Process dict values¶
Let us understand how we can process the values in dicts.
- We have already seen a function called as
valueswhich return all the values as a list like object.
In [1]:
order_item_subtotals = {
1: 299.98,
2: 199.99,
3: 250.0,
4: 129.99
}
In [2]:
order_item_subtotals
Out[2]:
{1: 299.98, 2: 199.99, 3: 250.0, 4: 129.99}
In [3]:
type(order_item_subtotals)
Out[3]:
dict
In [4]:
order_item_subtotals.values()
Out[4]:
dict_values([299.98, 199.99, 250.0, 129.99])
In [5]:
type(order_item_subtotals.values())
Out[5]:
dict_values
- If we would like to get total revenue by adding all the values, we can apply
sum.
In [6]:
sum(order_item_subtotals.values())
Out[6]:
879.96
In [7]:
# min
min(order_item_subtotals.values())
Out[7]:
129.99
In [8]:
# max
max(order_item_subtotals.values())
Out[8]:
299.98
In [9]:
# sort
sorted(order_item_subtotals.values())
Out[9]:
[129.99, 199.99, 250.0, 299.98]
- We can convert the values to
listand perform all available list operations.
In [10]:
list(order_item_subtotals.values())
Out[10]:
[299.98, 199.99, 250.0, 129.99]
- The values in the
dictneed not be unique. Sometimes, we might want to get all the unique values. - For example, get all the unique sports that is part of this dict. In this
dict, the key is name of the sports person and the value is the sport the person plays.
{note}
You can always use `set` to get unique elements from any list type object.In [11]:
famous_players = {
'Pete Sampras': 'Tennis',
'Sachin Tendulkar': 'Cricket',
'Brian Lara': 'Cricket',
'Diego Maradona': 'Soccer',
'Roger Federer': 'Tennis',
'Ian Thorpe': 'Swimming',
'Ronaldo': 'Soccer',
'Usain Bolt': 'Running',
'P. V. Sindhu': 'Badminton',
'Shane Warne': 'Cricket',
'David Beckham': 'Cricket',
'Michael Phelps': 'Swimming'
}
In [12]:
famous_players.values()
Out[12]:
dict_values(['Tennis', 'Cricket', 'Cricket', 'Soccer', 'Tennis', 'Swimming', 'Soccer', 'Running', 'Badminton', 'Cricket', 'Cricket', 'Swimming'])
In [13]:
len(famous_players.values())
Out[13]:
12
In [14]:
set(famous_players.values())
Out[14]:
{'Badminton', 'Cricket', 'Running', 'Soccer', 'Swimming', 'Tennis'}
In [15]:
len(set(famous_players.values()))
Out[15]:
6