Python 类型错误：无法连接非 NDFrame 对象，当时间序列混杂时
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TypeError: cannot concatenate a non-NDFrame object, when time series mungling
提问by Hello lad
Have a time series ts (dataframe.to_dict())
有一个时间序列 ts (dataframe.to_dict())
{'latitude': {Timestamp('2014-10-20 15:21:56.571000'): 48.145553900000003,
Timestamp('2014-10-20 15:24:00.789000'): 48.145584300000003,
Timestamp('2014-10-20 15:26:00.911000'): 48.145497599999999,
Timestamp('2014-10-20 15:33:57.764000'): 48.145548699999999,
Timestamp('2014-10-20 15:36:45.760000'): 48.145454999999998},
'longitude': {Timestamp('2014-10-20 15:21:56.571000'): 11.578263,
Timestamp('2014-10-20 15:24:00.789000'): 11.5783685,
Timestamp('2014-10-20 15:26:00.911000'): 11.578193499999999,
Timestamp('2014-10-20 15:33:57.764000'): 11.5782843,
Timestamp('2014-10-20 15:36:45.760000'): 11.5783164},
'speed': {Timestamp('2014-10-20 15:21:56.571000'): 0.0,
Timestamp('2014-10-20 15:24:00.789000'): 0.0,
Timestamp('2014-10-20 15:26:00.911000'): 0.0,
Timestamp('2014-10-20 15:33:57.764000'): 0.0,
Timestamp('2014-10-20 15:36:45.760000'): 0.0}}
and a customized aggregation function (example)
和自定义聚合函数（示例）
def my_func(group):
first_latitude = group['latitude'].sort_index().head(1).values[0]
last_longitude = group['longitude'].sort_index().tail(1).values[0]
return first_latitude - last_longitude
want to aggregate time series with customized function by 10 min, so
想要将时间序列与自定义函数聚合 10 分钟，所以
ts.groupby(pd.TimeGrouper(freq='10Min')).apply(my_func)
then instead of correct result, it gives me error
然后而不是正确的结果，它给了我错误
TypeError: cannot concatenate a non-NDFrame object
What does this error say ? How could I write the code correctly ? thx a lot
这个错误说明了什么？我怎么能正确编写代码？多谢
采纳答案by CT Zhu
I think you want to agg(aggregate), not apply, as for each of your group, you want 1 returning value:
我认为您想要agg（聚合），而不是apply，对于您的每个组，您想要 1 个返回值：
In [185]:
print ts.groupby(pd.TimeGrouper(freq='10Min')).agg(my_func)
latitude longitude speed
2014-10-20 15:20:00 36.567360 36.567360 36.567360
2014-10-20 15:30:00 36.567232 36.567232 36.567232
回答by Joseph Farah
pd.DataFrame()might be what you are looking for. It allows you to parse two dimensional dictionaries (or anything, really with a tabular structure).
Here is the documentation for the function:
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html#pandas.DataFrame
pd.DataFrame()可能是你正在寻找的。它允许您解析二维字典（或任何东西，真正具有表格结构）。这是该函数的文档：http:
//pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html#pandas.DataFrame
