How to replace a value for a key in dictionaries of a list based on another dictionary?

user_7048760 0
Viewed 31

Here's a sample of the data:

[{
  'name': 'Age', 
  'p_value': '<0.001', 
  'ks_score': '0.07', 
}, 
{
  'name': 'peer_LM_Mean_SelfAware', 
  'p_value': '<0.001', 
  'ks_score': '0.06', 
}]

I have over 16k dictionaries with several items in the list. What I want to do is replace the value of name in this dictionary from another dictionary which consists of the old name and new name.

col_rename_list = {'Male': 'Male, n (%)', 
                   'Age': 'Age, years', 
                   'Baby_Boomers__1946_1964_': 'Baby Boomers (1946-1964), n (%)',
                   'Generation_X__1965_1980_': 'Generation X (1965-1980), n (%)',
                   'Generation_Y___Millennials__1981_1996_': 'Generation Y/Millennials (1981-1996), n (%)', 
                   'Race_Asian': 'Asian, n (%)',
                   'peer_LM_Mean_SelfAware': 'Self-Awareness'
                  }

How can I do this? One way that I could think of is the following:

for d in dictionary_list:
    for k,v in d.items():
        if k == 'name':
            if col_rename_list.get(v) is not None:
                d[k] = col_rename_list.get(v)

This works, but is there a better and efficient way to do this?

list-comprehension dictionary python
1 Answers

You can use dict.get with with default parameter:

lst = [
    {
        "name": "Age",
        "p_value": "<0.001",
        "ks_score": "0.07",
    },
    {
        "name": "peer_LM_Mean_SelfAware",
        "p_value": "<0.001",
        "ks_score": "0.06",
    },
]

col_rename_list = {
    "Male": "Male, n (%)",
    "Age": "Age, years",
    "Baby_Boomers__1946_1964_": "Baby Boomers (1946-1964), n (%)",
    "Generation_X__1965_1980_": "Generation X (1965-1980), n (%)",
    "Generation_Y___Millennials__1981_1996_": "Generation Y/Millennials (1981-1996), n (%)",
    "Race_Asian": "Asian, n (%)",
    "peer_LM_Mean_SelfAware": "Self-Awareness",
}

for d in lst:
    d["name"] = col_rename_list.get(d["name"], d["name"])

# pretty print:
from pprint import pprint
pprint(lst)

Prints:

[{'ks_score': '0.07', 'name': 'Age, years', 'p_value': '<0.001'},
 {'ks_score': '0.06', 'name': 'Self-Awareness', 'p_value': '<0.001'}]
user_100359850
Related