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Introduction to Python(ihor)
Introduction to Python(ihor)
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 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
Nested Tuples in Python
Just like lists, tuples can also contain nested elements. For example, when storing country data in tuples, you can use nested indexing in the same way as with lists. The first index selects an item from the main tuple, while the second index accesses an element within the nested tuple.
# Two-dimensional tuple countries_2d = (('USA', 9629091, 331002651), ('Canada', 9984670, 37742154), ('Germany', 357114, 83783942), ('Brazil', 8515767, 212559417), ('India', 3166391, 1380004385)) # Get information about India print(countries_2d[4]) # Get the area of India print(countries_2d[4][1])
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Sektion 4. Kapitel 9
