Course Content
Introduction to Python
Introduction to Python
2. Variables and Types in Python
How to Store Numbers in PythonPython Naming Rules for VariablesHow to Work with Variables in PythonData Types in PythonChallenge: Converting Kilometers to MilesStore Text with Strings in PythonString Indexing in PythonNegative Indexing and String Length in PythonString Slicing in PythonChallenge: Retrieving Letters from StringString Concatenation in Python
3. Conditional Statements in Python
Boolean Data Type in PythonChallenge: Working with Comparison OperatorsHow to Combine Conditions in PythonChallenge: Working with Logical OperatorsMembership Operators and Type Comparisons in PythonHow to Use if/else Expressions in PythonChallenge: Running a Grocery StoreChallenge: Creating Odd and Even Logicif/elif/else ExpressionsChallenge: Running Grocery Store ExtendedChallenge: Weather Adviser
4. Other Data Types in Python
Python ListsCommon List Methods in PythonChallenge: Updating ListNested Lists in PythonChallenge: Retrieving Information from Nested ListPython TuplesCommon Tuple Methods in PythonChallenge: Updating TupleNested Tuples in PythonChallenge: Retrieving Information from Nested TuplePython DictionariesChallenge: Creating DictionaryCommon Dictionary Methods in PythonChallenge: Updating Dictionary
6. Functions in Python
Built-in Functions in PythonChallenge: Converting HeightsHow to Create Functions in PythonChallenge: Writing First FunctionUse of if/else Statements in Python FunctionsChallenge: Identifying Positive Values Functions Without Return in PythonChallenge: Creating Logging FunctionModifying Functions in PythonChallenge: Updating Logic of the FunctionLambda Functions in PythonChallenge: Creating Lambda Function
Modifying Functions in Python
Reconsider the example with the country information. What happens if the provided name parameter isn't found in the dataset?
# Data countries_dict = {'USA': (9629091, 331002651), 'Canada': (9984670, 37742154), 'Germany': (357114, 83783942), 'Brazil': (8515767, 212559417), 'India': (3166391, 1380004385)} # Defining a function def country_information(d, name): print('Country:', name) print('Area:', d[name][0], 'sq km') print('Population:', round(d[name][1]/1000000, 2), 'MM') # Testing the function country_information(countries_dict, 'USA') country_information(countries_dict, 'Ukraine')
Can we handle this situation? Absolutely, by implementing conditional statements!
# Data countries_dict = {'USA': (9629091, 331002651), 'Canada': (9984670, 37742154), 'Germany': (357114, 83783942), 'Brazil': (8515767, 212559417), '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') # Testing the function country_information_mod(countries_dict, "USA") country_information_mod(countries_dict, "Ukraine")
Note
The method
d.keys()is a dictionary method that returns a view containing all the keys from the dictionaryd. Here, it's used to check whether the providednameexists among the dictionary's keys.
As demonstrated, the error message in this revised format is more user-friendly. Although many other potential errors exist, there are numerous methods to handle them.
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SectionΒ 6. ChapterΒ 9
