如何使用for循环遍历列表中的这个嵌套字典

Question

I have a list of nested dictionaries that I want to get specific values and put into a dictionary like this:

vid = [{'a':{'display':'axe', 'desc':'red'}, 'b':{'confidence':'good'}},        
       {'a':{'display':'book', 'desc':'blue'}, 'b':{'confidence':'poor'}},  
       {'a':{'display':'apple', 'desc':'green'}, 'b':{'confidence':'good'}}
      ]

I saw previous questions similar to this, but I still can't get the values such as 'axe' and 'red' . I would like the new dict to have a 'Description' , 'Confidence' and other columns with the values from the nested dict.

I have tried this for loop:

    new_dict = {}

    for x in range(len(vid)):
       for y in vid[x]['a']:
           desc = y['desc']
           new_dict['Description'] = desc

I got many errors but mostly this error: TypeError: string indices must be integers

Can someone please help solve how to get the values from the nested dictionary?

Answer 1

You don't need to iterate through the keys in the dictionary (the inner for-loop), just access the value you want.

vid = [{'a':{'display':'axe', 'desc':'red'}, 'b':{'confidence':'good'} },
       {'a':{'display':'book', 'desc':'blue'}, 'b':{'confidence':'poor'}},  
       {'a':{'display':'apple', 'desc':'green'}, 'b':{'confidence':'good'}}
      ]

new_dict = {}

list_of_dicts = []

for x in range(len(vid)):
   desc = vid[x]['a']['desc']
   list_of_dicts.append({'desc': desc})

Answer 2

Try using this list comprehension:

d = [{'Description': i['a']['desc'], 'Confidence': i['b']['confidence']} for i in vid]
print(d)

Answer 3

I have found a temporary solution for this. I decided to use the pandas dataframe instead.

df = pd.DataFrame(columns = ['Desc'])

for x in range(len(vid)):
    desc = vid[x]['a']['desc']
    df.loc[len(df)] = [desc]

Answer 4

so you want to write this to csv later so pandas will help you a lot for this problem using pandas you can get the desc by

import pandas as pd
new_dict = {}
df = pd.DataFrame(vid)
for index, row in df.iterrows() : 
     new_dict['description'] = row['a']['desc']


                                       a                       b
          0      {'display': 'axe', 'desc': 'red'}  {'confidence': 'good'}
          1    {'display': 'book', 'desc': 'blue'}  {'confidence': 'poor'}
          2  {'display': 'apple', 'desc': 'green'}  {'confidence': 'good'}

this is how dataframe looks like ab are column of the dataframe and your nested dicts are rows of dataframe