Python Forum

Hi All,

So I have created a dictionary:

myDict = {
  "Name": {"Kindle Fire", "Samsung Galaxy Tab", "Dell Streak", "Apple iPad", "Lenovo Tab"},
  "Memory": {16, 8, 16, 64, 32},
  "Processor": {2.2, 1.2, 1.8, 2.65, 2.3},
  "Cost": {199, 114.99, 59.99, 319, 129},
}

I want to write a bit of python code that will print out the keys and the values of the devices that are over 150 in cost. However I am not sure how to do that? Any idea or a place where to look?

Thanks

Maybe restructure the dict like this

myDict = {
    'Kendle Fire': {'Memory': 16, 'Processor': 2.2, 'Cost': 199 },
    'Samsung Galaxy': {'Memory': 8, 'Processor': 1.2, 'Cost': 114.99},
    'Dell Streak': {'Memory': 16, 'Processor': 1.8, 'Cost': 59.99},
    'Apple IPad': {'Memory': 64, 'Processor': 2.65, 'Cost': 319},
    'Lenovo Tab': {'Memory': 32, 'Processor': 2.3, 'Cost': 129}
}

for item in myDict.keys():
    for data, info in myDict[item].items():
        if info > 150:
            print(item, myDict[item])

output

Output:
Kendle Fire {'Memory': 16, 'Processor': 2.2, 'Cost': 199}
Apple IPad {'Memory': 64, 'Processor': 2.65, 'Cost': 319}

Note that values in your dict are set, i.e. unordered collection

(Apr-12-2023, 06:42 PM)menator01 Wrote: [ -> ]Maybe restructure the dict like this

myDict = {
    'Kendle Fire': {'Memory': 16, 'Processor': 2.2, 'Cost': 199 },
    'Samsung Galaxy': {'Memory': 8, 'Processor': 1.2, 'Cost': 114.99},
    'Dell Streak': {'Memory': 16, 'Processor': 1.8, 'Cost': 59.99},
    'Apple IPad': {'Memory': 64, 'Processor': 2.65, 'Cost': 319},
    'Lenovo Tab': {'Memory': 32, 'Processor': 2.3, 'Cost': 129}
}

for item in myDict.keys():
    for data, info in myDict[item].items():
        if info > 150:
            print(item, myDict[item])

output

Output:
Kendle Fire {'Memory': 16, 'Processor': 2.2, 'Cost': 199}
Apple IPad {'Memory': 64, 'Processor': 2.65, 'Cost': 319}

This is perfect Thank you, I assumed that nested for Loops would be needed but wasn't sure on the execution. Thanks again.

Or a dataclass.

https://docs.python.org/3/library/dataclasses.html

from dataclasses import dataclass


@dataclass(order=True)
class Computer:
    name: str
    memory: float
    processor: str
    cost: float


computers = [
    Computer("Kindle Fire", 16, "2.2", 199),
    Computer("Samsung Galaxy", 8, "1.2", 114.99),
    Computer("Dell Streak", 16, "1.8", 59.99),
    Computer("Apple IPad", 64, "2.65", 319),
    Computer("Lenovo Tab", 32, "2.3", 129),
]

print("Computers", *sorted(computers), sep="\n")
print("\nBy price", *sorted(computers, key=lambda x: x.cost), sep="\n")
print("\nBy memory", *sorted(computers, key=lambda x: x.memory), sep="\n")
print("\nLess than $150", *(c for c in computers if c.cost < 150), sep="\n")

Output:
Computers
Computer(name='Apple IPad', memory=64, processor='2.65', cost=319)
Computer(name='Dell Streak', memory=16, processor='1.8', cost=59.99)
Computer(name='Kendle Fire', memory=16, processor='2.2', cost=199)
Computer(name='Lenovo Tab', memory=32, processor='2.3', cost=129)
Computer(name='Samsung Galaxy', memory=8, processor='1.2', cost=114.99)

By price
Computer(name='Dell Streak', memory=16, processor='1.8', cost=59.99)
Computer(name='Samsung Galaxy', memory=8, processor='1.2', cost=114.99)
Computer(name='Lenovo Tab', memory=32, processor='2.3', cost=129)
Computer(name='Kendle Fire', memory=16, processor='2.2', cost=199)
Computer(name='Apple IPad', memory=64, processor='2.65', cost=319)

By memory
Computer(name='Samsung Galaxy', memory=8, processor='1.2', cost=114.99)
Computer(name='Kendle Fire', memory=16, processor='2.2', cost=199)
Computer(name='Dell Streak', memory=16, processor='1.8', cost=59.99)
Computer(name='Lenovo Tab', memory=32, processor='2.3', cost=129)
Computer(name='Apple IPad', memory=64, processor='2.65', cost=319)

Less than $150
Computer(name='Samsung Galaxy', memory=8, processor='1.2', cost=114.99)
Computer(name='Dell Streak', memory=16, processor='1.8', cost=59.99)
Computer(name='Lenovo Tab', memory=32, processor='2.3', cost=129)

As mention bye buran so is it set,then there is one more surprise.

>>> memory = {16, 8, 16, 64, 32}
>>> memory
{16, 8, 32, 64} 

Oops missing one value👀
So list/tuple would be more suited for this task,and to show an other way,Pandas do also like this kind of structure.

import pandas as pd

my_dict = {
  "Name": ["Kindle Fire", "Samsung Galaxy Tab", "Dell Streak", "Apple iPad", "Lenovo Tab"],
  "Memory": [16, 8, 16, 64, 32],
  "Processor": [2.2, 1.2, 1.8, 2.65, 2.3],
  "Cost": [199, 114.99, 59.99, 319, 129],
}

df = pd.DataFrame(my_dict)

>>> df
                 Name  Memory  Processor    Cost
0         Kindle Fire      16       2.20  199.00
1  Samsung Galaxy Tab       8       1.20  114.99
2         Dell Streak      16       1.80   59.99
3          Apple iPad      64       2.65  319.00
4          Lenovo Tab      32       2.30  129.00

>>> # Select the devices whose cost is over 150 using query
>>> selected_devices = df.query('Cost > 150')['Name']
>>> selected_devices
0    Kindle Fire
3     Apple iPad
Name: Name, dtype: object

Pandas plays nice with dataclasses.

from dataclasses import dataclass
import pandas as pd


@dataclass(order=True)
class Computer:
    name: str
    memory: float
    processor: str
    cost: float


computers = [
    Computer("Kendle Fire", 16, "2.2", 199),
    Computer("Samsung Galaxy", 8, "1.2", 114.99),
    Computer("Dell Streak", 16, "1.8", 59.99),
    Computer("Apple IPad", 64, "2.65", 319),
    Computer("Lenovo Tab", 32, "2.3", 129),
]

df = pd.DataFrame(computers)
print("All computers", df, sep="\n")
print("\nCheap computers", df[df["cost"] < 150], sep="\n")  # could also use query like snippsat

Output:
All computers
             name  memory processor    cost
0     Kendle Fire      16       2.2  199.00
1  Samsung Galaxy       8       1.2  114.99
2     Dell Streak      16       1.8   59.99
3      Apple IPad      64      2.65  319.00
4      Lenovo Tab      32       2.3  129.00

Cheap computers
             name  memory processor    cost
1  Samsung Galaxy       8       1.2  114.99
2     Dell Streak      16       1.8   59.99
4      Lenovo Tab      32       2.3  129.00