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Learn Python from Scratch
course content

Course Content

Learn Python from Scratch

Learn Python from Scratch

1. The basics
Hello, World!Hello, me!VariablesCommentsIndentationNumbers and strings
2. Arithmetic operations
AdditionMultiplication and powerDivision and whole part division
3. Common data types
Data typesNumbersfloat and intStoring textStrings slicingConcatenation
4. Conditional statements
Boolean data typeCombining conditionsSimple if/else expressions (1/2)Simple if/else expressions (2/2)If/else expressions with multiple conditions (1/2)If/else expressions with multiple conditions (2/2)
5. Other data types
Lists (1/3)Lists (2/3)Lists (3/3)Tuples (1/3)Tuples (2/3)Tuples (3/3)Dictionaries (1/2)Dictionaries (2/2)
6. Loops
while loop (1/2)while loop (2/2)for loop (1/5)for loop (2/5)for loop (3/5)for loop (4/5)for loop (5/5)
7. Functions
Built-in functionsWriting your own functions (1/5)Writing your own functions (2/5)Writing your own functions (3/5)Writing your own functions (4/5)Writing your own functions (5/5)lambda functions

bookWriting your own functions (5/5)

But what if in our examples we pass as country argument some inappropriate name or name which does not exist in our dictionary? Let's predict it with some conditional statements!


              
1234567891011121314151617

            
# data
countries_dict = {'USA': (9629091, 331002651), 'Canada': (9984670, 37742154), 'Germany': (357114, 83783942)}
countries_dict["Brazil"] = (8515767, 212559417)
countries_dict["India"] = (3166391, 1380004385)

# modify our function
def country_information_mod(d, name):
  if name not in d.keys():
    print("There is no information about", name)
  else:
    print("Country:", name)
    print("Area:", d[name][0], 'sq km')
    print("Population:", round(d[name][1]/1000000, 2), 'mln')
        
# test our function
country_information_mod(countries_dict, "Ukraine")
country_information_mod(countries_dict, "USA")
copy

Task

Modify your previous function (name new as people_information_mod) so now it will detect if the name is in the dictionary. If not, print "There is no information about name"

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 7. Chapter 6
toggle bottom row

bookWriting your own functions (5/5)

But what if in our examples we pass as country argument some inappropriate name or name which does not exist in our dictionary? Let's predict it with some conditional statements!


              
1234567891011121314151617

            
# data
countries_dict = {'USA': (9629091, 331002651), 'Canada': (9984670, 37742154), 'Germany': (357114, 83783942)}
countries_dict["Brazil"] = (8515767, 212559417)
countries_dict["India"] = (3166391, 1380004385)

# modify our function
def country_information_mod(d, name):
  if name not in d.keys():
    print("There is no information about", name)
  else:
    print("Country:", name)
    print("Area:", d[name][0], 'sq km')
    print("Population:", round(d[name][1]/1000000, 2), 'mln')
        
# test our function
country_information_mod(countries_dict, "Ukraine")
country_information_mod(countries_dict, "USA")
copy

Task

Modify your previous function (name new as people_information_mod) so now it will detect if the name is in the dictionary. If not, print "There is no information about name"

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 7. Chapter 6
toggle bottom row

bookWriting your own functions (5/5)

But what if in our examples we pass as country argument some inappropriate name or name which does not exist in our dictionary? Let's predict it with some conditional statements!


              
1234567891011121314151617

            
# data
countries_dict = {'USA': (9629091, 331002651), 'Canada': (9984670, 37742154), 'Germany': (357114, 83783942)}
countries_dict["Brazil"] = (8515767, 212559417)
countries_dict["India"] = (3166391, 1380004385)

# modify our function
def country_information_mod(d, name):
  if name not in d.keys():
    print("There is no information about", name)
  else:
    print("Country:", name)
    print("Area:", d[name][0], 'sq km')
    print("Population:", round(d[name][1]/1000000, 2), 'mln')
        
# test our function
country_information_mod(countries_dict, "Ukraine")
country_information_mod(countries_dict, "USA")
copy

Task

Modify your previous function (name new as people_information_mod) so now it will detect if the name is in the dictionary. If not, print "There is no information about name"

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

But what if in our examples we pass as country argument some inappropriate name or name which does not exist in our dictionary? Let's predict it with some conditional statements!


              
1234567891011121314151617

            
# data
countries_dict = {'USA': (9629091, 331002651), 'Canada': (9984670, 37742154), 'Germany': (357114, 83783942)}
countries_dict["Brazil"] = (8515767, 212559417)
countries_dict["India"] = (3166391, 1380004385)

# modify our function
def country_information_mod(d, name):
  if name not in d.keys():
    print("There is no information about", name)
  else:
    print("Country:", name)
    print("Area:", d[name][0], 'sq km')
    print("Population:", round(d[name][1]/1000000, 2), 'mln')
        
# test our function
country_information_mod(countries_dict, "Ukraine")
country_information_mod(countries_dict, "USA")
copy

Task

Modify your previous function (name new as people_information_mod) so now it will detect if the name is in the dictionary. If not, print "There is no information about name"

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 7. Chapter 6
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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