2. Python Advanced Concepts

Objective:

By the end of this lesson, learners will master string manipulation, list comprehensions, advanced loops, and file handling in Python, with applications in data science workflows.

1. String Manipulation

Topics Covered:

• Splitting strings.

• Replacing substrings.

• f-strings for formatting.

Activity:

• Modify a filename string to remove the trailing -1 using .replace().

2. File Handling in Google Colab

Key Concepts:

• Mounting Google Drive.

• Searching for files.

3. List Comprehensions

Skills Practiced:

• Convert currencies.

• Filter data.

Activity:

• Filter a list of property records for entries in “Tlalpan”.

4. Advanced Loops

Key Concepts:

• while loops with break/continue.

• for loops with dictionaries.

Activity:

• Print only odd numbers from 0 to 100 using a for loop.

5. Nested Loops & Range

Examples:

• Nested loops.

• range() function.

Activity:

• Create an 8×8 grid of # symbols using nested loops.

6. Practical Exercises

Data Science Applications:

1. Summing numbers.

2. Filtering countries.

3. Reversing a list.

Challenge:

• Analyze countries_data.py to find:

  • Total languages.

  • Top 10 most spoken languages.

  • Top 10 most populated countries.

7. Summary & Resources

Key Takeaways:

• Strings: Split, replace, format.

• Files: Search/read in Colab.

• Loops: while, for, nested loops.

• Comprehensions: Transform/filter lists efficiently.

Access the whole lesson here: Access the lesson content here: Python Advanced Concepts.