Live Lecture 1.2

Cause and Effect, Names, Call Expressions,

Data Types, and Tables

Summer 2020

DATA 8

Spring 2020

Announcements

• Get DSP letters in by the end of the week!
• Midterm Conflict form due by Fri. 6/26 at midnight
• HW 1 due Thurs 6/25
• Update to lab checkoff policy

Agenda

1. Cause and Effect
2. Data Types
3. Names and Functions
4. Arrays and Tables

Cause and Effect

Two types of studies:

1. Observational - observe naturally occurring relationships in treatment status and outcome in participants
2. Experiments - participants are randomly assigned to a treatment group

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Confounding factors - systematic differences, other than the treatment itself, between the treatment and control group

Cause and Effect

Confounding factors are more common in observational studies.

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Why?

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• In observational studies, we’re observing the world in its “natural” state - including all its systemic biases

• In experiments, treatments are randomized so confounding factors are more evenly split between the control and treatment group

Agenda

• Cause and Effect
• Data Types
• Names and Functions
• Arrays and Tables

Data Types

Python has two real number types

• Int: an integer of any size (e.g. 1, 10, -5, 0)
• Convert to integer: int('12')
• Float: a number with an optional fractional part
• Convert to float: float('1.2')

Data Types

Python has two real number types

• Int: an integer of any size (e.g. 1, 10, -5, 0)
• Convert to integer: int('12')
• Float: a number with an optional fractional part
• Convert to float: float('1.2')

A string is a snippet of text of any length

• 'a'
• “there can be 2 sentences. Here's the second!”
• Convert to string: str(5)

• 'Word'

• '3.14'

Agenda

• Cause and Effect
• Data Types
• Names and Functions
• Arrays and Tables

Names and Call Expressions

f ( 27 )

"Call f on 27."

hours_per_wk = 24*7

Names:

Call Expressions:

Names and Call Expressions

f ( 27 )

"Call f on 27."

Call Expressions:

Toy Example:

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If we define f(x) = x + 1, then the snippet above would produce a value of 28

Agenda

• Cause and Effect
• Data Types
• Names and Functions
• Arrays and Tables

Arrays

An array contains a sequence of values

• All elements of an array should have the same type
• Arithmetic is applied to each element individually
• A column of a table is an array

DEMO

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A range is an array of consecutive numbers

• np.arange(end)
• np.arange(start, end)
• np.arange(start, end, step)

Table Structure

• A Table is a sequence of labeled columns
• Each row represents one individual
• Data within a column represents one attribute of the individuals

Some Table Operations

• t.select(label) - constructs a new table with just the specified columns
• t.drop(label) - constructs a new table in which the specified columns are omitted
• t.sort(label) - constructs a new table with rows sorted by the specified column
• t.where(label, condition) - constructs a new table with just the rows that match the condition

DEMO

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Recap and Questions