从数据框中的列中提取字典值 [英] Extract dictionary value from column in data frame

问题描述

我正在寻找一种优化我的代码的方法.

I'm looking for a way to optimize my code.

我以这种形式输入数据:

I have entry data in this form:

import pandas as pn

a=[{'Feature1': 'aa1','Feature2': 'bb1','Feature3': 'cc2' },
 {'Feature1': 'aa2','Feature2': 'bb2' },
 {'Feature1': 'aa1','Feature2': 'cc1' }
 ]
b=['num1','num2','num3']


df= pn.DataFrame({'num':b, 'dic':a })

我想从上面数据框中列"dic"(如果存在)中的字典中提取元素"Feature3".到目前为止，我已经能够解决它，但是我不知道这是否是最快的方法，这似乎有点复杂.

I would like to extract element 'Feature3' from dictionaries in column 'dic'(if exist) in above data frame. So far I was able to solve it but I don't know if this is the fastest way, it seems to be a little bit over complicated.

Feature3=[]
for idx, row in df['dic'].iteritems():
    l=row.keys()

    if 'Feature3' in l:
        Feature3.append(row['Feature3'])
    else:
        Feature3.append(None)

df['Feature3']=Feature3
print df

是否有更好/更快/更简单的方法来提取Feature3来分离数据框中的列?

Is there a better/faster/simpler way do extract this Feature3 to separate column in the dataframe?

预先感谢您的帮助.

推荐答案

您可以使用列表推导从数据框中的每一行提取特征3，并返回列表.

You can use a list comprehension to extract feature 3 from each row in your dataframe, returning a list.

feature3 = [d.get('Feature3') for d in df.dic]

如果"Feature3"不在dic中，则默认情况下返回None.

If 'Feature3' is not in dic, it returns None by default.

您甚至不需要熊猫，因为您可以再次使用列表理解功能从原始词典a中提取特征.

You don't even need pandas, as you can again use a list comprehension to extract the feature from your original dictionary a.

feature3 = [d.get('Feature3') for d in a]

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