CODEWITHSUNDEEP
pythonpandasstringdataframedictionary
Azamat Kaliyev
Azamat Kaliyev

Reputation: 11

How to get values in a column of dictionary-like string?

I have a dataframe with a column that looks like this:

d = {'genres': 
      [ [
          {"id": 10751,"name": "Family"}, 
          {"id": 16, "name": "Animation"}, 
          {"id": 12, "name": "Adventure"},           
          {"id": 35, "name": "Comedy"}],
        [
          {"id": 878, "name": "Science Fiction"}, 
          {"id": 12, "name": "Adventure"}, 
          {"id": 53, "name": "Thriller"}]]}

df_input = pd.DataFrame(data=d)

I need the following output:

d = {'genres': 
      [ ["Family", "Animation", "Adventure", "Comedy",],
        ["Science Fiction", "Adventure", "Thriller"]]}

df_output = pd.DataFrame(data=d)

Upvotes: 0

Views: 58

Answers (2)

jezrael
jezrael

Reputation: 862581

You can extract values from dictionary by list comprehension in Series.apply:

df_input['genres'] = df_input['genres'].apply(lambda x:[y['name'] for y in x])
print (df_input)
                                   genres
0  [Family, Animation, Adventure, Comedy]
1  [Science Fiction, Adventure, Thriller]

Or by nested list comprehension:

df_input['genres'] = [[y['name'] for y in x] for x in df_input['genres']]

EDIT: If real data contsins stings, not dicts use:

import json, ast

df_input['genres'] = df_input['genres'].apply(lambda x:[y['name'] for y in ast.literal_eval(x)])

Or:

df_input['genres'] = df_input['genres'].apply(lambda x:[y['name'] for y in json.loads(x)])

Upvotes: 2

Ravish Verma
Ravish Verma

Reputation: 221

If you want to do this with pandas, it is possible with apply method Try creating a function to return "name" values for each element,

>>> def getNames(x):
        return [xi["name"] for xi in x]

Now, all you need to do is apply it on a column in your dataframe,

>>> df = pd.DataFrame(data=d)

>>> d_out = df['genres'].apply(getNames) # This returns the output that you want

>>> df_output = pd.DataFrame(data=d_out, columns=["genres"])

    genres
0  [Family, Animation, Adventure, Comedy]
1  [Science Fiction, Adventure, Thriller]

There could be shorter ways.

Upvotes: 0

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