\u730e\u8840\u90fd\u5e02(\u6e2f)', u'\u9ece\u660e\u65f6\u5206']}
>>> D[u'aka'][0]
u'2019\u730e\u8840\u90fd\u5e02(\u6e2f)'
>>> print D[u'aka'][0]
2019猎血都市(港)

If you can't move to Python 3, you'll have to make your own display routine if you don't like the default repr() display. Something like:

D = {u'aka':[u'2019\u730e\u8840\u90fd\u5e02(\u6e2f)',u'\u9ece\u660e\u65f6\u5206']}

def dump(item):
    L = []
    if isinstance(item,dict):
        for k,v in item.items():
            L.append(dump(k) + ':')
            L.append(dump(v))
        return '{' + ', '.join(L) + '}'
    elif isinstance(item,list):
        for i in item:
            L.append(dump(i))
        return '[' + ', '.join(L) + ']'
    else:
        return "u'" + item + "'"

print dump(D)

Output:

{u'aka':, [u'2019猎血都市(港)', u'黎明时分']}

Note this is by no means complete as a generic dumping utility.

In Python 3 repr() has been updated:

>>> print(D)
{'aka': ['2019猎血都市(港)', '黎明时分']}

Call json.dump or json.dumps with ensure_ascii=False options, then you will get raw utf-8 encoded string.

referenced by https://docs.python.org/2/library/json.html

json.dump(obj, fp, skipkeys=False, **ensure_ascii=True**, check_circular=True, allow_nan=True, cls=None, indent=None, separators=None, encoding="utf-8", default=None, sort_keys=False, **kw)

you can try

df['douban_info'][0].to_json(ensure_ascii=False)

to get attribute values displayed with chinese character.

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