Working With Data
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Data Types Which data categories exist, and what are the differences?
Non-Parametric: - Categorical or discrete data; can be names, ID’s. They do not represent numerical values. Parametric: - Numerical data
Data Types Which category is the Data Type ‘Nominal’ in and what is it?
Category: Non-Parametric • Nominal: Simple Names or labels; e.g. car brand, gender.
Data Types Which category is the Data Type ‘Ordinal’ in and what is it?
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.
Data Types Which category is the Data Type ‘Interval’ in and what is it?
Category: Parametric Numerical data with even interval Interval: Numerical data representing real values evenly spaced or continuous.
Data Types Which category is the Data Type ‘Ratio’ in and what is it?
Category: Parametric As interval data, but with a true zero representation.
Taxonomies of Data Structured Data
Data in well-defined structures and atomic elements.
Taxonomies of Data Unstructured Data
Data that doesn’t follow a strict structure and is hard to represent in tables and columns, e.g. text, images, and video.
What is ‘Categorical Data’?
Same as Non-Parametric data. • Labels and categorical data: Simple names and labels such as gender, high
Taxonomies of Data Quantitative Data
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,.
What do we use NumPy for
Python module for high-performance nummerical computation.
What do we use Pandas for
Python module for high-performance data processing.