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Practice

Variables and Data Types

Before you analyze anything, you need a way to store values in memory and refer to them later.
This is where variables come in — they let you name pieces of information that your code can use again and again.


Why Variables Matter​

In data analysis, you deal with values like scores, prices, temperatures, or timestamps.
Instead of writing those values over and over, we store them in variables.

This makes your code:

  • Easier to read
  • Easier to update
  • More flexible for re-use

Imagine managing data for a coffee shop: storing the average order price in a variable like avg_order is clearer than writing 4.75 everywhere.


What About Data Types?​

Python doesn’t treat all values the same. It automatically assigns each variable a type based on the value you assign.

This is important because:

  • You can only do certain actions with certain types
  • Knowing the type helps avoid errors (e.g. adding a number to a string won’t work)

As you work with real datasets, you’ll often need to check or convert types before analysis.


The Analyst’s Perspective​

A good analyst not only writes correct code, but also keeps it clean and understandable.

Using well-named variables and understanding how types behave will make your work easier to debug, share, and explain.


Coming Up​

Next, you'll learn how to write expressions and perform calculations using Python’s arithmetic operators.

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