将字典的pd DataFrame行分开成列

本文介绍了将字典的pd DataFrame行分开成列的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我正在从API中提取一些数据，并且在将其转换为适当的数据帧方面遇到了挑战.

I am extracting some data from an API and having challenges transforming it into a proper dataframe.

结果DataFrame df的排列方式如下:

The resulting DataFrame df is arranged as such:

Index Column 0 {'email@email': [{'action': 'data', 'date': 'date'}, {'action': 'data', 'date': 'date'}]} 1 {'different-email@email': [{'action': 'data', 'date': 'date'}]}

我正在尝试将电子邮件分为一列，然后将列表分为另一列:

I am trying to split the emails into one column and the list into a separate column:

Index Column1 Column2 0 email@email [{'action': 'data', 'date': 'date'}, {'action': 'data', 'date': 'date'}]}

理想情况下，每个动作"/日期"都有自己的单独一行，但是我相信我可以做进一步的分解工作.

Ideally, each 'action'/'date' would have it's own separate row, however I believe I can do the further unpacking myself.

环顾四周后，我尝试/失败了许多解决方案，例如:

After looking around I tried/failed lots of solutions such as:

df.apply(pd.Series) # does nothing pd.DataFrame(df['column'].values.tolist()) # makes each dictionary key as a separate colum where most of the rows are NaN except one which has the pair value

许多问题都询问API中数据的初始格式，这是字典的列表:

As many of the questions asked the initial format of the data in the API, it's a list of dictionaries:

[{'email@email': [{'action': 'data', 'date': 'date'}, {'action': 'data', 'date': 'date'}]},{'different-email@email': [{'action': 'data', 'date': 'date'}]}]

谢谢

推荐答案

一种朴素的方法如下:

inp = [{'email@email': [{'action': 'data', 'date': 'date'}, {'action': 'data', 'date': 'date'}]} , {'different-email@email': [{'action': 'data', 'date': 'date'}]}] index = 0 df = pd.DataFrame() for each in inp: # iterate through the list of dicts for k, v in each.items(): #take each key value pairs for eachv in v: #the values being a list, iterate through each print (str(eachv)) df.set_value(index,'Column1',k) df.set_value(index,'Column2',str(eachv)) index += 1

我确信可能会有更好的方式编写此内容.希望这会有所帮助:)

I am sure there might be a better way of writing this. Hope this helps :)