将包含pandas对象(系列/数据框)的python元组，列表，字典转换为json [英] Converting python tuple, lists, dictionaries containing pandas objects (series/dataframes) to json

问题描述

我知道我可以将Series，DataFrame之类的pandas对象转换为json，如下所示:

I know I can convert pandas object like Series, DataFrame to json as follows:

series1 = pd.Series(np.random.randn(5), name='something')
jsonSeries1 = series1.to_json() #{"0":0.0548079371,"1":-0.9072821424,"2":1.3865642993,"3":-1.0609052074,"4":-3.3513341839}

但是，当该系列封装在其他数据结构中时，我该怎么办，请说出字典，如下所示:

However what should I do when that series is encapsulated inside other datastructure, say dictionary as follows:

seriesmap = {"key1":pd.Series(np.random.randn(5), name='something')}

如何将上面的地图转换为json:

How do I convert above map to json like this:

{"key1":{"0":0.0548079371,"1":-0.9072821424,"2":1.3865642993,"3":-1.0609052074,"4":-3.3513341839}}

simplejson不起作用:

 jsonObj = simplejson.dumps(seriesmap)

给予

Traceback (most recent call last):
  File "C:\..\py2.py", line 86, in <module>
    jsonObj = json.dumps(seriesmap)
  File "C:\Mahesh\Program Files\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\simplejson\__init__.py", line 380, in dumps
    return _default_encoder.encode(obj)
  File "C:\Mahesh\Program Files\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\simplejson\encoder.py", line 275, in encode
    chunks = self.iterencode(o, _one_shot=True)
  File "C:\Mahesh\Program Files\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\simplejson\encoder.py", line 357, in iterencode
    return _iterencode(o, 0)
  File "C:\Mahesh\Program Files\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\simplejson\encoder.py", line 252, in default
    raise TypeError(repr(o) + " is not JSON serializable")
TypeError: 0   -0.038824
1   -0.047297
2   -0.887672
3   -1.510238
4    0.900217
Name: something, dtype: float64 is not JSON serializable

为了进一步概括这一点，我想将任意对象转换为json.任意对象可以是简单的int，字符串或复杂类型，例如包含pandas对象以及其他类型的元组，列表，字典.在字典中，熊猫对象可以位于任意深度作为某个键的值.我想将这样的结构安全地转换为有效的json.有可能吗?

To generalize this even further, I want to convert arbitrary object to json. The arbitrary object may be simple int, string or of complex types such that tuple, list, dictionary containing pandas objects along with other types. In dictionary the pandas object may lie at arbitrary depth as some key's value. I want to safely convert such structure to valid json. Is it possible?

更新

我只是尝试将DataFrame封装为字典键之一的值，然后通过封装在另一个DataFrame中将字典转换为json(如以下答案所示).但似乎不起作用:

I just tried encapsulating DataFrame as a value of one of the keys of a dictionary and converting that dictionary to json by encapsulating in another DataFrame (as suggested in below answer). But seems that it does not work:

import pandas as pd

d = {'one' : pd.Series([1., 2., 3.], index=['a', 'b', 'c']),
    'two' : pd.Series([1., 2., 3., 4.], index=['a', 'b', 'c', 'd'])}

df = pd.DataFrame(d)

mapDict = {"key1":df}
print(pd.DataFrame(mapDict).to_json())

这给了:

Traceback (most recent call last):
  File "C:\Mahesh\repos\JavaPython\JavaPython\bin\py2.py", line 80, in <module>
    print(pd.DataFrame(mapDict).to_json())
  File "C:\Mahesh\Program Files\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\pandas\core\frame.py", line 224, in __init__
    mgr = self._init_dict(data, index, columns, dtype=dtype)
  File "C:\Mahesh\Program Files\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\pandas\core\frame.py", line 360, in _init_dict
    return _arrays_to_mgr(arrays, data_names, index, columns, dtype=dtype)
  File "C:\Mahesh\Program Files\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\pandas\core\frame.py", line 5231, in _arrays_to_mgr
    index = extract_index(arrays)
  File "C:\Mahesh\Program Files\WinPython-64bit-3.4.4.4Qt5\python-3.4.4.amd64\lib\site-packages\pandas\core\frame.py", line 5270, in extract_index
    raise ValueError('If using all scalar values, you must pass'
ValueError: If using all scalar values, you must pass an index

推荐答案

在seriesmap上调用pd.DataFrame，然后使用to_json

pd.DataFrame(seriesmap).to_json()

'{"key1":{"0":0.8513342674,"1":-1.3357052602,"2":0.2102391775,"3":-0.5957492995,"4":0.2356552588}}'

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