pandas 数据框中的字典列 [英] Dictionary column in pandas dataframe

问题描述

我有一个csv，我正在将其读入pandas数据框.但是，其中一列是字典的形式.这是一个示例:

I've got a csv that I'm reading into a pandas dataframe. However one of the columns is in the form of a dictionary. Here is an example:

ColA, ColB, ColC, ColdD
20, 30, {"ab":"1", "we":"2", "as":"3"},"String"

如何将其转换为如下所示的数据框:

How can I turn this into a dataframe that looks like this:

ColA, ColB, AB, WE, AS, ColdD
20, 30, "1", "2", "3", "String"

编辑 我解决了这个问题，它看起来像这样，但是它是一个需要解析的字符串，而不是dict对象.

edit I fixed up the question, it looks like this but is a string that needs to be parsed, not dict object.

推荐答案

按照 https://stackoverflow.com/a/38231651 /454773 ，您可以使用.apply(pd.Series)将包含dict的列映射到新列，然后将这些新列连接回到原始数据框中，减去包含dict的原始列:

As per https://stackoverflow.com/a/38231651/454773, you can use .apply(pd.Series) to map the dict containing column onto new columns and then concatenate these new columns back into the original dataframe minus the original dict containing column:

dw=pd.DataFrame( [[20, 30, {"ab":"1", "we":"2", "as":"3"},"String"]],
                columns=['ColA', 'ColB', 'ColC', 'ColdD'])
pd.concat([dw.drop(['ColC'], axis=1), dw['ColC'].apply(pd.Series)], axis=1)

返回:

ColA    ColB    ColdD   ab  as  we
20      30      String  1   3   2

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