5. Strings, Lists, and Files (Multiple Pieces of Data)

If we want to do data science, we’ll need tools to deal with many pieces of data at once. Data often enters the data science workflow in one or more files. From there we read it into strings, then usually break it up into separate values using lists. All of these are tools for working with multiple pieces of data; we’ll even see that a string is really multiple pieces of data (the individual characters) stored together in one place.

• 5.1. Strings
  • 5.1.1. A String is a Sequence
    • 5.1.1.1. Indexing
    • 5.1.1.2. Using len() with Strings
    • 5.1.1.3. Traversal Through a String with a Loop
    • 5.1.1.4. Slicing
    • 5.1.1.5. Strings are Immutable
    • 5.1.1.6. Looping and Counting
    • 5.1.1.7. The in Operator
  • 5.1.2. String Comparison
  • 5.1.3. string Objects and Methods
  • 5.1.4. Parsing Strings
  • 5.1.5. String Formatting with F-Strings
• 5.2. Lists
  • 5.2.1. A List is a Sequence
  • 5.2.2. Indexing (Lists are Mutable)
  • 5.2.3. Traversing a List
  • 5.2.4. List Operations
  • 5.2.5. List Methods
  • 5.2.6. Deleting elements
  • 5.2.7. Lists and Functions
  • 5.2.8. Lists and Strings
  • 5.2.9. Objects and Values
  • 5.2.10. References and Aliasing
  • 5.2.11. Common Pitfalls
• 5.3. Files
  • 5.3.1. Persistence
  • 5.3.2. Text Files and Lines
  • 5.3.3. Opening Files
  • 5.3.4. Reading Files
  • 5.3.5. Closing Files
  • 5.3.6. Searching Through a File
  • 5.3.7. Writing Files
  • 5.3.8. Debugging
• 5.4. Glossary