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Python for Data Science

Python Essentials for ML

Variables & Types, Through a Data Lens

7 min+55 XPStep 1/10

A variable is a labeled value

Open a notebook and type:

  • loss = 0.34
  • model_name = 'resnet'
  • is_done = True

Each line binds a name to a value — no declarations, no ceremony. loss is a float, model_name a string, is_done a bool. Ask Python what it made with type(loss) and it answers float.

In data work, types aren't bureaucracy — they're the first thing to check in every dataset, because a column's type decides what you're allowed to do with it.

analogy

A column's dtype is like a blank on a form: 'age' expects a number, 'name' expects text. Feed text where a number belongs and everything downstream breaks — quietly, at 2am.