Working With Data

Question 1

Data Types

Which data categories exist, and what are the differences?

Answer 1

Non-Parametric:
- Categorical or discrete data; can be names, ID’s. They do not represent numerical values.

Parametric:
- Numerical data

Question 2

Data Types

Which category is the Data Type ‘Nominal’ in and what is it?

Answer 2

Category: Non-Parametric

• Nominal: Simple Names or labels; e.g. car brand, gender.

Question 3

Data Types

Which category is the Data Type ‘Ordinal’ in and what is it?

Answer 3

Category: Non-Parametric

Ordinal: Ordered data; e.g Ranks in competition or military, first, second, third; level of education, high school, AP degree, bachelor’s degree.

Question 4

Data Types

Which category is the Data Type ‘Interval’ in and what is it?

Answer 4

Category: Parametric

Numerical data with even interval

Interval: Numerical data representing real values evenly spaced or continuous.

Question 5

Data Types

Which category is the Data Type ‘Ratio’ in and what is it?

Answer 5

Category: Parametric

As interval data, but with a true zero representation.

Question 6

Taxonomies of Data

Structured Data

Answer 6

Data in well-defined structures and atomic elements.

Question 7

Taxonomies of Data

Unstructured Data

Answer 7

Data that doesn’t follow a strict structure and is hard to represent in tables and columns, e.g. text, images, and video.

Question 8

What is ‘Categorical Data’?

Answer 8

Same as Non-Parametric data.

• Labels and categorical data: Simple names and labels such as gender, high

Question 9

Taxonomies of Data

Quantitative Data

Answer 9

Same as Parametric

Interval data, representing real values that are evenly spaced. e.g. 1 is half of 2 and 4 is double of what 2 is,.

Question 10

What do we use NumPy for

Answer 10

Python module for high-performance nummerical computation.

Question 11

What do we use Pandas for

Answer 11

Python module for high-performance data processing.