This lecture

Data organization (quick)
Doing stuff with data
Dimensions of representation

If time permits

Linked data
Grammar of Graphics
bqplot and dashboarding

Data organization: A few notes

Doing Stuff with Data

Now that we understand a few ways that data can be stored, let's do some things to it.

Doing stuff with data

You have a palette of operations to apply.

Filtering Operations

Relationships:
- Equality, inequality
- Quantitative value (less than, greater than)
- Intersection, disjoint
Subsampling
- Regular sampling
- Randomized sampling
- Nyquist frequency
Related data queries
- Queries on other columns at fixed row location
- External membership queries

Relationships Examples

Equality
- Identity
- Quantitative values
Ordering or quantitative
- Less than (or equal)
- Greater than (or equal)
- "Comes before" and "Comes after"
Set-based operations
- "Is a member"
- "Is not a member"
- "Shares members"
- "Shares no members"

Examples

Equality

value == "hello"
value == 10

Ordering and Quantitative

value < 30
value > July 1, 2010

Set-Based

value in ("red", "blue")
value not in (3.141, 2.7)

Examples

Equality

value == "hello"
value == 10

Ordering and Quantitative

value < 30
value > July 1, 2010

Set-Based

value in ("red", "blue")
value not in (3.141, 2.7)

We will often mask data to select just what we want to show.

Dimensions of representation

i.e. how can we represent data in visualizations?

Representing Quantities

We can encode the values associated with a data point by modifying how we express it. To do so, we need to be able to identify the different components of representation, and how we can scale between them.