将Python dict转换为数据帧 [英] Convert Python dict into a dataframe

问题描述

我有一个Python字典，如下所示：

I have a Python dictionary like the following:

{u'2012-06-08': 388,
 u'2012-06-09': 388,
 u'2012-06-10': 388,
 u'2012-06-11': 389,
 u'2012-06-12': 389,
 u'2012-06-13': 389,
 u'2012-06-14': 389,
 u'2012-06-15': 389,
 u'2012-06-16': 389,
 u'2012-06-17': 389,
 u'2012-06-18': 390,
 u'2012-06-19': 390,
 u'2012-06-20': 390,
 u'2012-06-21': 390,
 u'2012-06-22': 390,
 u'2012-06-23': 390,
 u'2012-06-24': 390,
 u'2012-06-25': 391,
 u'2012-06-26': 391,
 u'2012-06-27': 391,
 u'2012-06-28': 391,
 u'2012-06-29': 391,
 u'2012-06-30': 391,
 u'2012-07-01': 391,
 u'2012-07-02': 392,
 u'2012-07-03': 392,
 u'2012-07-04': 392,
 u'2012-07-05': 392,
 u'2012-07-06': 392}

Unicode 日期，值为整数。通过将日期及其对应的值作为两个单独的列，我想将其转换为大熊猫数据框。示例：col1：日期col2：DateValue（日期仍然是Unicode和日期值仍然是整数）

The keys are Unicode dates and the values are integers. I would like to convert this into a pandas dataframe by having the dates and their corresponding values as two separate columns. Example: col1: Dates col2: DateValue (the dates are still Unicode and datevalues are still integers)

     Date         DateValue
0    2012-07-01    391
1    2012-07-02    392
2    2012-07-03    392
.    2012-07-04    392
.    ...           ...
.    ...           ...

对此方向的任何帮助将不胜感激。我无法在熊猫文档中找到资源来帮助我。

Any help in this direction would be much appreciated. I am unable to find resources on the pandas docs to help me with this.

我知道一个解决方案可能是将这个dict中的每个键值对转换为dict所以整个结构变成一个dict的指令，然后我们可以将每一行分别添加到数据框。但是我想知道是否有更简单的方法和更直接的方式来实现。

I know one solution might be to convert each key-value pair in this dict, into a dict so the entire structure becomes a dict of dicts, and then we can add each row individually to the dataframe. But I want to know if there is an easier way and a more direct way to do this.

到目前为止，我已经尝试将dict转换为一个系列对象，但这不似乎保持列之间的关系：

So far I have tried converting the dict into a series object but this doesn't seem to maintain the relationship between the columns:

s  = Series(my_dict,index=my_dict.keys())

推荐答案

这里的错误是使用标量调用DataFrame构造函数值（它希望值为列表/ dict / ...即有多个列）：

The error here, is since calling the DataFrame constructor with scalar values (where it expects values to be a list/dict/... i.e. have multiple columns):

pd.DataFrame(d)
ValueError: If using all scalar values, you must must pass an index

您可以从字典中获取项目（即键值对）：

You could take the items from the dictionary (i.e. the key-value pairs):

In [11]: pd.DataFrame(d.items())  # or list(d.items()) in python 3
Out[11]:
             0    1
0   2012-07-02  392
1   2012-07-06  392
2   2012-06-29  391
3   2012-06-28  391
...

In [12]: pd.DataFrame(d.items(), columns=['Date', 'DateValue'])
Out[12]:
          Date  DateValue
0   2012-07-02        392
1   2012-07-06        392
2   2012-06-29        391

但是，我认为通过Series构造函数更有意义：

But I think it makes more sense to pass the Series constructor:

In [21]: s = pd.Series(d, name='DateValue')
Out[21]:
2012-06-08    388
2012-06-09    388
2012-06-10    388

In [22]: s.index.name = 'Date'

In [23]: s.reset_index()
Out[23]:
          Date  DateValue
0   2012-06-08        388
1   2012-06-09        388
2   2012-06-10        388

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