将字典的pd DataFrame行分开成列 [英] Separate pd DataFrame Rows that are dictionaries into columns
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.com': [{'action': 'data', 'date': 'date'}, {'action': 'data', 'date': 'date'}]}
1 {'different-email@email.com': [{'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.com [{'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.com': [{'action': 'data', 'date': 'date'}, {'action': 'data', 'date': 'date'}]},{'different-email@email.com': [{'action': 'data', 'date': 'date'}]}]
谢谢
推荐答案
一种朴素的方法如下:
inp = [{'email@email.com': [{'action': 'data', 'date': 'date'}, {'action': 'data', 'date': 'date'}]}
, {'different-email@email.com': [{'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 :)
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