Using Dictionaries to Store Structured Data¶

The values in a dictionary can be lists. This is convenient if we would like use a dictionary to store records of some type. In this case, we can imagine the keys of the dictionary as indicating columns in a table.

employee_dict = {
    'EID': [103, 105, 101, 106, 108],
    'Name': ['Anna', 'Beth', 'Craig', 'Drew', 'Emma'],
    'Salary': [43700, 50250, 47600, 39800, 38750],
    'Rank': [2, 1, 1, 2, 3]
}

Each key in the dictionary represents a particular type of information. The associated value is a list that represents this piece of information for each record (row) in our table.

print(employee_dict['Name'])

['Anna', 'Beth', 'Craig', 'Drew', 'Emma']

If we want to see the information for a specific entry in the table, we can provide the same index to each of the lists stored within the dictionary.

print('EID   Name    Salary  Rank')
print('---------------------------------')
for i in range(len(employee_dict['Name'])):
    e = employee_dict['EID'][i]
    n = employee_dict['Name'][i] 
    s = employee_dict['Salary'][i]
    r = employee_dict['Rank'][i]
    
    print(f'{e:<6}{n:<8}{s:<8}{r:>4}')
    

EID   Name    Salary  Rank
---------------------------------
 Anna    43700      2
 Beth    50250      1
 Craig   47600      1
 Drew    39800      2
 Emma    38750      3

One limitation of using a dictionary in this way is that there is no convenient way to extract all of the information related to a single individual at once.

As an alternate approach to using dictionaries to store structured data, we can store individual records in dictionaries, and then collect them together into a list (or another dictionary). In the setup, we could imaging the dictionaries as representing rows in a table rather than columns.

my_cats = [
    {
        'name':'Luna', 
        'birthplace':'State College, PA', 
        'weight':14.3, 
        'age':11, 
        'characteristics':['lazy', 'hungry', 'cranky']
    },
    {
        'name':'Garbanzo', 
        'birthplace':'State College, PA',
        'weight':8.9,
        'age':11,
        'characteristics':['talkative', 'friendly', 'skittish']
    },
    {
        'name':'Cauchy',
        'birthplace':'St. Louis, MO',
        'weight':10.6,
        'age':4,
        'characteristics':['insane', 'destructive', 'scoundrel']
    }
]

We will display the contents of the list above by looping over the dictionaries contained inside of it. We will use an f-string to print the values stored in each of the dictionaries.

print(f'{"Name":<12}{"Birthplace":<20}{"Weight":>6}{"Age":>6}   {"Characteristics":<10}')
print('-'*85)
for cat in my_cats:
        
    n = cat['name'] 
    b = cat['birthplace'] 
    w = cat['weight'] 
    a = cat['age'] 
    c = cat['characteristics'] 
    
    print(f'{n:<12}{b:<20}{w:>6}{a:>6}   {str(c):<10}')
    

Name        Birthplace          Weight   Age   Characteristics
-------------------------------------------------------------------------------------
Luna        State College, PA     14.3    11   ['lazy', 'hungry', 'cranky']
Garbanzo    State College, PA      8.9    11   ['talkative', 'friendly', 'skittish']
Cauchy      St. Louis, MO         10.6     4   ['insane', 'destructive', 'scoundrel']

Python for Data Science

Using Dictionaries to Store Structured Data¶