Create a JSON string from column values

How do I mutate a Pandas DataFrame with a series of dictionaries.

Given the following DataFrame:

data = [['tom', 10], ['nick', 15], ['juli', 14]]
df = pd.DataFrame(data, columns = ['Name', 'Age'])

# add dict series
df = df.assign(my_dict="{}")
df.my_dict = df.my_dict.apply(json.loads)

How would I operate on column my_dict and mutate it as follows:

Age > 10

And then mutate again:

Name = "tom":

I’m interested in the process of mutating the dictionary, the rules are arbitrary examples.

>Solution :

You can use:

df['my_dict'] = df.apply(lambda x: x['my_dict'] | {'Age': x['Age'] > 10}, axis=1)
print(df)

# Output
   Name  Age         my_dict
0   tom   10  {'Age': False}
1  nick   15   {'Age': True}
2  juli   14   {'Age': True}

Add a new condition:

df['my_dict'] = df.apply(lambda x: x['my_dict'] | {'Name': x['Name'] == 'tom'}, axis=1)
print(df)

# Output
   Name  Age                       my_dict
0   tom   10  {'Age': False, 'Name': True}
1  nick   15  {'Age': True, 'Name': False}
2  juli   14  {'Age': True, 'Name': False}

Obviously if you want to convert to json, use:

>>> df['my_dict'].apply(json.dumps)
0    {"Age": false, "Name": true}
1    {"Age": true, "Name": false}
2    {"Age": true, "Name": false}
Name: my_dict, dtype: object